WorldWideScience

Sample records for spatial-temporal gene-expression information

  1. Selective 4D modelling framework for spatial-temporal land information management system

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    Doulamis, Anastasios; Soile, Sofia; Doulamis, Nikolaos; Chrisouli, Christina; Grammalidis, Nikos; Dimitropoulos, Kosmas; Manesis, Charalambos; Potsiou, Chryssy; Ioannidis, Charalabos

    2015-06-01

    This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

  2. Evaluation of gene-expression clustering via mutual information distance measure

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    Maimon Oded

    2007-03-01

    Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

  3. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

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    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network

  4. Blood-informative transcripts define nine common axes of peripheral blood gene expression.

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    Marcela Preininger

    Full Text Available We describe a novel approach to capturing the covariance structure of peripheral blood gene expression that relies on the identification of highly conserved Axes of variation. Starting with a comparison of microarray transcriptome profiles for a new dataset of 189 healthy adult participants in the Emory-Georgia Tech Center for Health Discovery and Well-Being (CHDWB cohort, with a previously published study of 208 adult Moroccans, we identify nine Axes each with between 99 and 1,028 strongly co-regulated transcripts in common. Each axis is enriched for gene ontology categories related to sub-classes of blood and immune function, including T-cell and B-cell physiology and innate, adaptive, and anti-viral responses. Conservation of the Axes is demonstrated in each of five additional population-based gene expression profiling studies, one of which is robustly associated with Body Mass Index in the CHDWB as well as Finnish and Australian cohorts. Furthermore, ten tightly co-regulated genes can be used to define each Axis as "Blood Informative Transcripts" (BITs, generating scores that define an individual with respect to the represented immune activity and blood physiology. We show that environmental factors, including lifestyle differences in Morocco and infection leading to active or latent tuberculosis, significantly impact specific axes, but that there is also significant heritability for the Axis scores. In the context of personalized medicine, reanalysis of the longitudinal profile of one individual during and after infection with two respiratory viruses demonstrates that specific axes also characterize clinical incidents. This mode of analysis suggests the view that, rather than unique subsets of genes marking each class of disease, differential expression reflects movement along the major normal Axes in response to environmental and genetic stimuli.

  5. Blood-informative transcripts define nine common axes of peripheral blood gene expression.

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    Preininger, Marcela; Arafat, Dalia; Kim, Jinhee; Nath, Artika P; Idaghdour, Youssef; Brigham, Kenneth L; Gibson, Greg

    2013-01-01

    We describe a novel approach to capturing the covariance structure of peripheral blood gene expression that relies on the identification of highly conserved Axes of variation. Starting with a comparison of microarray transcriptome profiles for a new dataset of 189 healthy adult participants in the Emory-Georgia Tech Center for Health Discovery and Well-Being (CHDWB) cohort, with a previously published study of 208 adult Moroccans, we identify nine Axes each with between 99 and 1,028 strongly co-regulated transcripts in common. Each axis is enriched for gene ontology categories related to sub-classes of blood and immune function, including T-cell and B-cell physiology and innate, adaptive, and anti-viral responses. Conservation of the Axes is demonstrated in each of five additional population-based gene expression profiling studies, one of which is robustly associated with Body Mass Index in the CHDWB as well as Finnish and Australian cohorts. Furthermore, ten tightly co-regulated genes can be used to define each Axis as "Blood Informative Transcripts" (BITs), generating scores that define an individual with respect to the represented immune activity and blood physiology. We show that environmental factors, including lifestyle differences in Morocco and infection leading to active or latent tuberculosis, significantly impact specific axes, but that there is also significant heritability for the Axis scores. In the context of personalized medicine, reanalysis of the longitudinal profile of one individual during and after infection with two respiratory viruses demonstrates that specific axes also characterize clinical incidents. This mode of analysis suggests the view that, rather than unique subsets of genes marking each class of disease, differential expression reflects movement along the major normal Axes in response to environmental and genetic stimuli.

  6. Gene expression

    International Nuclear Information System (INIS)

    Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

    1983-01-01

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  7. Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

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    Sura Zaki Alrashid

    2018-02-01

    Full Text Available Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlation between such genes,more information is gain within the cluster about how the genes interrelate. Amyotrophic lateral sclerosis (ALS is an irreversible neurodegenerative disorder that kills the motor neurons and results in death within 2 to 3 years from the symptom onset. Speed of progression for different patients are heterogeneous with significant variability. The SOD1G93A transgenic mice from different backgrounds (129Sv and C57 showed consistent phenotypic differences for disease progression. A hierarchy of Gaussian isused processes to model condition-specific and gene-specific temporal co-variances. This study demonstrated about finding some significant gene expression profiles and clusters of associated or co-regulated gene expressions together from four groups of data (SOD1G93A and Ntg from 129Sv and C57 backgrounds. Our study shows the effectiveness of sharing information between replicates and different model conditions when modelling gene expression time series. Further gene enrichment score analysis and ontology pathway analysis of some specified clusters for a particular group may lead toward identifying features underlying the differential speed of disease progression.

  8. Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.

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    Tchagang, Alain B; Phan, Sieu; Famili, Fazel; Shearer, Heather; Fobert, Pierre; Huang, Yi; Zou, Jitao; Huang, Daiqing; Cutler, Adrian; Liu, Ziying; Pan, Youlian

    2012-04-04

    Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.

  9. Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

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    Zhang, Ao; Tian, Suyan

    2018-05-01

    Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. A novel mutual information-based Boolean network inference method from time-series gene expression data.

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    Shohag Barman

    Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.

  11. Spatial-temporal cluster analysis of mortality from road traffic injuries using geographic information systems in West of Iran during 2009-2014.

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    Zangeneh, Alireza; Najafi, Farid; Karimi, Saeed; Saeidi, Shahram; Izadi, Neda

    2018-04-01

    Road traffic injuries (RTIs) are considered as one of the most important health problems endangering people's life. The examination of the geographical distribution of RTIs could help policymakers in better planning to reduce RTIs. This study, therefore, aimed to determine the spatial-temporal clustering of mortality from RTIs in West of Iran. Deaths from RTIs, registered in Forensic Medicine Organization of Kermanshah province over a period of six years (2009-2014), were used. Using negative binomial regression, the mortality trend was investigated. In order to investigate the spatial distribution of RTIs, we used ArcGIS. (Version 10.3). The median age of the 3231 people died in RTIs was 37 (IQR = 31) year, 78.4% were male. The 6-year average mortality rate from RTIs was 27.8/100,000 deaths, and the average rate had a declining trend. The dispersion of RTIs showed that most deaths occurred in Kermanshah, Islamabad, Bisotun, and Harsin road axes, respectively. The mean center of all deaths from RTIs occurred in Kermanshah province, the central area of Kermanshah district. The spatial trend of such deaths has moved to the northeast-southwest, and such deaths were geographically centralized. Results of Moran's I with respect to cluster analysis also indicated positive spatial autocorrelations. The results showed that the mortality rate from RTIs, despite the decline in recent years, is still high when compared with other countries. The clustering of accidents raises the concern that road infrastructure in certain locations may also be a factor. Regarding the results related to the temporal analysis, it is suggested that the enforcement of traffic rules be stricter at rush hours. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  12. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

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    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  13. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

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    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  14. Gene expression from polynomial dynamics in the 2-adic information space

    International Nuclear Information System (INIS)

    Khrennikov, Andrei Yu.

    2009-01-01

    We perform geometrization of genetics by representing genetic information by points of the 4-adic information space. By well known theorem of number theory this space can also be represented as the 2-adic space. The process of DNA-reproduction is described by the action of a 4-adic (or equivalently 2-adic) dynamical system. As we know, the genes contain information for production of proteins. The genetic code is a degenerate map of codons to proteins. We model this map as functioning of a polynomial dynamical system. The purely mathematical problem under consideration is to find a dynamical system reproducing the degenerate structure of the genetic code. We present one of possible solutions of this problem.

  15. Missing value imputation for microarray gene expression data using histone acetylation information

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    Feng Jihua

    2008-05-01

    Full Text Available Abstract Background It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. Results The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor and LLS(local least square imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE. Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information. Conclusion We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

  16. Mechanisms of information decoding in a cascade system of gene expression

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    Wang, Haohua; Yuan, Zhanjiang; Liu, Peijiang; Zhou, Tianshou

    2016-05-01

    Biotechnology advances have allowed investigation of heterogeneity of cellular responses to stimuli on the single-cell level. Functionally, this heterogeneity can compromise cellular responses to environmental signals, and it can also enlarge the repertoire of possible cellular responses and hence increase the adaptive nature of cellular behaviors. However, the mechanism of how this response heterogeneity is generated remains elusive. Here, by systematically analyzing a representative cellular signaling system, we show that (1) the upstream activator always amplifies the downstream burst frequency (BF) but the noiseless activator performs better than the noisy one, remarkably for small or moderate input signal strengths, and the repressor always reduces the downstream BF but the difference in the reducing effect between noiseless and noise repressors is very small; (2) both the downstream burst size and mRNA mean are a monotonically increasing function of the activator strength but a monotonically decreasing function of the repressor strength; (3) for repressor-type input, there is a noisy signal strength such that the downstream mRNA noise arrives at an optimal level, but for activator-type input, the output noise intensity is fundamentally a monotonically decreasing function of the input strength. Our results reveal the essential mechanisms of both signal information decoding and cellular response heterogeneity, whereas our analysis provides a paradigm for analyzing dynamics of noisy biochemical signaling systems.

  17. Human Plague Risk: Spatial-Temporal Models

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    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  18. The use of a priori information in ICA-based techniques for real-time fMRI: an evaluation of static/dynamic and spatial/temporal characteristics

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    Nicola eSoldati

    2013-03-01

    Full Text Available Real-time brain functional MRI (rt-fMRI allows in-vivo non-invasive monitoring of neural networks. The use of multivariate data-driven analysis methods such as independent component analysis (ICA offers an attractive trade-off between data interpretability and information extraction, and can be used during both task-based and rest experiments. The purpose of this study was to assess the effectiveness of different ICA-based procedures to monitor in real-time a target IC defined from a functional localizer which also used ICA. Four novel methods were implemented to monitor ongoing brain activity in a sliding window approach. The methods differed in the ways in which a priori information, derived from ICA algorithms, was used to monitora target independent component (IC. We implemented four different algorithms, all based on ICA. One Back-projection method used ICA to derive static spatial information from the functional localizer, off line, which was then back-projected dynamically during the real-time acquisition. The other three methods used real-time ICA algorithms that dynamically exploited temporal, spatial, or spatial-temporal priors during the real-time acquisition. The methods were evaluated by simulating a rt-fMRI experiment that used real fMRI data. The performance of each method was characterized by the spatial and/or temporal correlation with the target IC component monitored, computation time and intrinsic stochastic variability of the algorithms. In this study the Back-projection method, which could monitor more than one IC of interest, outperformed the other methods. These results are consistent with a functional task that gives stable target ICs over time. The dynamic adaptation possibilities offered by the other ICA methods proposed may offer better performance than the Back-projection in conditions where the functional activation shows higher spatial and/or temporal variability.

  19. Spatial-Temporal Clustering of Tornadoes

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    Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

    2017-04-01

    The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated

  20. Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

    OpenAIRE

    Sura Zaki Alrashid; Muhammad Arifur Rahman; Nabeel H Al-Aaraji; Neil D Lawrence; Paul R Heath

    2018-01-01

    Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlati...

  1. Gene Expression Omnibus (GEO)

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    U.S. Department of Health & Human Services — Gene Expression Omnibus is a public functional genomics data repository supporting MIAME-compliant submissions of array- and sequence-based data. Tools are provided...

  2. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

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    Pugalendhi Ganesh Kumar

    Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively

  3. Action Recognition by Joint Spatial-Temporal Motion Feature

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    Weihua Zhang

    2013-01-01

    Full Text Available This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance without reducing accuracy is induced. The main contributions of this study include (1 a joint spatial-temporal multiresolution optical flow computation method which can keep encoding more informative motion information than recent proposed methods, (2 an enhanced DTW method to improve temporal consistence of motion in action recognition, and (3 coarse-to-fine DTW constraint on motion features pyramids to speed up recognition performance. Using this method, high recognition accuracy is achieved on different action databases like Weizmann database and KTH database.

  4. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

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    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  5. Spatial-temporal data model and fractal analysis of transportation network in GIS environment

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    Feng, Yongjiu; Tong, Xiaohua; Li, Yangdong

    2008-10-01

    How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

  6. Spatial-temporal modeling of malware propagation in networks.

    Science.gov (United States)

    Chen, Zesheng; Ji, Chuanyi

    2005-09-01

    Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.

  7. Spatial-Temporal Event Detection from Geo-Tagged Tweets

    Directory of Open Access Journals (Sweden)

    Yuqian Huang

    2018-04-01

    Full Text Available As one of the most popular social networking services in the world, Twitter allows users to post messages along with their current geographic locations. Such georeferenced or geo-tagged Twitter datasets can benefit location-based services, targeted advertising and geosocial studies. Our study focused on the detection of small-scale spatial-temporal events and their textual content. First, we used Spatial-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN to spatially-temporally cluster the tweets. Then, the word frequencies were summarized for each cluster and the potential topics were modeled by the Latent Dirichlet Allocation (LDA algorithm. Using two years of Twitter data from four college cities in the U.S., we were able to determine the spatial-temporal patterns of two known events, two unknown events and one recurring event, which then were further explored and modeled to identify the semantic content about the events. This paper presents our process and recommendations for both finding event-related tweets as well as understanding the spatial-temporal behaviors and semantic natures of the detected events.

  8. A comparative gene expression database for invertebrates

    Directory of Open Access Journals (Sweden)

    Ormestad Mattias

    2011-08-01

    Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of gene expression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling gene expression patterns from a variety of organisms, we have developed the first web-based comparative gene expression database for invertebrates that allows species-specific as well as cross-species gene expression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of gene expression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

  9. Developing a spatial-temporal method for the geographic investigation of shoeprint evidence.

    Science.gov (United States)

    Lin, Ge; Elmes, Gregory; Walnoha, Mike; Chen, Xiannian

    2009-01-01

    This article examines the potential of a spatial-temporal method for analysis of forensic shoeprint data. The large volume of shoeprint evidence recovered at crime scenes results in varied success in matching a print to a known shoe type and subsequently linking sets of matched prints to suspected offenders. Unlike DNA and fingerprint data, a major challenge is to reduce the uncertainty in linking sets of matched shoeprints to a suspected serial offender. Shoeprint data for 2004 were imported from the Greater London Metropolitan Area Bigfoot database into a geographic information system, and a spatial-temporal algorithm developed for this project. The results show that by using distance and time constraints interactively, the number of candidate shoeprints that can implicate one or few suspects can be substantially reduced. It concludes that the use of space-time and other ancillary information within a geographic information system can be quite helpful for forensic investigation.

  10. Spatial-temporal changes in phytoplankton biomass and primary ...

    African Journals Online (AJOL)

    Spatial-temporal variations in phytoplankton primary production (PP) and biomass (B) were studied for a period of about one year, from July 1999 to July 2000. In addition, changes in corresponding environmental variables were examined. Sampling took place at two stations in Chwaka Bay, one located in mangrove areas, ...

  11. Visualization of spatial-temporal data based on 3D virtual scene

    Science.gov (United States)

    Wang, Xianghong; Liu, Jiping; Wang, Yong; Bi, Junfang

    2009-10-01

    The main purpose of this paper is to realize the expression of the three-dimensional dynamic visualization of spatialtemporal data based on three-dimensional virtual scene, using three-dimensional visualization technology, and combining with GIS so that the people's abilities of cognizing time and space are enhanced and improved by designing dynamic symbol and interactive expression. Using particle systems, three-dimensional simulation, virtual reality and other visual means, we can simulate the situations produced by changing the spatial location and property information of geographical entities over time, then explore and analyze its movement and transformation rules by changing the interactive manner, and also replay history and forecast of future. In this paper, the main research object is the vehicle track and the typhoon path and spatial-temporal data, through three-dimensional dynamic simulation of its track, and realize its timely monitoring its trends and historical track replaying; according to visualization techniques of spatialtemporal data in Three-dimensional virtual scene, providing us with excellent spatial-temporal information cognitive instrument not only can add clarity to show spatial-temporal information of the changes and developments in the situation, but also be used for future development and changes in the prediction and deduction.

  12. Differential Gene Expression and Aging

    Directory of Open Access Journals (Sweden)

    Laurent Seroude

    2002-01-01

    Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

  13. Regulation of mitochondrial gene expression, the epigenetic enigma

    NARCIS (Netherlands)

    Mposhi, Archibold; van der Wijst, Monique G. P.; Faber, Klaas Nico; Rots, Marianne G.

    2017-01-01

    Epigenetics provides an important layer of information on top of the DNA sequence and is essential for establishing gene expression profiles. Extensive studies have shown that nuclear DNA methylation and histone modifications influence nuclear gene expression. However, it remains unclear whether

  14. Spatial-temporal event detection in climate parameter imagery.

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  15. Spatial-temporal migration laws of Cd in Jiaozhou Bay

    Science.gov (United States)

    Yang, Dongfang; Li, Haixia; Zhang, Xiaolong; Wang, Qi; Miao, Zhenqing

    2018-02-01

    Many marine bays have been polluted by various pollutants, and understanding the migration laws is essential to scientific research and pollution control. This paper analyzed the spatial and temporal migration laws of Cd in waters in Jiaozhou Bay during 1979—1983. Results showed that there were twenty spatial-temporal migration law for the migration processes of Cd. These laws were helpful for better understanding the migration of Cd in marine bay, providing basis for scientific research and pollution control.

  16. Correction of gene expression data

    DEFF Research Database (Denmark)

    Darbani Shirvanehdeh, Behrooz; Stewart, C. Neal, Jr.; Noeparvar, Shahin

    2014-01-01

    This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies....... For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce...

  17. Analysis of baseline gene expression levels from ...

    Science.gov (United States)

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  18. Metallothionein gene expression in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Deeksha Pal

    2014-01-01

    Full Text Available Introduction: Metallothioneins (MTs are a group of low-molecular weight, cysteine-rich proteins. In general, MT is known to modulate three fundamental processes: (1 the release of gaseous mediators such as hydroxyl radical or nitric oxide, (2 apoptosis and (3 the binding and exchange of heavy metals such as zinc, cadmium or copper. Previous studies have shown a positive correlation between the expression of MT with invasion, metastasis and poor prognosis in various cancers. Most of the previous studies primarily used immunohistochemistry to analyze localization of MT in renal cell carcinoma (RCC. No information is available on the gene expression of MT2A isoform in different types and grades of RCC. Materials and Methods: In the present study, total RNA was isolated from 38 histopathologically confirmed cases of RCC of different types and grades. Corresponding adjacent normal renal parenchyma was taken as control. Real-time polymerase chain reaction (RT PCR analysis was done for the MT2A gene expression using b-actin as an internal control. All statistical calculations were performed using SPSS software. Results: The MT2A gene expression was found to be significantly increased (P < 0.01 in clear cell RCC in comparison with the adjacent normal renal parenchyma. The expression of MT2A was two to three-fold higher in sarcomatoid RCC, whereas there was no change in papillary and collecting duct RCC. MT2A gene expression was significantly higher in lower grade (grades I and II, P < 0.05, while no change was observed in high-grade tumor (grade III and IV in comparison to adjacent normal renal tissue. Conclusion: The first report of the expression of MT2A in different types and grades of RCC and also these data further support the role of MT2A in tumorigenesis.

  19. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  20. Analysis of multiplex gene expression maps obtained by voxelation

    OpenAIRE

    An, L; Xie, H; Chin, MH; Obradovic, Z; Smith, DJ; Megalooikonomou, V

    2009-01-01

    Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we presen...

  1. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-01-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  2. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-05-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  3. A constructive approach to gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2004-01-01

    Recently, experiments on mRNA abundance (gene expression) have revealed that gene expression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to gene expression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

  4. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder

    2002-01-01

    Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

  5. Gene expression in periodontal tissues following treatment

    Directory of Open Access Journals (Sweden)

    Eisenacher Martin

    2008-07-01

    Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on gene expression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to gene expression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressed genes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressed genes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Gene expression profiles found in periodontal tissues following

  6. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  7. Integrated olfactory receptor and microarray gene expression databases

    Directory of Open Access Journals (Sweden)

    Crasto Chiquito J

    2007-06-01

    Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

  8. Network Security via Biometric Recognition of Patterns of Gene Expression

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

    Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT (Information Technology) organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time assays of gene expression products.

  9. Spatial-temporal dynamics of broadband terahertz Bessel beam propagation

    International Nuclear Information System (INIS)

    Semenova, V A; Kulya, M S; Bespalov, V G

    2016-01-01

    The unique properties of narrowband and broadband terahertz Bessel beams have led to a number of their applications in different fields, for example, for the depth of focusing and resolution enhancement in terahertz imaging. However, broadband terahertz Bessel beams can probably be also used for the diffraction minimization in the short-range broadband terahertz communications. For this purpose, the study of spatial-temporal dynamics of the broadband terahertz Bessel beams is needed. Here we present a simulation-based study of the propagating in non-dispersive medium broadband Bessel beams generated by a conical axicon lens. The algorithm based on scalar diffraction theory was used to obtain the spatial amplitude and phase distributions of the Bessel beam in the frequency range from 0.1 to 3 THz at the distances 10-200 mm from the axicon. Bessel beam field is studied for the different spectral components of the initial pulse. The simulation results show that for the given parameters of the axicon lens one can obtain the Gauss-Bessel beam generation in the spectral range from 0.1 to 3 THz. The length of non-diffraction propagation for a different spectral components was measured, and it was shown that for all spectral components of the initial pulse this length is about 130 mm. (paper)

  10. Spatial Temporal Modelling of Particulate Matter for Health Effects Studies

    Science.gov (United States)

    Hamm, N. A. S.

    2016-10-01

    Epidemiological studies of the health effects of air pollution require estimation of individual exposure. It is not possible to obtain measurements at all relevant locations so it is necessary to predict at these space-time locations, either on the basis of dispersion from emission sources or by interpolating observations. This study used data obtained from a low-cost sensor network of 32 air quality monitoring stations in the Dutch city of Eindhoven, which make up the ILM (innovative air (quality) measurement system). These stations currently provide PM10 and PM2.5 (particulate matter less than 10 and 2.5 m in diameter), aggregated to hourly means. The data provide an unprecedented level of spatial and temporal detail for a city of this size. Despite these benefits the time series of measurements is characterized by missing values and noisy values. In this paper a space-time analysis is presented that is based on a dynamic model for the temporal component and a Gaussian process geostatistical for the spatial component. Spatial-temporal variability was dominated by the temporal component, although the spatial variability was also substantial. The model delivered accurate predictions for both isolated missing values and 24-hour periods of missing values (RMSE = 1.4 μg m-3 and 1.8 μg m-3 respectively). Outliers could be detected by comparison to the 95% prediction interval. The model shows promise for predicting missing values, outlier detection and for mapping to support health impact studies.

  11. Network Security via Biometric Recognition of Patterns of Gene Expression

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

    Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time expression and assay of gene expression products.

  12. Analysis of multiplex gene expression maps obtained by voxelation.

    Science.gov (United States)

    An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

    2009-04-29

    Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

  13. Analysis of multiplex gene expression maps obtained by voxelation

    Directory of Open Access Journals (Sweden)

    Smith Desmond J

    2009-04-01

    Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

  14. Gene expression profile of pulpitis.

    Science.gov (United States)

    Galicia, J C; Henson, B R; Parker, J S; Khan, A A

    2016-06-01

    The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in gene expression levels were determined by the significance analysis of microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (⩾30 mm on VAS) compared with those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology.

  15. Coordinated Regulation of Anthocyanin Biosynthesis Genes Confers Varied Phenotypic and Spatial-Temporal Anthocyanin Accumulation in Radish (Raphanus sativus L.

    Directory of Open Access Journals (Sweden)

    Everlyne M'mbone Muleke

    2017-07-01

    Full Text Available Anthocyanins are natural pigments that have important functions in plant growth and development. Radish taproots are rich in anthocyanins which confer different taproot colors and are potentially beneficial to human health. The crop differentially accumulates anthocyanin during various stages of growth, yet molecular mechanisms underlying this differential anthocyanin accumulation remains unknown. In the present study, transcriptome analysis was used to concisely identify putative genes involved in anthocyanin biosynthesis in radish. Spatial-temporal transcript expressions were then profiled in four color variant radish cultivars. From the total transcript sequences obtained through illumina sequencing, 102 assembled unigenes, and 20 candidate genes were identified to be involved in anthocyanin biosynthesis. Fifteen genomic sequences were isolated and sequenced from radish taproot. The length of these sequences was between 900 and 1,579 bp, and the unigene coverage to all of the corresponding cloned sequences was more than 93%. Gene structure analysis revealed that RsF3′H is intronless and anthocyanin biosynthesis genes (ABGs bear asymmetrical exons, except RsSAM. Anthocyanin accumulation showed a gradual increase in the leaf of the red radish and the taproot of colored cultivars during development, with a rapid increase at 30 days after sowing (DAS, and the highest content at maturity. Spatial-temporal transcriptional analysis of 14 genes revealed detectable expressions of 12 ABGs in various tissues at different growth levels. The investigation of anthocyanin accumulation and gene expression in four color variant radish cultivars, at different stages of development, indicated that total anthocyanin correlated with transcript levels of ABGs, particularly RsUFGT, RsF3H, RsANS, RsCHS3 and RsF3′H1. Our results suggest that these candidate genes play key roles in phenotypic and spatial-temporal anthocyanin accumulation in radish through

  16. Social Content Recommendation Based on Spatial-Temporal Aware Diffusion Modeling in Social Networks

    Directory of Open Access Journals (Sweden)

    Farman Ullah

    2016-09-01

    Full Text Available User interactions in online social networks (OSNs enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme.

  17. Analysis of gene expression in normal and neoplastic human testis: new roles of RNA

    DEFF Research Database (Denmark)

    Novotny, G W; Nielsen, J E; Sonne, Si Brask

    2007-01-01

    Large-scale methods for analysing gene expression, such as microarrays, have yielded a wealth of information about gene expression at the mRNA level. However, expression of alternative transcripts, together with the presence of a wide range of largely undescribed RNA transcripts combined with reg......Large-scale methods for analysing gene expression, such as microarrays, have yielded a wealth of information about gene expression at the mRNA level. However, expression of alternative transcripts, together with the presence of a wide range of largely undescribed RNA transcripts combined...

  18. Serial analysis of gene expression (SAGE)

    NARCIS (Netherlands)

    van Ruissen, Fred; Baas, Frank

    2007-01-01

    In 1995, serial analysis of gene expression (SAGE) was developed as a versatile tool for gene expression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

  19. Genetic architecture of gene expression in ovine skeletal muscle

    DEFF Research Database (Denmark)

    Kogelman, Lisette Johanna Antonia; Byrne, Keren; Vuocolo, Tony

    2011-01-01

    architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value...... has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny...

  20. Adaptive Evolution of Gene Expression in Drosophila

    Directory of Open Access Journals (Sweden)

    Armita Nourmohammad

    2017-08-01

    Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

  1. Modeling gene expression measurement error: a quasi-likelihood approach

    Directory of Open Access Journals (Sweden)

    Strimmer Korbinian

    2003-03-01

    Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

  2. A compendium of canine normal tissue gene expression.

    Directory of Open Access Journals (Sweden)

    Joseph Briggs

    Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

  3. RNA preparation and characterization for gene expression studies

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Much information can be obtained from knowledge of the relative expression level of each gene in the transcriptome. With the current advances in technology as little as a single cell is required as starting material for gene expression experiments. The mRNA from a single cell may be linearly...

  4. Qualitative analysis of mouse specific-locus mutations: information on genetic organization, gene expression, and the chromosomal nature of induced lesions

    International Nuclear Information System (INIS)

    Russell, L.B.

    1982-01-01

    Analysis of mouse specific-locus (SL) mutations at three loci has identified over 33 distinct complementation groups - most of which are probably overlapping deficiencies - and 13 to 14 new functional units. The complementation maps that have been generated for the d-se and c regions include numerous vital functions; however, some of the genes in these regions are non-vital. At such loci, hypomorphic mutants must represent intragenic alterations, and some viable nulls could conceivably be intragenic lesions also. Analysis of SL mutations has provided information on genetic expression. Homozygous deficiencies can be completely viable or can kill at any one of a range of developmental stages. Heterozygonus deficiencies of up to 6 cM or more in genetic length have been recovered and propagated. The time of death of homozygous and the degree of inviability of heterozygous deficiencies are related more to specific content of the missing segment than to its length. Combinations of deficiencies with x-autosome translocations that inactivate the homologous region in a mosaic fashion have shown that organismic lethals are not necessarily cell lethal. The spectrum of mutations induced depends on the nature of the mutagen and the type of germ cell exposed. Radiation of spermatogonia produces intragenic as well as null mutations. Spontaneous mutations have an admixture of types not present in populations of mutations induced in germ cells, and this raises doubts concerning the accuracy of doubling-dose calculations in genetic risk estimation. The analysis of SL mutations has yielded genetic tools for the construction of detailed gene-dosage series, cis-trans comparisons, the mapping of known genes and identification of new genes, genetic rescue of various types, and the identification and isolation of DNA sequences

  5. Applying Spatial-Temporal Model and Game Theory to Asymmetric Threat Prediction

    National Research Council Canada - National Science Library

    Wei, Mo; Chen, Genshe; Cruz, Jr., Jose B; Haynes, Leonard; Kruger, Martin

    2007-01-01

    .... In most Command and Control "C2" applications, the existing techniques, such as spatial-temporal point models for ECOA prediction or Discrete Choice Model "DCM", assume that insurgent attack features...

  6. EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

    KAUST Repository

    Tian, Tian Siva; Huang, Jianhua Z.; Shen, Haipeng; Li, Zhimin

    2013-01-01

    In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously

  7. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    blood glucose > 16.7 mmol/L were used as the model group and treated with Dendrobium mixture. (DEN ... Keywords: Diabetes, Gene expression, Dendrobium mixture, Microarray testing ..... homeostasis in airway smooth muscle. Am J.

  8. Drosophila melanogaster gene expression changes after spaceflight.

    Data.gov (United States)

    National Aeronautics and Space Administration — Gene expression levels were determined in 3rd instar and adult Drosophila melanogaster reared during spaceflight to elucidate the genetic and molecular mechanisms...

  9. Exertional Heat Illness and Human Gene Expression

    National Research Council Canada - National Science Library

    Sonna, L.A; Sawka, M. N; Lilly, C. M

    2007-01-01

    Microarray analysis of gene expression at the level of RNA has generated new insights into the relationship between cellular responses to acute heat shock in vitro, exercise, and exertional heat illness...

  10. Gene expression and gene therapy imaging

    International Nuclear Information System (INIS)

    Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

    2007-01-01

    The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

  11. Occlusion-Aware Fragment-Based Tracking With Spatial-Temporal Consistency.

    Science.gov (United States)

    Sun, Chong; Wang, Dong; Lu, Huchuan

    2016-08-01

    In this paper, we present a robust tracking method by exploiting a fragment-based appearance model with consideration of both temporal continuity and discontinuity information. From the perspective of probability theory, the proposed tracking algorithm can be viewed as a two-stage optimization problem. In the first stage, by adopting the estimated occlusion state as a prior, the optimal state of the tracked object can be obtained by solving an optimization problem, where the objective function is designed based on the classification score, occlusion prior, and temporal continuity information. In the second stage, we propose a discriminative occlusion model, which exploits both foreground and background information to detect the possible occlusion, and also models the consistency of occlusion labels among different frames. In addition, a simple yet effective training strategy is introduced during the model training (and updating) process, with which the effects of spatial-temporal consistency are properly weighted. The proposed tracker is evaluated by using the recent benchmark data set, on which the results demonstrate that our tracker performs favorably against other state-of-the-art tracking algorithms.

  12. Object-oriented spatial-temporal association rules mining on ocean remote sensing imagery

    International Nuclear Information System (INIS)

    Xue, C J; Dong, Q; Ma, W X

    2014-01-01

    Using the long term marine remote sensing imagery, we develop an object-oriented spatial-temporal association rules mining framework to explore the association rules mining among marine environmental elements. Within the framework, two key issues are addressed. They are how to effectively deal with the related lattices and how to reduce the related dimensions? To deal with the first key issues, this paper develops an object-oriented method for abstracting marine sensitive objects from raster pixels and for representing them with a quadruple. To deal with the second key issues, by embedding the mutual information theory, we construct the direct association pattern tree to reduce the related elements at the first step, and then the Apriori algorithm is used to discover the spatio-temporal associated rules. Finally, Pacific Ocean is taken as a research area and multi- marine remote sensing imagery in recent three decades is used as a case study. The results show that the object-oriented spatio-temporal association rules mining can acquire the associated relationships not only among marine environmental elements in same region, also among the different regions. In addition, the information from association rules mining is much more expressive and informative in space and time than traditional spatio-temporal analysis

  13. Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

    OpenAIRE

    Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

    2016-01-01

    Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

  14. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jacobs Kevin

    2007-08-01

    Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

  15. Dynamic association rules for gene expression data analysis.

    Science.gov (United States)

    Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

    2015-10-14

    The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

  16. Adaptive Evolution of Gene Expression in Drosophila.

    Science.gov (United States)

    Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

    2017-08-08

    Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator

    Directory of Open Access Journals (Sweden)

    Nuno Eduardo Simões

    2015-06-01

    Full Text Available It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2 located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.

  18. Lithium ions induce prestalk-associated gene expression and inhibit prespore gene expression in Dictyostelium discoideum

    NARCIS (Netherlands)

    Peters, Dorien J.M.; Lookeren Campagne, Michiel M. van; Haastert, Peter J.M. van; Spek, Wouter; Schaap, Pauline

    1989-01-01

    We investigated the effect of Li+ on two types of cyclic AMP-regulated gene expression and on basal and cyclic AMP-stimulated inositol 1,4,5-trisphosphate (Ins(1,4,5)P3) levels. Li+ effectively inhibits cyclic AMP-induced prespore gene expression, half-maximal inhibition occurring at about 2mM-LiCl.

  19. Scaling of gene expression data allowing the comparison of different gene expression platforms

    NARCIS (Netherlands)

    van Ruissen, Fred; Schaaf, Gerben J.; Kool, Marcel; Baas, Frank; Ruijter, Jan M.

    2008-01-01

    Serial analysis of gene expression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce

  20. Regulation of Gene Expression in Protozoa Parasites

    Directory of Open Access Journals (Sweden)

    Consuelo Gomez

    2010-01-01

    Full Text Available Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  1. Regulation of gene expression in protozoa parasites.

    Science.gov (United States)

    Gomez, Consuelo; Esther Ramirez, M; Calixto-Galvez, Mercedes; Medel, Olivia; Rodríguez, Mario A

    2010-01-01

    Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  2. Stochastic gene expression in Arabidopsis thaliana.

    Science.gov (United States)

    Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

    2017-12-14

    Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

  3. Deriving Trading Rules Using Gene Expression Programming

    Directory of Open Access Journals (Sweden)

    Adrian VISOIU

    2011-01-01

    Full Text Available This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Gene expression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the gene expression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

  4. The effect of the Mozart Sonata for Two Pianos in D Major on the spatial-temporal reasoning

    Directory of Open Access Journals (Sweden)

    Katarina Habe

    2006-12-01

    Full Text Available The influence of music on cognitive functioning was investigated with the Mozart effect, i. e. the increase in spatial-temporal reasoning performance immediately after exposure to the Mozart piano sonata K.448. The experiment was performed on the sample of 315 students. Based on the results of the main experiment, two groups were formed: the enhancement group (N = 30 and the stagnation group (N = 30. Differences between these extreme groups in intellectual, personal, emotional characteristics, and in the learning styles were examined. The Mozart effect on the spatial-temporal reasoning performance was confirmed. The effect was not influenced by gender, musical knowledge, or the study area. It was also not affected by personality and emotional characteristics. On the other hand, there was an influence of the general intelligence factor (the effect was more pronounced in the individuals with lower IQ in comparison with those with higher IQ and in the learning styles (the enhancement group processed information more on auditory and holistic level, while the stagnation group was more visual and analytical. Our study confirmed that Mozart's music has a positive influence on cognitive functioning, but this influence depends on intellectual capacities, perceptual style, and information processing style.

  5. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    Tang Ganghua

    2001-01-01

    The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of gene expression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging gene expression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon

  6. Enhanced learning of proportional math through music training and spatial-temporal training.

    Science.gov (United States)

    Graziano, A B; Peterson, M; Shaw, G L

    1999-03-01

    It was predicted, based on a mathematical model of the cortex, that early music training would enhance spatial-temporal reasoning. We have demonstrated that preschool children given six months of piano keyboard lessons improved dramatically on spatial-temporal reasoning while children in appropriate control groups did not improve. It was then predicted that the enhanced spatial-temporal reasoning from piano keyboard training could lead to enhanced learning of specific math concepts, in particular proportional math, which is notoriously difficult to teach using the usual language-analytic methods. We report here the development of Spatial-Temporal Math Video Game software designed to teach fractions and proportional math, and its strikingly successful use in a study involving 237 second-grade children (age range six years eight months-eight years five months). Furthermore, as predicted, children given piano keyboard training along with the Math Video Game training scored significantly higher on proportional math and fractions than children given a control training along with the Math Video Game. These results were readily measured using the companion Math Video Game Evaluation Program. The training time necessary for children on the Math Video Game is very short, and they rapidly reach a high level of performance. This suggests that, as predicted, we are tapping into fundamental cortical processes of spatial-temporal reasoning. This spatial-temporal approach is easily generalized to teach other math and science concepts in a complementary manner to traditional language-analytic methods, and at a younger age. The neural mechanisms involved in thinking through fractions and proportional math during training with the Math Video Game might be investigated in EEG coherence studies along with priming by specific music.

  7. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Wiebe, Leonard I.

    1997-01-01

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k + ) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k + gene expression where the H S V-1 t k + gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([ 18 F]F H P G; [ 18 F]-A C V), and pyrimidine- ([ 123 / 131 I]I V R F U; [ 124 / 131I ]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [ 123 / 131I ]I V R F U imaging with the H S V-1 t k + reporter gene will be presented

  8. Imaging gene expression in gene therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-12-31

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

  9. Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard

    2016-09-01

    An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

  10. Global gene expression analysis for evaluation and design of biomaterials

    Directory of Open Access Journals (Sweden)

    Nobutaka Hanagata, Taro Takemura and Takashi Minowa

    2010-01-01

    Full Text Available Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data.

  11. Visually Relating Gene Expression and in vivo DNA Binding Data

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Min-Yu; Mackey, Lester; Ker?,; nen, Soile V. E.; Weber, Gunther H.; Jordan, Michael I.; Knowles, David W.; Biggin, Mark D.; Hamann, Bernd

    2011-09-20

    Gene expression and in vivo DNA binding data provide important information for understanding gene regulatory networks: in vivo DNA binding data indicate genomic regions where transcription factors are bound, and expression data show the output resulting from this binding. Thus, there must be functional relationships between these two types of data. While visualization and data analysis tools exist for each data type alone, there is a lack of tools that can easily explore the relationship between them. We propose an approach that uses the average expression driven by multiple of ciscontrol regions to visually relate gene expression and in vivo DNA binding data. We demonstrate the utility of this tool with examples from the network controlling early Drosophila development. The results obtained support the idea that the level of occupancy of a transcription factor on DNA strongly determines the degree to which the factor regulates a target gene, and in some cases also controls whether the regulation is positive or negative.

  12. Global gene expression analysis for evaluation and design of biomaterials

    International Nuclear Information System (INIS)

    Hanagata, Nobutaka; Takemura, Taro; Minowa, Takashi

    2010-01-01

    Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data. (topical review)

  13. Spatial-Temporal Junction Extraction and Semantic Interpretation

    DEFF Research Database (Denmark)

    Simonsen, Kasper Broegaard; Thorsted Nielsen, Mads; Pilz, Florian

    2009-01-01

    This article describes a novel junction descriptor that encodes junctions’ semantic information in terms incoming lines’ orientations, both in 2D and 3D. A Kalman filter process is used to reduce the effect of local noise on the descriptor's error and to track the features. The improvement gained...

  14. Water data in US: a spatial, temporal and sectoral analysis

    Science.gov (United States)

    Josset, L.; Allaire, M.; Rising, J. A.; Thomas, C.; Lall, U.

    2017-12-01

    Water data plays a crucial role in the development and implementation of sustainable water management strategies. Both effective design and assessment hinge on accurate information. This requires environmental, climatic, hydrologic, hydrogeologic, industrial, agricultural, energetic and socio-economic data to accurately characterize and project future supply and demand. In 2001, Vorosmarty et al. painted a stark future for water data, which was qualified as ``a new endangered species". Sixteen years after this publication, we propose a review of the current state of water data in the United States. While considerable progress has been made in data science and model development in the recent years, models are only as good as the data that populate them. After a brief overview of water data aggregated at the national level, we compare datasets from federal agencies with water information collected by individual states. We note in particular the potential gaps in the collected information that would support research beyond water balance accounts to informing regulations, investments, and economic decisions. In addition, we assess the information structures that host and disseminate data as well as data availability and usability (i.e. whether tools are proposed such as metrics, visualization, projections). We conclude our paper with a review of the current technological developments, policies and initiatives that may be transformative and redefine the future of water data. We follow two angles: the progress made in data collection (e.g. remote sensing, datascience, reporting policies) and in data dissemination (frameworks, cyber-infrastructures and standards). We review in particular the current initiatives taking place in US and around the world that promote water data freely available to all.

  15. Gene expression of the endolymphatic sac

    DEFF Research Database (Denmark)

    Friis, Morten; Martin-Bertelsen, Tomas; Friis-Hansen, Lennart

    2011-01-01

    that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...

  16. Gene expression profiling in autoimmune diseases

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo

    2007-01-01

    A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific gene expression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...

  17. Gene expression in early stage cervical cancer

    NARCIS (Netherlands)

    Biewenga, Petra; Buist, Marrije R.; Moerland, Perry D.; van Thernaat, Emiel Ver Loren; van Kampen, Antoine H. C.; ten Kate, Fiebo J. W.; Baas, Frank

    2008-01-01

    Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage

  18. Shrinkage Approach for Gene Expression Data Analysis

    Czech Academy of Sciences Publication Activity Database

    Haman, Jiří; Valenta, Zdeněk; Kalina, Jan

    2013-01-01

    Roč. 1, č. 1 (2013), s. 65-65 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : shrinkage estimation * covariance matrix * high dimensional data * gene expression Subject RIV: IN - Informatics, Computer Science

  19. Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

    Science.gov (United States)

    Liu, Pei; Han, Ruimei; Wang, Shuangting

    2014-11-01

    According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

  20. Social Regulation of Gene Expression in Threespine Sticklebacks.

    Directory of Open Access Journals (Sweden)

    Anna K Greenwood

    Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

  1. Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

    Science.gov (United States)

    Jin, Y.; Lee, D.

    2017-12-01

    North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods

  2. A Case Study of a Child with Dyslexia and Spatial-Temporal Gifts

    Science.gov (United States)

    Cooper, Eileen E.; Ness, Maryann; Smith, Mary

    2004-01-01

    This case study details the history and K-5 school experience of a boy with dyslexia and spatial-temporal gifts. It describes assessment, evaluation, and identification procedures; the learning specialist's interventions and program; the critical role of the parent; and the services provided by the gifted program. Specific interventions are…

  3. Comparison of Urban Human Movements Inferring from Multi-Source Spatial-Temporal Data

    Science.gov (United States)

    Cao, Rui; Tu, Wei; Cao, Jinzhou; Li, Qingquan

    2016-06-01

    The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.

  4. COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA

    Directory of Open Access Journals (Sweden)

    R. Cao

    2016-06-01

    Full Text Available The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.

  5. A Randomized Trial of an Elementary School Mathematics Software Intervention: Spatial-Temporal Math

    Science.gov (United States)

    Rutherford, Teomara; Farkas, George; Duncan, Greg; Burchinal, Margaret; Kibrick, Melissa; Graham, Jeneen; Richland, Lindsey; Tran, Natalie; Schneider, Stephanie; Duran, Lauren; Martinez, Michael E.

    2014-01-01

    Fifty-two low performing schools were randomly assigned to receive Spatial-Temporal (ST) Math, a supplemental mathematics software and instructional program, in second/third or fourth/fifth grades or to a business-as-usual control. Analyses reveal a negligible effect of ST Math on mathematics scores, which did not differ significantly across…

  6. Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

    Science.gov (United States)

    Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

    2017-11-08

    Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

  7. Evaluation of the MIND Research Institute's Spatial-Temporal Math (ST Math) Program in California

    Science.gov (United States)

    Wendt, Staci; Rice, John; Nakamoto, Jonathan

    2014-01-01

    The MIND Research Institute contracted with the Evaluation Research Program at WestEd to conduct an independent assessment of mathematics outcomes in elementary school grades across California that were provided with the ST Math program. Spatial-Temporal (ST) Math is a game-based instructional software designed to boost K-5 and secondary-level…

  8. Kronecker-ARX models in identifying (2D) spatial-temporal systems

    NARCIS (Netherlands)

    Sinquin, B.; Verhaegen, M.H.G.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    In this paper we address the identification of (2D) spatial-temporal dynamical systems governed by the Vector Auto-Regressive (VAR) form. The coefficient-matrices of the VAR model are parametrized as sums of Kronecker products. When the number of terms in the sum is small compared to the size of

  9. SPATIAL-TEMPORAL ANALYSIS OF OPENSTREETMAP DATA AFTER NATURAL DISASTERS: A CASE STUDY OF HAITI UNDER HURRICANE MATTHEW

    Directory of Open Access Journals (Sweden)

    J. Xu

    2017-09-01

    Full Text Available Volunteered geographic information (VGI has been widely adopted as an alternative for authoritative geographic information in disaster management considering its up-to-date data. OpenStreetMap, in particular, is now aiming at crisis mapping for humanitarian purpose. This paper illustrated that natural disaster played an essential role in updating OpenStreetMap data after Haiti was hit by Hurricane Matthew in October, 2016. Spatial-temporal analysis of updated OSM data was conducted in this paper. Correlation of features was also studied to figure out whether updates of data were coincidence or the results of the hurricane. Spatial pattern matched the damaged areas and temporal changes fitted the time when disaster occurred. High level of correlation values of features were recorded when hurricane occurred, suggesting that updates in data were led by the hurricane.

  10. Spatial-Temporal Analysis of Openstreetmap Data after Natural Disasters: a Case Study of Haiti Under Hurricane Matthew

    Science.gov (United States)

    Xu, J.; Li, L.; Zhou, Q.

    2017-09-01

    Volunteered geographic information (VGI) has been widely adopted as an alternative for authoritative geographic information in disaster management considering its up-to-date data. OpenStreetMap, in particular, is now aiming at crisis mapping for humanitarian purpose. This paper illustrated that natural disaster played an essential role in updating OpenStreetMap data after Haiti was hit by Hurricane Matthew in October, 2016. Spatial-temporal analysis of updated OSM data was conducted in this paper. Correlation of features was also studied to figure out whether updates of data were coincidence or the results of the hurricane. Spatial pattern matched the damaged areas and temporal changes fitted the time when disaster occurred. High level of correlation values of features were recorded when hurricane occurred, suggesting that updates in data were led by the hurricane.

  11. Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram

    Directory of Open Access Journals (Sweden)

    Lei Zhao

    2017-01-01

    Full Text Available This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better.

  12. Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

    Directory of Open Access Journals (Sweden)

    Jiwei Li

    2016-11-01

    Full Text Available Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

  13. Fluid Mechanics, Arterial Disease, and Gene Expression.

    Science.gov (United States)

    Tarbell, John M; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs.

  14. Regulation of meiotic gene expression in plants

    Directory of Open Access Journals (Sweden)

    Adele eZhou

    2014-08-01

    Full Text Available With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been built. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa, wheat (Triticum aestivum, petunia (Petunia hybrida, sunflower (Helianthus annuus, and maize (Zea mays. Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs, that might be involved in the regulation of meiotic transcription patterns.

  15. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

    Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of gene expression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between gene expression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

  16. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  17. Profiling Gene Expression in Germinating Brassica Roots.

    Science.gov (United States)

    Park, Myoung Ryoul; Wang, Yi-Hong; Hasenstein, Karl H

    2014-01-01

    Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.

  18. Using gene expression noise to understand gene regulation

    NARCIS (Netherlands)

    Munsky, B.; Neuert, G.; van Oudenaarden, A.

    2012-01-01

    Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

  19. Changes in gene expression following androgen receptor blockade ...

    Indian Academy of Sciences (India)

    Madhu urs

    of gene expression in the ventral prostate, it is not clear whether all the gene expression ... These include clusterin, methionine adenosyl transferase IIα, and prostate-specific ..... MAGEE1 melanoma antigen and no similarity was found with the ...

  20. Rubisco activity and gene expression of tropical tree species under ...

    African Journals Online (AJOL)

    Young

    2013-05-15

    May 15, 2013 ... Proteomics analysis associated with gene expression of plants reveal .... Consequently, Rubisco enzyme plays a role in assi- milating into ... technique for examining gene expression encoded at the. mRNA level .... Ammonia.

  1. Cholinergic regulation of VIP gene expression in human neuroblastoma cells

    DEFF Research Database (Denmark)

    Kristensen, Bo; Georg, Birgitte; Fahrenkrug, Jan

    1997-01-01

    Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing......Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing...

  2. Gene expression inference with deep learning.

    Science.gov (United States)

    Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

    2016-06-15

    Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. Comparative gene expression between two yeast species

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    Guan Yuanfang

    2013-01-01

    Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

  4. Mining gene expression data of multiple sclerosis.

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    Pi Guo

    Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

  5. Gene Expression Profiling of Xeroderma Pigmentosum

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    Bowden Nikola A

    2006-05-01

    Full Text Available Abstract Xeroderma pigmentosum (XP is a rare recessive disorder that is characterized by extreme sensitivity to UV light. UV light exposure results in the formation of DNA damage such as cyclobutane dimers and (6-4 photoproducts. Nucleotide excision repair (NER orchestrates the removal of cyclobutane dimers and (6-4 photoproducts as well as some forms of bulky chemical DNA adducts. The disease XP is comprised of 7 complementation groups (XP-A to XP-G, which represent functional deficiencies in seven different genes, all of which are believed to be involved in NER. The main clinical feature of XP is various forms of skin cancers; however, neurological degeneration is present in XPA, XPB, XPD and XPG complementation groups. The relationship between NER and other types of DNA repair processes is now becoming evident but the exact relationships between the different complementation groups remains to be precisely determined. Using gene expression analysis we have identified similarities and differences after UV light exposure between the complementation groups XP-A, XP-C, XP-D, XP-E, XP-F, XP-G and an unaffected control. The results reveal that there is a graded change in gene expression patterns between the mildest, most similar to the control response (XP-E and the severest form (XP-A of the disease, with the exception of XP-D. Distinct differences between the complementation groups with neurological symptoms (XP-A, XP-D and XP-G and without (XP-C, XP-E and XP-F were also identified. Therefore, this analysis has revealed distinct gene expression profiles for the XP complementation groups and the first step towards understanding the neurological symptoms of XP.

  6. Meta Analysis of Gene Expression Data within and Across Species.

    Science.gov (United States)

    Fierro, Ana C; Vandenbussche, Filip; Engelen, Kristof; Van de Peer, Yves; Marchal, Kathleen

    2008-12-01

    Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.

  7. Spatial-temporal noise reduction method optimized for real-time implementation

    Science.gov (United States)

    Romanenko, I. V.; Edirisinghe, E. A.; Larkin, D.

    2013-02-01

    Image de-noising in the spatial-temporal domain has been a problem studied in-depth in the field of digital image processing. However complexity of algorithms often leads to high hardware resource usage, or computational complexity and memory bandwidth issues, making their practical use impossible. In our research we attempt to solve these issues with an optimized implementation of a practical spatial-temporal de-noising algorithm. Spatial-temporal filtering was performed in Bayer RAW data space, which allowed us to benefit from predictable sensor noise characteristics and reduce memory bandwidth requirements. The proposed algorithm efficiently removes different kinds of noise in a wide range of signal to noise ratios. In our algorithm the local motion compensation is performed in Bayer RAW data space, while preserving the resolution and effectively improving the signal to noise ratios of moving objects. The main challenge for the use of spatial-temporal noise reduction algorithms in video applications is the compromise between the quality of the motion prediction and the complexity of the algorithm and required memory bandwidth. In photo and video applications it is very important that moving objects should stay sharp, while the noise is efficiently removed in both the static background and moving objects. Another important use case is the case when background is also non-static as well as the foreground where objects are also moving. Taking into account the achievable improvement in PSNR (on the level of the best known noise reduction techniques, like VBM3D) and low algorithmic complexity, enabling its practical use in commercial video applications, the results of our research can be very valuable.

  8. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

  9. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

  10. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

  11. [Application of Land-use Regression Models in Spatial-temporal Differentiation of Air Pollution].

    Science.gov (United States)

    Wu, Jian-sheng; Xie, Wu-dan; Li, Jia-cheng

    2016-02-15

    With the rapid development of urbanization, industrialization and motorization, air pollution has become one of the most serious environmental problems in our country, which has negative impacts on public health and ecological environment. LUR model is one of the common methods simulating spatial-temporal differentiation of air pollution at city scale. It has broad application in Europe and North America, but not really in China. Based on many studies at home and abroad, this study started with the main steps to develop LUR model, including obtaining the monitoring data, generating variables, developing models, model validation and regression mapping. Then a conclusion was drawn on the progress of LUR models in spatial-temporal differentiation of air pollution. Furthermore, the research focus and orientation in the future were prospected, including highlighting spatial-temporal differentiation, increasing classes of model variables and improving the methods of model development. This paper was aimed to popularize the application of LUR model in China, and provide a methodological basis for human exposure, epidemiologic study and health risk assessment.

  12. Multiple Suboptimal Solutions for Prediction Rules in Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Osamu Komori

    2013-01-01

    Full Text Available This paper discusses mathematical and statistical aspects in analysis methods applied to microarray gene expressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray gene expression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence.

  13. Decomposition of gene expression state space trajectories.

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    Jessica C Mar

    2009-12-01

    Full Text Available Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005 which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005 build on the work of Kauffman (2004 who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions-core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005 dataset.

  14. Noise minimization in eukaryotic gene expression.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2004-06-01

    Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  15. Noise minimization in eukaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-15

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  16. Noise minimization in eukaryotic gene expression

    International Nuclear Information System (INIS)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-01

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

  17. Molecular mechanisms of curcumin action: gene expression.

    Science.gov (United States)

    Shishodia, Shishir

    2013-01-01

    Curcumin derived from the tropical plant Curcuma longa has a long history of use as a dietary agent, food preservative, and in traditional Asian medicine. It has been used for centuries to treat biliary disorders, anorexia, cough, diabetic wounds, hepatic disorders, rheumatism, and sinusitis. The preventive and therapeutic properties of curcumin are associated with its antioxidant, anti-inflammatory, and anticancer properties. Extensive research over several decades has attempted to identify the molecular mechanisms of curcumin action. Curcumin modulates numerous molecular targets by altering their gene expression, signaling pathways, or through direct interaction. Curcumin regulates the expression of inflammatory cytokines (e.g., TNF, IL-1), growth factors (e.g., VEGF, EGF, FGF), growth factor receptors (e.g., EGFR, HER-2, AR), enzymes (e.g., COX-2, LOX, MMP9, MAPK, mTOR, Akt), adhesion molecules (e.g., ELAM-1, ICAM-1, VCAM-1), apoptosis related proteins (e.g., Bcl-2, caspases, DR, Fas), and cell cycle proteins (e.g., cyclin D1). Curcumin modulates the activity of several transcription factors (e.g., NF-κB, AP-1, STAT) and their signaling pathways. Based on its ability to affect multiple targets, curcumin has the potential for the prevention and treatment of various diseases including cancers, arthritis, allergies, atherosclerosis, aging, neurodegenerative disease, hepatic disorders, obesity, diabetes, psoriasis, and autoimmune diseases. This review summarizes the molecular mechanisms of modulation of gene expression by curcumin. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  18. Mutual repression enhances the steepness and precision of gene expression boundaries.

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    Thomas R Sokolowski

    Full Text Available Embryonic development is driven by spatial patterns of gene expression that determine the fate of each cell in the embryo. While gene expression is often highly erratic, embryonic development is usually exceedingly precise. In particular, gene expression boundaries are robust not only against intra-embryonic fluctuations such as noise in gene expression and protein diffusion, but also against embryo-to-embryo variations in the morphogen gradients, which provide positional information to the differentiating cells. How development is robust against intra- and inter-embryonic variations is not understood. A common motif in the gene regulation networks that control embryonic development is mutual repression between pairs of genes. To assess the role of mutual repression in the robust formation of gene expression patterns, we have performed large-scale stochastic simulations of a minimal model of two mutually repressing gap genes in Drosophila, hunchback (hb and knirps (kni. Our model includes not only mutual repression between hb and kni, but also the stochastic and cooperative activation of hb by the anterior morphogen Bicoid (Bcd and of kni by the posterior morphogen Caudal (Cad, as well as the diffusion of Hb and Kni between neighboring nuclei. Our analysis reveals that mutual repression can markedly increase the steepness and precision of the gap gene expression boundaries. In contrast to other mechanisms such as spatial averaging and cooperative gene activation, mutual repression thus allows for gene-expression boundaries that are both steep and precise. Moreover, mutual repression dramatically enhances their robustness against embryo-to-embryo variations in the morphogen levels. Finally, our simulations reveal that diffusion of the gap proteins plays a critical role not only in reducing the width of the gap gene expression boundaries via the mechanism of spatial averaging, but also in repairing patterning errors that could arise because of the

  19. Curcumin administration suppress acetylcholinesterase gene expression in cadmium treated rats.

    Science.gov (United States)

    Akinyemi, Ayodele Jacob; Oboh, Ganiyu; Fadaka, Adewale Oluwaseun; Olatunji, Babawale Peter; Akomolafe, Seun

    2017-09-01

    Curcumin, the main polyphenolic component of turmeric (Curcuma longa) rhizomes have been reported to exert anticholinesterase potential with limited information on how they regulate acetylcholinesterase (AChE) gene expression. Hence, this study sought to evaluate the effect of curcumin on cerebral cortex acetylcholinesterase (AChE) activity and their mRNA gene expression level in cadmium (Cd)-treated rats. Furthermore, in vitro effect of different concentrations of curcumin (1-5μg/mL) on rat cerebral cortex AChE activity was assessed. Animals were divided into six groups (n=6): group 1 serve as control (without Cd) and receive saline/vehicle, group 2 receive saline plus curcumin at 25mg/kg, group 3 receive saline plus curcumin 50mg/kg, group 4 receive Cd plus vehicle, group 5 receive Cd plus curcumin at 25mg/kg and group 6 receive Cd plus curcumin at 50mg/kg. Rats received Cd (2.5mg/kg) and curcumin (25 and 50mg/kg, respectively) by oral gavage for 7days. Acetylcholinesterase activity was measured by Ellman's method and AChE expression was carried out by a quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assay. We observed that acute administration of Cd increased acetylcholinesterase activity and in addition caused a significant (Pcurcumin inhibited AChE activity and alters AChE mRNA levels when compared to Cd-treated group. In addition, curcumin inhibits rat cerebral cortex AChE activity in vitro. In conclusion, curcumin exhibit anti-acetylcholinesterase activity and suppressed AChE mRNA gene expression level in Cd exposed rats, thus providing some biochemical and molecular evidence on the therapeutic effect of this turmeric-derived compound in treating neurological disorders including Alzheimer's disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Serial Analysis of Gene Expression: Applications in Human Studies

    Directory of Open Access Journals (Sweden)

    Tuteja Renu

    2004-01-01

    Full Text Available Serial analysis of gene expression (SAGE is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressed genes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE results in an accurate picture of gene expression at both the qualitative and the quantitative levels. It does not require a hybridization probe for each transcript and allows new genes to be discovered. This technique has been applied widely in human studies and various SAGE tags/SAGE libraries have been generated from different cells/tissues such as dendritic cells, lung fibroblast cells, oocytes, thyroid tissue, B-cell lymphoma, cultured keratinocytes, muscles, brain tissues, sciatic nerve, cultured Schwann cells, cord blood-derived mast cells, retina, macula, retinal pigment epithelial cells, skin cells, and so forth. In this review we present the updated information on the applications of SAGE technology mainly to human studies.

  1. Gene Expression Commons: an open platform for absolute gene expression profiling.

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    Jun Seita

    Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

  2. The Medicago truncatula gene expression atlas web server

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    Tang Yuhong

    2009-12-01

    Full Text Available Abstract Background Legumes (Leguminosae or Fabaceae play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA web server for this purpose. Description The Medicago truncatula Gene Expression Atlas (MtGEA web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible

  3. Construction and use of gene expression covariation matrix

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    Bellis Michel

    2009-07-01

    Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

  4. Gene expression analysis of flax seed development

    Science.gov (United States)

    2011-01-01

    Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise

  5. Gene expression analysis of flax seed development

    Directory of Open Access Journals (Sweden)

    Sharpe Andrew

    2011-04-01

    Full Text Available Abstract Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages seed coats (globular and torpedo stages and endosperm (pooled globular to torpedo stages and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST (GenBank accessions LIBEST_026995 to LIBEST_027011 were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152 had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid

  6. Classification across gene expression microarray studies

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    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  7. Cerebrovascular gene expression in spontaneously hypertensive rats

    DEFF Research Database (Denmark)

    Grell, Anne-Sofie; Frederiksen, Simona Denise; Edvinsson, Lars

    2017-01-01

    Hypertension is a hemodynamic disorder and one of the most important and well-established risk factors for vascular diseases such as stroke. Blood vessels exposed to chronic shear stress develop structural changes and remodeling of the vascular wall through many complex mechanisms. However......, the molecular mechanisms involved are not fully understood. Hypertension-susceptible genes may provide a novel insight into potential molecular mechanisms of hypertension and secondary complications associated with hypertension. The aim of this exploratory study was to identify gene expression differences......, the identified genes in the middle cerebral arteries from spontaneously hypertensive rats could be possible mediators of the vascular changes and secondary complications associated with hypertension. This study supports the selection of key genes to investigate in the future research of hypertension-induced end...

  8. Retrotransposons as regulators of gene expression.

    Science.gov (United States)

    Elbarbary, Reyad A; Lucas, Bronwyn A; Maquat, Lynne E

    2016-02-12

    Transposable elements (TEs) are both a boon and a bane to eukaryotic organisms, depending on where they integrate into the genome and how their sequences function once integrated. We focus on two types of TEs: long interspersed elements (LINEs) and short interspersed elements (SINEs). LINEs and SINEs are retrotransposons; that is, they transpose via an RNA intermediate. We discuss how LINEs and SINEs have expanded in eukaryotic genomes and contribute to genome evolution. An emerging body of evidence indicates that LINEs and SINEs function to regulate gene expression by affecting chromatin structure, gene transcription, pre-mRNA processing, or aspects of mRNA metabolism. We also describe how adenosine-to-inosine editing influences SINE function and how ongoing retrotransposition is countered by the body's defense mechanisms. Copyright © 2016, American Association for the Advancement of Science.

  9. Determinants of human adipose tissue gene expression

    DEFF Research Database (Denmark)

    Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José

    2012-01-01

    weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

  10. Network Completion for Static Gene Expression Data

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    Natsu Nakajima

    2014-01-01

    Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.

  11. Peak flood estimation using gene expression programming

    Science.gov (United States)

    Zorn, Conrad R.; Shamseldin, Asaad Y.

    2015-12-01

    As a case study for the Auckland Region of New Zealand, this paper investigates the potential use of gene-expression programming (GEP) in predicting specific return period events in comparison to the established and widely used Regional Flood Estimation (RFE) method. Initially calibrated to 14 gauged sites, the GEP derived model was further validated to 10 and 100 year flood events with a relative errors of 29% and 18%, respectively. This is compared to the RFE method providing 48% and 44% errors for the same flood events. While the effectiveness of GEP in predicting specific return period events is made apparent, it is argued that the derived equations should be used in conjunction with those existing methodologies rather than as a replacement.

  12. Nuclear AXIN2 represses MYC gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S., E-mail: gsy3@psu.edu

    2014-01-03

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling.

  13. Nuclear AXIN2 represses MYC gene expression

    International Nuclear Information System (INIS)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S.

    2014-01-01

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling

  14. Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

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    Richard Danger

    2018-01-01

    Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

  15. Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

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    Yu Zhang

    2013-12-01

    Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genes expression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of gene expression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

  16. Repetitive Imaging of Reporter Gene Expression in the Lung

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    Jean-Christophe Richard

    2003-10-01

    Full Text Available Positron emission tomographic imaging is emerging as a powerful technology to monitor reporter transgene expression in the lungs and other organs. However, little information is available about its usefulness for studying gene expression over time. Therefore, we infected 20 rats with a replication-deficient adenovirus containing a fusion gene encoding for a mutant Herpes simplex virus type-1 thymidine kinase and an enhanced green fluorescent protein. Five additional rats were infected with a control virus. Pulmonary gene transfer was performed via intratracheal administration of vector using a surfactant-based method. Imaging was performed 4–6 hr, and 4, 7, and 10 days after gene transfer, using 9-(4-[18F]-fluoro-3-hydroxymethylbutylguanine, an imaging substrate for the mutant kinase. Lung tracer uptake assessed with imaging was moderately but significantly increased 4–6 hr after gene transfer, was maximal after 4 days, and was no longer detectable by 10 days. The temporal pattern of transgene expression measured ex vivo with in vitro assays of thymidine kinase activity and green fluorescent protein was similar to imaging. In conclusion, positron emission tomography is a reliable new tool to evaluate the onset and duration of reporter gene expression noninvasively in the lungs of intact animals.

  17. Using interpolation to estimate system uncertainty in gene expression experiments.

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    Lee J Falin

    Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.

  18. Spatial-temporal analysis of wind power forecast errors for West-Coast Norway

    Energy Technology Data Exchange (ETDEWEB)

    Revheim, Paal Preede; Beyer, Hans Georg [Agder Univ. (UiA), Grimstad (Norway). Dept. of Engineering Sciences

    2012-07-01

    In this paper the spatial-temporal structure of forecast errors for wind power in West-Coast Norway is analyzed. Starting on the qualitative analysis of the forecast error reduction, with respect to single site data, for the lumped conditions of groups of sites the spatial and temporal correlations of the wind power forecast errors within and between the same groups are studied in detail. Based on this, time-series regression models to be used to analytically describe the error reduction are set up. The models give an expected reduction in forecast error between 48.4% and 49%. (orig.)

  19. Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE

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    Piña-Sanchez Patricia

    2005-09-01

    Full Text Available Abstract Background Serial Analysis of Gene Expression (SAGE is a new technique that allows a detailed and profound quantitative and qualitative knowledge of gene expression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE, useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV, where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC. Results We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation. Conclusion This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma.

  20. Transitions between central and peripheral vision create spatial/temporal distortions: a hypothesis concerning the perceived break of the curveball.

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    Arthur Shapiro

    2010-10-01

    Full Text Available The human visual system does not treat all parts of an image equally: the central segments of an image, which fall on the fovea, are processed with a higher resolution than the segments that fall in the visual periphery. Even though the differences between foveal and peripheral resolution are large, these differences do not usually disrupt our perception of seamless visual space. Here we examine a motion stimulus in which the shift from foveal to peripheral viewing creates a dramatic spatial/temporal discontinuity.The stimulus consists of a descending disk (global motion with an internal moving grating (local motion. When observers view the disk centrally, they perceive both global and local motion (i.e., observers see the disk's vertical descent and the internal spinning. When observers view the disk peripherally, the internal portion appears stationary, and the disk appears to descend at an angle. The angle of perceived descent increases as the observer views the stimulus from further in the periphery. We examine the first- and second-order information content in the display with the use of a three-dimensional Fourier analysis and show how our results can be used to describe perceived spatial/temporal discontinuities in real-world situations.The perceived shift of the disk's direction in the periphery is consistent with a model in which foveal processing separates first- and second-order motion information while peripheral processing integrates first- and second-order motion information. We argue that the perceived distortion may influence real-world visual observations. To this end, we present a hypothesis and analysis of the perception of the curveball and rising fastball in the sport of baseball. The curveball is a physically measurable phenomenon: the imbalance of forces created by the ball's spin causes the ball to deviate from a straight line and to follow a smooth parabolic path. However, the curveball is also a perceptual puzzle

  1. Transitions between central and peripheral vision create spatial/temporal distortions: a hypothesis concerning the perceived break of the curveball.

    Science.gov (United States)

    Shapiro, Arthur; Lu, Zhong-Lin; Huang, Chang-Bing; Knight, Emily; Ennis, Robert

    2010-10-13

    The human visual system does not treat all parts of an image equally: the central segments of an image, which fall on the fovea, are processed with a higher resolution than the segments that fall in the visual periphery. Even though the differences between foveal and peripheral resolution are large, these differences do not usually disrupt our perception of seamless visual space. Here we examine a motion stimulus in which the shift from foveal to peripheral viewing creates a dramatic spatial/temporal discontinuity. The stimulus consists of a descending disk (global motion) with an internal moving grating (local motion). When observers view the disk centrally, they perceive both global and local motion (i.e., observers see the disk's vertical descent and the internal spinning). When observers view the disk peripherally, the internal portion appears stationary, and the disk appears to descend at an angle. The angle of perceived descent increases as the observer views the stimulus from further in the periphery. We examine the first- and second-order information content in the display with the use of a three-dimensional Fourier analysis and show how our results can be used to describe perceived spatial/temporal discontinuities in real-world situations. The perceived shift of the disk's direction in the periphery is consistent with a model in which foveal processing separates first- and second-order motion information while peripheral processing integrates first- and second-order motion information. We argue that the perceived distortion may influence real-world visual observations. To this end, we present a hypothesis and analysis of the perception of the curveball and rising fastball in the sport of baseball. The curveball is a physically measurable phenomenon: the imbalance of forces created by the ball's spin causes the ball to deviate from a straight line and to follow a smooth parabolic path. However, the curveball is also a perceptual puzzle because batters often

  2. Transcriptome database resource and gene expression atlas for the rose

    Science.gov (United States)

    2012-01-01

    Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy. PMID:23164410

  3. Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

    Science.gov (United States)

    O'Connor, Timothy R.; Bailey, Timothy L.

    2014-01-01

    Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

  4. Semantic integration of gene expression analysis tools and data sources using software connectors

    Science.gov (United States)

    2013-01-01

    Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

  5. Online Analytical Processing (OLAP: A Fast and Effective Data Mining Tool for Gene Expression Databases

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    Alkharouf Nadim W.

    2005-01-01

    Full Text Available Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD. A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

  6. Protists and the Wild, Wild West of Gene Expression: New Frontiers, Lawlessness, and Misfits.

    Science.gov (United States)

    Smith, David Roy; Keeling, Patrick J

    2016-09-08

    The DNA double helix has been called one of life's most elegant structures, largely because of its universality, simplicity, and symmetry. The expression of information encoded within DNA, however, can be far from simple or symmetric and is sometimes surprisingly variable, convoluted, and wantonly inefficient. Although exceptions to the rules exist in certain model systems, the true extent to which life has stretched the limits of gene expression is made clear by nonmodel systems, particularly protists (microbial eukaryotes). The nuclear and organelle genomes of protists are subject to the most tangled forms of gene expression yet identified. The complicated and extravagant picture of the underlying genetics of eukaryotic microbial life changes how we think about the flow of genetic information and the evolutionary processes shaping it. Here, we discuss the origins, diversity, and growing interest in noncanonical protist gene expression and its relationship to genomic architecture.

  7. Online analytical processing (OLAP): a fast and effective data mining tool for gene expression databases.

    Science.gov (United States)

    Alkharouf, Nadim W; Jamison, D Curtis; Matthews, Benjamin F

    2005-06-30

    Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

  8. Polycistronic gene expression in Aspergillus niger.

    Science.gov (United States)

    Schuetze, Tabea; Meyer, Vera

    2017-09-25

    Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

  9. Comparative gene expression of intestinal metabolizing enzymes.

    Science.gov (United States)

    Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

    2009-11-01

    The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

  10. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    DEFF Research Database (Denmark)

    Manijak, Mieszko P.; Nielsen, Henrik Bjørn

    2011-01-01

    circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

  11. Spatial-Temporal Similarity Correlation between Public Transit Passengers Using Smart Card Data

    Directory of Open Access Journals (Sweden)

    Hamed Faroqi

    2017-01-01

    Full Text Available The increasing availability of public transit smart card data has enabled several studies to focus on identifying passengers with similar spatial and/or temporal trip characteristics. However, this paper goes one step further by investigating the relationship between passengers’ spatial and temporal characteristics. For the first time, this paper investigates the correlation of the spatial similarity with the temporal similarity between public transit passengers by developing spatial similarity and temporal similarity measures for the public transit network with a novel passenger-based perspective. The perspective considers the passengers as agents who can make multiple trips in the network. The spatial similarity measure takes into account direction as well as the distance between the trips of the passengers. The temporal similarity measure considers both the boarding and alighting time in a continuous linear space. The spatial-temporal similarity correlation between passengers is analysed using histograms, Pearson correlation coefficients, and hexagonal binning. Also, relations between the spatial and temporal similarity values with the trip time and length are examined. The proposed methodology is implemented for four-day smart card data including 80,000 passengers in Brisbane, Australia. The results show a nonlinear spatial-temporal similarity correlation among the passengers.

  12. Understanding structure of urban traffic network based on spatial-temporal correlation analysis

    Science.gov (United States)

    Yang, Yanfang; Jia, Limin; Qin, Yong; Han, Shixiu; Dong, Honghui

    2017-08-01

    Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

  13. Technologies for Elastic Optical Networking Systems in Spatial, Temporal and Spectral Domains

    Science.gov (United States)

    Qin, Chuan

    wavelength to track the signal wavelength, thus providing a technique for authentically automatic wavelength tracking. I also explored different materials and crystal orientations to reduce the radio-frequency (RF) power consumption required to shift the wavelengths. Based on the elastic optical networking in the temporal, spectral and spatial domains, an additional degree of freedom has been investigated recently to increase the data capacity. The exploration to use the spatial domain to carry more data is termed as spatial division multiplexing (SDM). One such SDM method is orbital angular momentum(OAM), which is a group of orthogonal light beams carrying orbital angular momentum exhibiting an azimuthal phase variation. The utilization of OAM states has the potential to significantly increase the spectral efficiency and channel capacity. The thesis also includes the demonstration to establish a connection by exploiting the elasticity steering in spatial, temporal and spectral domains. Beam steering based on optical phased array (OPA) is also a potential candidate of SDM to carry information when a different linear phase will distribute light to different spatial locations. The states are intrinsically orthogonal to one another. Using 4x4 3-D waveguides written by ultrafast laser inscription (ULI), we demonstrated 2-D optical phased array (OPA) beam steering that shows steering in both vertical and horizontal directions. Enabling technologies provide future pathways for elastic optical networking and will fundamentally impact optical communication systems in many ways.

  14. Redox regulation of photosynthetic gene expression.

    Science.gov (United States)

    Queval, Guillaume; Foyer, Christine H

    2012-12-19

    Redox chemistry and redox regulation are central to the operation of photosynthesis and respiration. However, the roles of different oxidants and antioxidants in the regulation of photosynthetic or respiratory gene expression remain poorly understood. Leaf transcriptome profiles of a range of Arabidopsis thaliana genotypes that are deficient in either hydrogen peroxide processing enzymes or in low molecular weight antioxidant were therefore compared to determine how different antioxidant systems that process hydrogen peroxide influence transcripts encoding proteins targeted to the chloroplasts or mitochondria. Less than 10 per cent overlap was observed in the transcriptome patterns of leaves that are deficient in either photorespiratory (catalase (cat)2) or chloroplastic (thylakoid ascorbate peroxidase (tapx)) hydrogen peroxide processing. Transcripts encoding photosystem II (PSII) repair cycle components were lower in glutathione-deficient leaves, as were the thylakoid NAD(P)H (nicotinamide adenine dinucleotide (phosphate)) dehydrogenases (NDH) mRNAs. Some thylakoid NDH mRNAs were also less abundant in tAPX-deficient and ascorbate-deficient leaves. Transcripts encoding the external and internal respiratory NDHs were increased by low glutathione and low ascorbate. Regulation of transcripts encoding specific components of the photosynthetic and respiratory electron transport chains by hydrogen peroxide, ascorbate and glutathione may serve to balance non-cyclic and cyclic electron flow pathways in relation to oxidant production and reductant availability.

  15. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

    Schembri, Mark; Kjærgaard, K.; Klemm, Per

    2003-01-01

    It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance to antimicr......It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance...... the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered...... in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces....

  16. Differential gene expression during Trypanosoma cruzi metacyclogenesis

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Krieger

    1999-09-01

    Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressed genes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential gene expression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

  17. Cell cycle gene expression under clinorotation

    Science.gov (United States)

    Artemenko, Olga

    2016-07-01

    Cyclins and cyclin-dependent kinase (CDK) are main regulators of the cell cycle of eukaryotes. It's assumes a significant change of their level in cells under microgravity conditions and by other physical factors actions. The clinorotation use enables to determine the influence of gravity on simulated events in the cell during the cell cycle - exit from the state of quiet stage and promotion presynthetic phase (G1) and DNA synthesis phase (S) of the cell cycle. For the clinorotation effect study on cell proliferation activity is the necessary studies of molecular mechanisms of cell cycle regulation and development of plants under altered gravity condition. The activity of cyclin D, which is responsible for the events of the cell cycle in presynthetic phase can be controlled by the action of endogenous as well as exogenous factors, but clinorotation is one of the factors that influence on genes expression that regulate the cell cycle.These data can be used as a model for further research of cyclin - CDK complex for study of molecular mechanisms regulation of growth and proliferation. In this investigation we tried to summarize and analyze known literature and own data we obtained relatively the main regulators of the cell cycle in altered gravity condition.

  18. Geo-Parcel Based Crop Identification by Integrating High Spatial-Temporal Resolution Imagery from Multi-Source Satellite Data

    Directory of Open Access Journals (Sweden)

    Yingpin Yang

    2017-12-01

    Full Text Available Geo-parcel based crop identification plays an important role in precision agriculture. It meets the needs of refined farmland management. This study presents an improved identification procedure for geo-parcel based crop identification by combining fine-resolution images and multi-source medium-resolution images. GF-2 images with fine spatial resolution of 0.8 m provided agricultural farming plot boundaries, and GF-1 (16 m and Landsat 8 OLI data were used to transform the geo-parcel based enhanced vegetation index (EVI time-series. In this study, we propose a piecewise EVI time-series smoothing method to fit irregular time profiles, especially for crop rotation situations. Global EVI time-series were divided into several temporal segments, from which phenological metrics could be derived. This method was applied to Lixian, where crop rotation was the common practice of growing different types of crops, in the same plot, in sequenced seasons. After collection of phenological features and multi-temporal spectral information, Random Forest (RF was performed to classify crop types, and the overall accuracy was 93.27%. Moreover, an analysis of feature significance showed that phenological features were of greater importance for distinguishing agricultural land cover compared to temporal spectral information. The identification results indicated that the integration of high spatial-temporal resolution imagery is promising for geo-parcel based crop identification and that the newly proposed smoothing method is effective.

  19. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  20. Dissecting specific and global transcriptional regulation of bacterial gene expression

    NARCIS (Netherlands)

    Gerosa, Luca; Kochanowski, Karl; Heinemann, Matthias; Sauer, Uwe

    Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional-but often neglected-layer of complexity in gene expression. Here, we develop an

  1. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  2. Classification between normal and tumor tissues based on the pair-wise gene expression ratio

    International Nuclear Information System (INIS)

    Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

    2004-01-01

    Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

  3. Gene expression response to EWS–FLI1 in mouse embryonic cartilage

    Directory of Open Access Journals (Sweden)

    Miwa Tanaka

    2014-12-01

    Full Text Available Ewing's sarcoma is a rare bone tumor that affects children and adolescents. We have recently succeeded to induce Ewing's sarcoma-like small round cell tumor in mice by expression of EWS–ETS fusion genes in murine embryonic osteochondrogenic progenitors. The Ewing's sarcoma precursors are enriched in embryonic superficial zone (eSZ cells of long bone. To get insights into the mechanisms of Ewing's sarcoma development, gene expression profiles between EWS–FLI1-sensitive eSZ cells and EWS–FLI1-resistant embryonic growth plate (eGP cells were compared using DNA microarrays. Gene expression of eSZ and eGP cells (total, 30 samples was evaluated with or without EWS–FLI1 expression 0, 8 or 48 h after gene transduction. Our data provide useful information for gene expression responses to fusion oncogenes in human sarcoma.

  4. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    Science.gov (United States)

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  5. Functional clustering of time series gene expression data by Granger causality

    Science.gov (United States)

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  6. Mapping and spatial-temporal modeling of Bromus tectorum invasion in central Utah

    Science.gov (United States)

    Jin, Zhenyu

    Cheatgrass, or Downy Brome, is an exotic winter annual weed native to the Mediterranean region. Since its introduction to the U.S., it has become a significant weed and aggressive invader of sagebrush, pinion-juniper, and other shrub communities, where it can completely out-compete native grasses and shrubs. In this research, remotely sensed data combined with field collected data are used to investigate the distribution of the cheatgrass in Central Utah, to characterize the trend of the NDVI time-series of cheatgrass, and to construct a spatially explicit population-based model to simulate the spatial-temporal dynamics of the cheatgrass. This research proposes a method for mapping the canopy closure of invasive species using remotely sensed data acquired at different dates. Different invasive species have their own distinguished phenologies and the satellite images in different dates could be used to capture the phenology. The results of cheatgrass abundance prediction have a good fit with the field data for both linear regression and regression tree models, although the regression tree model has better performance than the linear regression model. To characterize the trend of NDVI time-series of cheatgrass, a novel smoothing algorithm named RMMEH is presented in this research to overcome some drawbacks of many other algorithms. By comparing the performance of RMMEH in smoothing a 16-day composite of the MODIS NDVI time-series with that of two other methods, which are the 4253EH, twice and the MVI, we have found that RMMEH not only keeps the original valid NDVI points, but also effectively removes the spurious spikes. The reconstructed NDVI time-series of different land covers are of higher quality and have smoother temporal trend. To simulate the spatial-temporal dynamics of cheatgrass, a spatially explicit population-based model is built applying remotely sensed data. The comparison between the model output and the ground truth of cheatgrass closure demonstrates

  7. Heterologous gene expression in filamentous fungi.

    Science.gov (United States)

    Su, Xiaoyun; Schmitz, George; Zhang, Meiling; Mackie, Roderick I; Cann, Isaac K O

    2012-01-01

    Filamentous fungi are critical to production of many commercial enzymes and organic compounds. Fungal-based systems have several advantages over bacterial-based systems for protein production because high-level secretion of enzymes is a common trait of their decomposer lifestyle. Furthermore, in the large-scale production of recombinant proteins of eukaryotic origin, the filamentous fungi become the vehicle of choice due to critical processes shared in gene expression with other eukaryotic organisms. The complexity and relative dearth of understanding of the physiology of filamentous fungi, compared to bacteria, have hindered rapid development of these organisms as highly efficient factories for the production of heterologous proteins. In this review, we highlight several of the known benefits and challenges in using filamentous fungi (particularly Aspergillus spp., Trichoderma reesei, and Neurospora crassa) for the production of proteins, especially heterologous, nonfungal enzymes. We review various techniques commonly employed in recombinant protein production in the filamentous fungi, including transformation methods, selection of gene regulatory elements such as promoters, protein secretion factors such as the signal peptide, and optimization of coding sequence. We provide insights into current models of host genomic defenses such as repeat-induced point mutation and quelling. Furthermore, we examine the regulatory effects of transcript sequences, including introns and untranslated regions, pre-mRNA (messenger RNA) processing, transcript transport, and mRNA stability. We anticipate that this review will become a resource for researchers who aim at advancing the use of these fascinating organisms as protein production factories, for both academic and industrial purposes, and also for scientists with general interest in the biology of the filamentous fungi. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. Predicting cellular growth from gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Edoardo M Airoldi

    2009-01-01

    Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

  9. Spatial-Temporal Correlation Properties of the 3GPP Spatial Channel Model and the Kronecker MIMO Channel Model

    Directory of Open Access Journals (Sweden)

    Cheng-Xiang Wang

    2007-02-01

    Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.

  10. Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

    Science.gov (United States)

    Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

    2015-01-27

    Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

  11. Inferring gene expression dynamics via functional regression analysis

    Directory of Open Access Journals (Sweden)

    Leng Xiaoyan

    2008-01-01

    Full Text Available Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

  12. Gene expression profiling of resting and activated vascular smooth muscle cells by serial analysis of gene expression and clustering analysis

    NARCIS (Netherlands)

    Beauchamp, Nicholas J.; van Achterberg, Tanja A. E.; Engelse, Marten A.; Pannekoek, Hans; de Vries, Carlie J. M.

    2003-01-01

    Migration and proliferation of vascular smooth muscle cells (SMCs) are key events in atherosclerosis. However, little is known about alterations in gene expression upon transition of the quiescent, contractile SMC to the proliferative SMC. We performed serial analysis of gene expression (SAGE) of

  13. A Model System for the Study of Gene Expression in the Undergraduate Laboratory

    Science.gov (United States)

    Hargadon, Kristian M.

    2016-01-01

    The flow of genetic information from DNA to RNA to protein, otherwise known as the "central dogma" of biology, is one of the most basic and overarching concepts in the biological sciences. Nevertheless, numerous studies have reported student misconceptions at the undergraduate level of this fundamental process of gene expression. This…

  14. Analysis of spatial temporal plantar pressure pattern during gait in Parkinson's disease.

    Science.gov (United States)

    Okuno, Ryuhei; Fujimoto, Satoshi; Akazawa, Jun; Yokoe, Masaru; Sakoda, Saburo; Akazawa, Kenzo

    2008-01-01

    Spatial temporal plantar pressure patterns measured with sheet-shaped pressure sensor were investigated to extract features of gait in Parkinson's disease. Both six subjects of Parkinson's disease (PD) and elderly fourteen normal control subjects were asked to execute usual walking on the pressure sensor sheets. Candidate features were step length, step time, gait velocity and transition of center of pressure to foot axis direction. The step length and gait velocity were smaller in PD subjects than those in normal subjects. Time of step cycle in three PD subjects were longer than that in normal subjects while the times of other PD subjects were similar to those of control subjects. The length from heel contact to toe off within one footprint was small in the subjects with short step length. Such possibility was indicated that Parkinson's disease in gait could be separated from normal subjects by these features.

  15. Meteor localization via statistical analysis of spatially temporal fluctuations in image sequences

    Science.gov (United States)

    Kukal, Jaromír.; Klimt, Martin; Šihlík, Jan; Fliegel, Karel

    2015-09-01

    Meteor detection is one of the most important procedures in astronomical imaging. Meteor path in Earth's atmosphere is traditionally reconstructed from double station video observation system generating 2D image sequences. However, the atmospheric turbulence and other factors cause spatially-temporal fluctuations of image background, which makes the localization of meteor path more difficult. Our approach is based on nonlinear preprocessing of image intensity using Box-Cox and logarithmic transform as its particular case. The transformed image sequences are then differentiated along discrete coordinates to obtain statistical description of sky background fluctuations, which can be modeled by multivariate normal distribution. After verification and hypothesis testing, we use the statistical model for outlier detection. Meanwhile the isolated outlier points are ignored, the compact cluster of outliers indicates the presence of meteoroids after ignition.

  16. Quantitative tradeoffs between spatial, temporal, and thermometric resolution of nonresonant Raman thermometry for dynamic experiments.

    Science.gov (United States)

    McGrane, Shawn D; Moore, David S; Goodwin, Peter M; Dattelbaum, Dana M

    2014-01-01

    The ratio of Stokes to anti-Stokes nonresonant spontaneous Raman can provide an in situ thermometer that is noncontact, independent of any material specific parameters or calibrations, can be multiplexed spatially with line imaging, and can be time resolved for dynamic measurements. However, spontaneous Raman cross sections are very small, and thermometric measurements are often limited by the amount of laser energy that can be applied without damaging the sample or changing its temperature appreciably. In this paper, we quantitatively detail the tradeoff space between spatial, temporal, and thermometric accuracy measurable with spontaneous Raman. Theoretical estimates are pinned to experimental measurements to form realistic expectations of the resolution tradeoffs appropriate to various experiments. We consider the effects of signal to noise, collection efficiency, laser heating, pulsed laser ablation, and blackbody emission as limiting factors, provide formulae to help choose optimal conditions and provide estimates relevant to planning experiments along with concrete examples for single-shot measurements.

  17. Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

    Science.gov (United States)

    Estupinan Roldan, Kevin; Ortega Piedrahita, Marco A.; Benitez, Hernan D.

    2014-02-01

    Disorders associated with repeated trauma account for about 60% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.

  18. Risk assessment of flood disaster and forewarning model at different spatial-temporal scales

    Science.gov (United States)

    Zhao, Jun; Jin, Juliang; Xu, Jinchao; Guo, Qizhong; Hang, Qingfeng; Chen, Yaqian

    2018-05-01

    Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus

  19. Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

    Science.gov (United States)

    Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

    2012-12-01

    Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

  20. Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

    Directory of Open Access Journals (Sweden)

    Mika Gustafsson

    Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

  1. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-05-01

    Microarray technology has enriched the study of gene expression in such a way that scientists are now able to measure the expression levels of thousands of genes in a single experiment. Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification, interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This thesis aims on a comparative study of state-of-the-art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k- nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t- statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used for this study. Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in

  2. Sex hormones and gene expression signatures in peripheral blood from postmenopausal women - the NOWAC postgenome study

    Directory of Open Access Journals (Sweden)

    Rylander Charlotta

    2011-03-01

    Full Text Available Abstract Background Postmenopausal hormone therapy (HT influences endogenous hormone concentrations and increases the risk of breast cancer. Gene expression profiling may reveal the mechanisms behind this relationship. Our objective was to explore potential associations between sex hormones and gene expression in whole blood from a population-based, random sample of postmenopausal women Methods Gene expression, as measured by the Applied Biosystems microarray platform, was compared between hormone therapy (HT users and non-users and between high and low hormone plasma concentrations using both gene-wise analysis and gene set analysis. Gene sets found to be associated with HT use were further analysed for enrichment in functional clusters and network predictions. The gene expression matrix included 285 samples and 16185 probes and was adjusted for significant technical variables. Results Gene-wise analysis revealed several genes significantly associated with different types of HT use. The functional cluster analyses provided limited information on these genes. Gene set analysis revealed 22 gene sets that were enriched between high and low estradiol concentration (HT-users excluded. Among these were seven oestrogen related gene sets, including our gene list associated with systemic estradiol use, which thereby represents a novel oestrogen signature. Seven gene sets were related to immune response. Among the 15 gene sets enriched for progesterone, 11 overlapped with estradiol. No significant gene expression patterns were found for testosterone, follicle stimulating hormone (FSH or sex hormone binding globulin (SHBG. Conclusions Distinct gene expression patterns associated with sex hormones are detectable in a random group of postmenopausal women, as demonstrated by the finding of a novel oestrogen signature.

  3. Neighboring Genes Show Correlated Evolution in Gene Expression

    Science.gov (United States)

    Ghanbarian, Avazeh T.; Hurst, Laurence D.

    2015-01-01

    When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

  4. A deep auto-encoder model for gene expression prediction.

    Science.gov (United States)

    Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

    2017-11-17

    Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

  5. Genetic Variants Contribute to Gene Expression Variability in Humans

    Science.gov (United States)

    Hulse, Amanda M.; Cai, James J.

    2013-01-01

    Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed. PMID:23150607

  6. Fungal and plant gene expression in arbuscular mycorrhizal symbiosis.

    Science.gov (United States)

    Balestrini, Raffaella; Lanfranco, Luisa

    2006-11-01

    Arbuscular mycorrhizas (AMs) are a unique example of symbiosis between two eukaryotes, soil fungi and plants. This association induces important physiological changes in each partner that lead to reciprocal benefits, mainly in nutrient supply. The symbiosis results from modifications in plant and fungal cell organization caused by specific changes in gene expression. Recently, much effort has gone into studying these gene expression patterns to identify a wider spectrum of genes involved. We aim in this review to describe AM symbiosis in terms of current knowledge on plant and fungal gene expression profiles.

  7. Improved gene expression signature of testicular carcinoma in situ

    DEFF Research Database (Denmark)

    Almstrup, Kristian; Leffers, Henrik; Lothe, Ragnhild A

    2007-01-01

    on global gene expression in testicular CIS have been previously published. We have merged the two data sets on CIS samples (n = 6) and identified the shared gene expression signature in relation to expression in normal testis. Among the top-20 highest expressed genes, one-third was transcription factors...... development' were significantly altered and could collectively affect cellular pathways like the WNT signalling cascade, which thus may be disrupted in testicular CIS. The merged CIS data from two different microarray platforms, to our knowledge, provide the most precise CIS gene expression signature to date....

  8. Drug-loaded nanoparticles induce gene expression in human pluripotent stem cell derivatives

    Science.gov (United States)

    Gajbhiye, Virendra; Escalante, Leah; Chen, Guojun; Laperle, Alex; Zheng, Qifeng; Steyer, Benjamin; Gong, Shaoqin; Saha, Krishanu

    2013-12-01

    higher fibroblast proliferation levels and MMP activity. The results demonstrate that the PEG-H40-DXC nanoparticle system provides an effective tool to controlling gene expression in human stem cell derivatives. Electronic supplementary information (ESI) available: ESI containing 1H NMR spectra and additional fibroblast characterization data. See DOI: 10.1039/c3nr04794f

  9. Gene Expression Measurement Module (GEMM) - a fully automated, miniaturized instrument for measuring gene expression in space

    Science.gov (United States)

    Karouia, Fathi; Ricco, Antonio; Pohorille, Andrew; Peyvan, Kianoosh

    2012-07-01

    The capability to measure gene expression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure gene expression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

  10. Crosstalk between histone modifications maintains the developmental pattern of gene expression on a tissue-specific locus.

    Science.gov (United States)

    Hosey, Alison M; Chaturvedi, Chandra-Prakash; Brand, Marjorie

    2010-05-16

    Genome wide studies have provided a wealth of information related to histone modifications. Particular modifications, which can encompass both broad and discrete regions, are associated with certain genomic elements and gene expression status. Here we focus on how studies on the beta-globin gene cluster can complement the genome wide effort through the thorough dissection of histone modifying protein crosstalk. The beta-globin locus serves as a model system to study both regulation of gene expression driven at a distance by enhancers and mechanisms of developmental switching of clustered genes. We investigate recent studies, which uncover that histone methyltransferases, recruited at the beta-globin enhancer, control gene expression by long range propagation on chromatin. Specifically, we focus on how seemingly antagonistic complexes, such as those including MLL2, G9a and UTX, can cooperate to functionally regulate developmentally controlled gene expression. Finally, we speculate on the mechanisms of chromatin modifying complex propagation on genomic domains.

  11. The evolution of gene expression levels in mammalian organs

    DEFF Research Database (Denmark)

    Brawand, David; Soumillon, Magali; Necsulea, Anamaria

    2011-01-01

    and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped......Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across...... ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages...

  12. Gene expression programming for power system static security ...

    African Journals Online (AJOL)

    user

    Keywords: static security, gene expression programming, probabilistic neural network ... Hence digital computers are usually installed in operations control centers to gather ...... power system protection, and applications of AI in power systems.

  13. GAL4 enhancer trap strains with reporter gene expression during ...

    Indian Academy of Sciences (India)

    the development of adult brain in Drosophila melanogaster. C. R. VENKATESH ... vous system (CNS), at different time points during the pupal stage—a critical .... in frontal view, with further reduced reporter gene expression. Orthodenticle and ...

  14. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette

    2006-01-01

    Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

  15. Research Article Gene expression profiling for coronary artery ...

    Indian Academy of Sciences (India)

    Shiridhar Kashyap

    stored at -80˚C in nuclease free water for gene expression experiments. ..... So, identification of a unique signature for CAD globally as treatment target and early diagnostic biomarker needs ..... The colour of bar, blue, brown, grey and yellow.

  16. State-related alterations of gene expression in bipolar disorder

    DEFF Research Database (Denmark)

    Munkholm, Klaus; Vinberg, Maj; Berk, Michael

    2012-01-01

    Munkholm K, Vinberg M, Berk M, Kessing LV. State-related alterations of gene expression in bipolar disorder: a systematic review. Bipolar Disord 2012: 14: 684-696. © 2012 The Authors. Journal compilation © 2012 John Wiley & Sons A/S. Objective:  Alterations in gene expression in bipolar disorder...... have been found in numerous studies. It is unclear whether such alterations are related to specific mood states. As a biphasic disorder, mood state-related alterations in gene expression have the potential to point to markers of disease activity, and trait-related alterations might indicate...... vulnerability pathways. This review therefore evaluated the evidence for whether gene expression in bipolar disorder is state or trait related. Methods:  A systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline for reporting systematic reviews, based...

  17. Molecular subsets in the gene expression signatures of scleroderma skin.

    Directory of Open Access Journals (Sweden)

    Ausra Milano

    2008-07-01

    Full Text Available Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.

  18. Multiobjective optimization in Gene Expression Programming for Dew Point

    OpenAIRE

    Shroff, Siddharth; Dabhi, Vipul

    2013-01-01

    The processes occurring in climatic change evolution and their variations play a major role in environmental engineering. Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Gene expression programming is capable of modelling complex realities with great accuracy, allowing, at the same time, the extraction of knowledge from the evolved models compared to other learning algorithms. This research aims to use Gene Expression Programming ...

  19. Host Gene Expression Analysis in Sri Lankan Melioidosis Patients

    Science.gov (United States)

    2017-06-19

    CCL5 Chemokine (C-C motif) ligand 5 /RANTES. IFNγ Interferon gamma TNFα Tumor necrosis factor alpha HMGB1 High mobility group box 1 protein /high...aim of this study was to analyze gene expression levels of human host factors in melioidosis patients and establish useful correlation with disease...PBMC’s) of study subjects. Gene expression profiles of 25 gene targets including 19 immune response genes and 6 epigenetic factors were analyzed by

  20. Semi-supervised consensus clustering for gene expression data analysis

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

    Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

  1. Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset

    Science.gov (United States)

    Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

    2016-01-01

    Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

  2. The Spatial-Temporal Reasoning States of Children Who Play a Musical Instrument, Regarding the Mathematics Lesson: Teachers' Views

    Science.gov (United States)

    Tezer, Murat; Cumhur, Meryem; Hürsen, Emine

    2016-01-01

    The aim of this study is to try to investigate the spatial-temporal reasoning states of primary school children between the ages 8 and 11 who play an instrument, regarding mathematics lessons from the teachers' views. This current study is both qualitative and quantitative in nature. In other words, the mixed research method was used in the study.…

  3. Genetic Networks and Anticipation of Gene Expression Patterns

    Science.gov (United States)

    Gebert, J.; Lätsch, M.; Pickl, S. W.; Radde, N.; Weber, G.-W.; Wünschiers, R.

    2004-08-01

    An interesting problem for computational biology is the analysis of time-series expression data. Here, the application of modern methods from dynamical systems, optimization theory, numerical algorithms and the utilization of implicit discrete information lead to a deeper understanding. In [1], we suggested to represent the behavior of time-series gene expression patterns by a system of ordinary differential equations, which we analytically and algorithmically investigated under the parametrical aspect of stability or instability. Our algorithm strongly exploited combinatorial information. In this paper, we deepen, extend and exemplify this study from the viewpoint of underlying mathematical modelling. This modelling consists in evaluating DNA-microarray measurements as the basis of anticipatory prediction, in the choice of a smooth model given by differential equations, in an approach of the right-hand side with parametric matrices, and in a discrete approximation which is a least squares optimization problem. We give a mathematical and biological discussion, and pay attention to the special case of a linear system, where the matrices do not depend on the state of expressions. Here, we present first numerical examples.

  4. Bayesian assignment of gene ontology terms to gene expression experiments.

    Science.gov (United States)

    Sykacek, P

    2012-09-15

    Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

  5. Bayesian assignment of gene ontology terms to gene expression experiments

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

    Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

  6. Detecting microRNA activity from gene expression data

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-05-18

    Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  7. Detecting microRNA activity from gene expression data.

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-01-01

    BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  8. A comparative study of three different gene expression analysis methods.

    Science.gov (United States)

    Choe, Jae Young; Han, Hyung Soo; Lee, Seon Duk; Lee, Hanna; Lee, Dong Eun; Ahn, Jae Yun; Ryoo, Hyun Wook; Seo, Kang Suk; Kim, Jong Kun

    2017-12-04

    TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for gene expression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human gene expression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human gene expression analysis. We compared three gene expression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of gene expression analysis. In the comparison of three gene expression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

  9. Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

    Science.gov (United States)

    Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

    2016-07-21

    Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

  10. Serial analysis of gene expression (SAGE) in normal human trabecular meshwork.

    Science.gov (United States)

    Liu, Yutao; Munro, Drew; Layfield, David; Dellinger, Andrew; Walter, Jeffrey; Peterson, Katherine; Rickman, Catherine Bowes; Allingham, R Rand; Hauser, Michael A

    2011-04-08

    To identify the genes expressed in normal human trabecular meshwork tissue, a tissue critical to the pathogenesis of glaucoma. Total RNA was extracted from human trabecular meshwork (HTM) harvested from 3 different donors. Extracted RNA was used to synthesize individual SAGE (serial analysis of gene expression) libraries using the I-SAGE Long kit from Invitrogen. Libraries were analyzed using SAGE 2000 software to extract the 17 base pair sequence tags. The extracted sequence tags were mapped to the genome using SAGE Genie map. A total of 298,834 SAGE tags were identified from all HTM libraries (96,842, 88,126, and 113,866 tags, respectively). Collectively, there were 107,325 unique tags. There were 10,329 unique tags with a minimum of 2 counts from a single library. These tags were mapped to known unique Unigene clusters. Approximately 29% of the tags (orphan tags) did not map to a known Unigene cluster. Thirteen percent of the tags mapped to at least 2 Unigene clusters. Sequence tags from many glaucoma-related genes, including myocilin, optineurin, and WD repeat domain 36, were identified. This is the first time SAGE analysis has been used to characterize the gene expression profile in normal HTM. SAGE analysis provides an unbiased sampling of gene expression of the target tissue. These data will provide new and valuable information to improve understanding of the biology of human aqueous outflow.

  11. Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

    Science.gov (United States)

    Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

    2017-10-01

    A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

  12. A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis.

    Science.gov (United States)

    Voyle, Nicola; Keohane, Aoife; Newhouse, Stephen; Lunnon, Katie; Johnston, Caroline; Soininen, Hilkka; Kloszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon; Hodges, Angela; Kiddle, Steven; Dobson, Richard Jb

    2016-01-01

    Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer's disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. Gene and pathway level models performed similarly to each other and to a model based on demographic information only. Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

  13. Both noncoding and protein-coding RNAs contribute to gene expression evolution in the primate brain.

    Science.gov (United States)

    Babbitt, Courtney C; Fedrigo, Olivier; Pfefferle, Adam D; Boyle, Alan P; Horvath, Julie E; Furey, Terrence S; Wray, Gregory A

    2010-01-18

    Despite striking differences in cognition and behavior between humans and our closest primate relatives, several studies have found little evidence for adaptive change in protein-coding regions of genes expressed primarily in the brain. Instead, changes in gene expression may underlie many cognitive and behavioral differences. Here, we used digital gene expression: tag profiling (here called Tag-Seq, also called DGE:tag profiling) to assess changes in global transcript abundance in the frontal cortex of the brains of 3 humans, 3 chimpanzees, and 3 rhesus macaques. A substantial fraction of transcripts we identified as differentially transcribed among species were not assayed in previous studies based on microarrays. Differentially expressed tags within coding regions are enriched for gene functions involved in synaptic transmission, transport, oxidative phosphorylation, and lipid metabolism. Importantly, because Tag-Seq technology provides strand-specific information about all polyadenlyated transcripts, we were able to assay expression in noncoding intragenic regions, including both sense and antisense noncoding transcripts (relative to nearby genes). We find that many noncoding transcripts are conserved in both location and expression level between species, suggesting a possible functional role. Lastly, we examined the overlap between differential gene expression and signatures of positive selection within putative promoter regions, a sign that these differences represent adaptations during human evolution. Comparative approaches may provide important insights into genes responsible for differences in cognitive functions between humans and nonhuman primates, as well as highlighting new candidate genes for studies investigating neurological disorders.

  14. GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Chris Cheadle

    2007-01-01

    Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

  15. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

    Directory of Open Access Journals (Sweden)

    Tintle Nathan L

    2012-08-01

    Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  16. Creation of subsonic macro-and microjets facilities and automated measuring system (AMS-2) for the spatial - temporal hot - wire anemometric visualization of jet flow field

    Science.gov (United States)

    Sorokin, A. M.; Grek, G. R.; Gilev, V. M.; Zverkov, I. D.

    2017-10-01

    Macro-and microjets facilities for generation of the round and plane subsonic jets are designed and fabricated. Automated measuring system (AMS - 2) for the spatial - temporal hot - wire anemometric visualization of jet flow field is designed and fabricated. Coordinate device and unit of the measurement, collecting, storage and processing of hot - wire anemometric information were integrated in the AMS. Coordinate device is intended for precision movement of the hot - wire probe in jet flow field according to the computer program. At the same time accuracy of the hot - wire probe movement is 5 microns on all three coordinates (x, y, z). Unit of measurement, collecting, storage and processing of hot - wire anemometric information is intended for the hot - wire anemometric measurement of the jet flow field parameters (registration of the mean - U and fluctuation - u' characteristics of jet flow velocity), their accumulation and preservation in the computer memory, and also carries out their processing according to certain programms.

  17. Extraction of spatial-temporal rules from mesoscale eddies in the South China Sea Based on rough set theory

    Science.gov (United States)

    Du, Y.; Fan, X.; He, Z.; Su, F.; Zhou, C.; Mao, H.; Wang, D.

    2011-06-01

    In this paper, a rough set theory is introduced to represent spatial-temporal relationships and extract the corresponding rules from typical mesoscale-eddy states in the South China Sea (SCS). Three decision attributes are adopted in this study, which make the approach flexible in retrieving spatial-temporal rules with different features. Spatial-temporal rules of typical states in the SCS are extracted as three decision attributes, which then are confirmed by the previous works. The results demonstrate that this approach is effective in extracting spatial-temporal rules from typical mesoscale-eddy states, and therefore provides a powerful approach to forecasts in the future. Spatial-temporal rules in the SCS indicate that warm eddies following the rules are generally in the southeastern and central SCS around 2000 m isobaths in winter. Their intensity and vorticity are weaker than those of cold eddies. They usually move a shorter distance. By contrast, cold eddies are in 2000 m-deeper regions of the southwestern and northeastern SCS in spring and fall. Their intensity and vorticity are strong. Usually they move a long distance. In winter, a few rules are followed by cold eddies in the northern tip of the basin and southwest of Taiwan Island rather than warm eddies, indicating cold eddies may be well-regulated in the region. Several warm-eddy rules are achieved west of Luzon Island, indicating warm eddies may be well-regulated in the region as well. Otherwise, warm and cold eddies are distributed not only in the jet flow off southern Vietnam induced by intraseasonal wind stress in summer-fall, but also in the northern shallow water, which should be a focus of future study.

  18. Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.

    Directory of Open Access Journals (Sweden)

    Rebeca Sanz-Pamplona

    Full Text Available INTRODUCTION: The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. METHODS: A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. RESULTS: Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. CONCLUSIONS: The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.

  19. SEGEL: A Web Server for Visualization of Smoking Effects on Human Lung Gene Expression.

    Science.gov (United States)

    Xu, Yan; Hu, Brian; Alnajm, Sammy S; Lu, Yin; Huang, Yangxin; Allen-Gipson, Diane; Cheng, Feng

    2015-01-01

    Cigarette smoking is a major cause of death worldwide resulting in over six million deaths per year. Cigarette smoke contains complex mixtures of chemicals that are harmful to nearly all organs of the human body, especially the lungs. Cigarette smoking is considered the major risk factor for many lung diseases, particularly chronic obstructive pulmonary diseases (COPD) and lung cancer. However, the underlying molecular mechanisms of smoking-induced lung injury associated with these lung diseases still remain largely unknown. Expression microarray techniques have been widely applied to detect the effects of smoking on gene expression in different human cells in the lungs. These projects have provided a lot of useful information for researchers to understand the potential molecular mechanism(s) of smoke-induced pathogenesis. However, a user-friendly web server that would allow scientists to fast query these data sets and compare the smoking effects on gene expression across different cells had not yet been established. For that reason, we have integrated eight public expression microarray data sets from trachea epithelial cells, large airway epithelial cells, small airway epithelial cells, and alveolar macrophage into an online web server called SEGEL (Smoking Effects on Gene Expression of Lung). Users can query gene expression patterns across these cells from smokers and nonsmokers by gene symbols, and find the effects of smoking on the gene expression of lungs from this web server. Sex difference in response to smoking is also shown. The relationship between the gene expression and cigarette smoking consumption were calculated and are shown in the server. The current version of SEGEL web server contains 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 Plus 2.0 platform. SEGEL will be an invaluable resource for researchers interested in the effects of smoking on gene expression in the lungs. The server also provides useful information

  20. Spatial-temporal particularities of the ecological status of surface water bodies and pollution sources from Siret river basin

    Directory of Open Access Journals (Sweden)

    Dan DĂSCĂLIȚA

    2011-06-01

    Full Text Available The ecological status of surface water bodies from Siret River Basin is monitored systematically and spatial in accordance with the requirements of European Directives in the water area. Analysis temporary and spatial of qualitative and quantitative status of surface waters (rivers, lakes is achieved according to the specificities of each body of water resulting from physical and geographical conditions, climatic and hydromorphological regimes of river basin and from human activities.In order to know of those features, there are needed specific monitoring systems of water bodies. The parametersunderlying the assessment of ecological status of rivers and lakes are monitored systematically and temporary: daily, monthly, quarterly, annually, according to these characteristics. In this context, the daily variations in environmental condition, expresses the current status of surface waters. Monthly changes are correlated with climate change and characterize the seasonal variations. On annual basis are identified the mean, minimum and maximum for each parameter and the trends (increase, decrease, regularity, periodicity, changes, etc.. Based on this information, extensive to multiannual level, itcan achieve medium and long term forecasts and it might be issued the concepts and strategies for maintaining a balance and sustainable development of water resources.In this paper we have presented some issues related to the synthesis of spatial-temporal ecological status of water bodies managed by Administration of Siret Water Basin(ABAS. Results of studies on the ecological status of water bodies have been presented for the year 2009. Also, in this paper it was presented an evolution of the quantities ofpollutants from wastewater discharged in surface receptors and their purification by water users from of activity of ABAS area in 1999-2009 periods.

  1. Argudas: lessons for argumentation in biology based on a gene expression use case

    OpenAIRE

    McLeod, Kenneth; Ferguson, Gus; Burger, Albert

    2012-01-01

    Background In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both...

  2. Three-Dimensional Water and Carbon Cycle Modeling at High Spatial-Temporal Resolutions

    Science.gov (United States)

    Liao, C.; Zhuang, Q.

    2017-12-01

    Terrestrial ecosystems in cryosphere are very sensitive to the global climate change due to the presence of snow covers, mountain glaciers and permafrost, especially when the increase in near surface air temperature is almost twice as large as the global average. However, few studies have investigated the water and carbon cycle dynamics using process-based hydrological and biogeochemistry modeling approach. In this study, we used three-dimensional modeling approach at high spatial-temporal resolutions to investigate the water and carbon cycle dynamics for the Tanana Flats Basin in interior Alaska with emphases on dissolved organic carbon (DOC) dynamics. The results have shown that: (1) lateral flow plays an important role in water and carbon cycle, especially in dissolved organic carbon (DOC) dynamics. (2) approximately 2.0 × 104 kg C yr-1 DOC is exported to the hydrological networks and it compromises 1% and 0.01% of total annual gross primary production (GPP) and total organic carbon stored in soil, respectively. This study has established an operational and flexible framework to investigate and predict the water and carbon cycle dynamics under the changing climate.

  3. Spatial-temporal-covariance-based modeling, analysis, and simulation of aero-optics wavefront aberrations.

    Science.gov (United States)

    Vogel, Curtis R; Tyler, Glenn A; Wittich, Donald J

    2014-07-01

    We introduce a framework for modeling, analysis, and simulation of aero-optics wavefront aberrations that is based on spatial-temporal covariance matrices extracted from wavefront sensor measurements. Within this framework, we present a quasi-homogeneous structure function to analyze nonhomogeneous, mildly anisotropic spatial random processes, and we use this structure function to show that phase aberrations arising in aero-optics are, for an important range of operating parameters, locally Kolmogorov. This strongly suggests that the d5/3 power law for adaptive optics (AO) deformable mirror fitting error, where d denotes actuator separation, holds for certain important aero-optics scenarios. This framework also allows us to compute bounds on AO servo lag error and predictive control error. In addition, it provides us with the means to accurately simulate AO systems for the mitigation of aero-effects, and it may provide insight into underlying physical processes associated with turbulent flow. The techniques introduced here are demonstrated using data obtained from the Airborne Aero-Optics Laboratory.

  4. Spatial-temporal variability of leaf chlorophyll and its relationship with cocoa yield

    Directory of Open Access Journals (Sweden)

    Caique C. Medauar

    Full Text Available ABSTRACT The objective of this study was to evaluate the spatial-temporal variability of leaf chlorophyll index and its relationship with cocoa yield. The experiment was carried out in an experimental area of cocoa production located in Ilhéus, Bahia State, Brazil. Leaf chlorophyll content was measured in September, October, January, February, March and April in the 2014/2015 season, at each sampling point of a regular grid by using a portable chlorophyll meter. Under the same conditions, yield was evaluated and the data were submitted to descriptive statistics and a linear correlation study. Geostatistical analysis was used to determine and quantify the spatial and temporal variability of leaf chlorophyll index and yield. Leaf chlorophyll index varied over the period evaluated, but the months of February, March and April showed no spatial dependence in the study area, indicating absence of temporal stability. Cocoa monthly yield, except in January, presented high spatial variability. Under the conditions of this study, it was not possible to establish a relationship between leaf chlorophyll index and cocoa yield.

  5. Spatial Temporal Dynamics and Molecular Evolution of Re-Emerging Rabies Virus in Taiwan

    Directory of Open Access Journals (Sweden)

    Yung-Cheng Lin

    2016-03-01

    Full Text Available Taiwan has been recognized by the World Organization for Animal Health as rabies-free since 1961. Surprisingly, rabies virus (RABV was identified in a dead Formosan ferret badger in July 2013. Later, more infected ferret badgers were reported from different geographic regions of Taiwan. In order to know its evolutionary history and spatial temporal dynamics of this virus, phylogeny was reconstructed by maximum likelihood and Bayesian methods based on the full-length of glycoprotein (G, matrix protein (M, and nucleoprotein (N genes. The evolutionary rates and phylogeographic were determined using Beast and SPREAD software. Phylogenetic trees showed a monophyletic group containing all of RABV isolates from Taiwan and it further separated into three sub-groups. The estimated nucleotide substitution rates of G, M, and N genes were between 2.49 × 10−4–4.75 × 10−4 substitutions/site/year, and the mean ratio of dN/dS was significantly low. The time of the most recent common ancestor was estimated around 75, 89, and 170 years, respectively. Phylogeographic analysis suggested the origin of the epidemic could be in Eastern Taiwan, then the Formosan ferret badger moved across the Central Range of Taiwan to western regions and separated into two branches. In this study, we illustrated the evolution history and phylogeographic of RABV in Formosan ferret badgers.

  6. Spatial-temporal analysis of building surface temperatures in Hung Hom

    Science.gov (United States)

    Zeng, Ying; Shen, Yueqian

    2015-12-01

    This thesis presents a study on spatial-temporal analysis of building surface temperatures in Hung Hom. Observations were collected from Aug 2013 to Oct 2013 at a 30-min interval, using iButton sensors (N=20) covering twelve locations in Hung Hom. And thermal images were captured in PolyU from 05 Aug 2013 to 06 Aug 2013. A linear regression model of iButton and thermal records is established to calibrate temperature data. A 3D modeling system is developed based on Visual Studio 2010 development platform, using ArcEngine10.0 component, Microsoft Access 2010 database and C# programming language. The system realizes processing data, spatial analysis, compound query and 3D face temperature rendering and so on. After statistical analyses, building face azimuths are found to have a statistically significant relationship with sun azimuths at peak time. And seasonal building temperature changing also corresponds to the sun angle and sun azimuth variations. Building materials are found to have a significant effect on building surface temperatures. Buildings with lower albedo materials tend to have higher temperatures and larger thermal conductivity material have significant diurnal variations. For the geographical locations, the peripheral faces of campus have higher temperatures than the inner faces during day time and buildings located at the southeast are cooler than the western. Furthermore, human activity is found to have a strong relationship with building surface temperatures through weekday and weekend comparison.

  7. The spatial-temporal characteristics of type I collagen-based extracellular matrix.

    Science.gov (United States)

    Jones, Christopher Allen Rucksack; Liang, Long; Lin, Daniel; Jiao, Yang; Sun, Bo

    2014-11-28

    Type I collagen abounds in mammalian extracellular matrix (ECM) and is crucial to many biophysical processes. While previous studies have mostly focused on bulk averaged properties, here we provide a comprehensive and quantitative spatial-temporal characterization of the microstructure of type I collagen-based ECM as the gelation temperature varies. The structural characteristics including the density and nematic correlation functions are obtained by analyzing confocal images of collagen gels prepared at a wide range of gelation temperatures (from 16 °C to 36 °C). As temperature increases, the gel microstructure varies from a "bundled" network with strong orientational correlation between the fibers to an isotropic homogeneous network with no significant orientational correlation, as manifested by the decaying of length scales in the correlation functions. We develop a kinetic Monte-Carlo collagen growth model to better understand how ECM microstructure depends on various environmental or kinetic factors. We show that the nucleation rate, growth rate, and an effective hydrodynamic alignment of collagen fibers fully determines the spatiotemporal fluctuations of the density and orientational order of collagen gel microstructure. Also the temperature dependence of the growth rate and nucleation rate follow the prediction of classical nucleation theory.

  8. Spatial Temporal Image Correlation Spectroscopy (STICS) for Flow Analysis with Application for Blood Flow Mapping

    International Nuclear Information System (INIS)

    Rossow, Molly; Gratton, Enrico; Mantulin, William M.

    2009-01-01

    It is important for surgeons to be able to measure blood flow in exposed arterioles during surgery. We report our progress in the development of an optical technique that will measure blood flow in surgically exposed blood vessels and enable previously difficult measurements. By monitoring optical fluctuations, the optical technique, based on Spatial Temporal Image Correlation (STICS), will directly measure the velocity of micron-scale particles--such as red blood cells. It will complement existing technology and provide qualitative measurements that were not previously possible. It relies on the concept that blood, when viewed on a small enough scale, is an inhomogeneous substance. Individual blood cells passing between a near-infrared light source and a detector will cause fluctuations in the transmitted optical signal. The speed, direction, and flow pattern of blood cells can be determined from these optical fluctuations. We present a series of computer simulations and experiments on phantom and animal systems to test this technique's ability to map complex flow patterns.

  9. Spatial-temporal variation of low-frequency earthquake bursts near Parkfield, California

    Science.gov (United States)

    Wu, Chunquan; Guyer, Robert; Shelly, David R.; Trugman, D.; Frank, William; Gomberg, Joan S.; Johnson, P.

    2015-01-01

    Tectonic tremor (TT) and low-frequency earthquakes (LFEs) have been found in the deeper crust of various tectonic environments globally in the last decade. The spatial-temporal behaviour of LFEs provides insight into deep fault zone processes. In this study, we examine recurrence times from a 12-yr catalogue of 88 LFE families with ∼730 000 LFEs in the vicinity of the Parkfield section of the San Andreas Fault (SAF) in central California. We apply an automatic burst detection algorithm to the LFE recurrence times to identify the clustering behaviour of LFEs (LFE bursts) in each family. We find that the burst behaviours in the northern and southern LFE groups differ. Generally, the northern group has longer burst duration but fewer LFEs per burst, while the southern group has shorter burst duration but more LFEs per burst. The southern group LFE bursts are generally more correlated than the northern group, suggesting more coherent deep fault slip and relatively simpler deep fault structure beneath the locked section of SAF. We also found that the 2004 Parkfield earthquake clearly increased the number of LFEs per burst and average burst duration for both the northern and the southern groups, with a relatively larger effect on the northern group. This could be due to the weakness of northern part of the fault, or the northwesterly rupture direction of the Parkfield earthquake.

  10. EEG/MEG Source Reconstruction with Spatial-Temporal Two-Way Regularized Regression

    KAUST Repository

    Tian, Tian Siva

    2013-07-11

    In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously through minimizing a single penalized least squares criterion. The novelty of our methodology is the simultaneous consideration of three desirable properties of the reconstructed source signals, that is, spatial focality, spatial smoothness, and temporal smoothness. The desirable properties are achieved by using three separate penalty functions in the penalized regression framework. Specifically, we impose a roughness penalty in the temporal domain for temporal smoothness, and a sparsity-inducing penalty and a graph Laplacian penalty in the spatial domain for spatial focality and smoothness. We develop a computational efficient multilevel block coordinate descent algorithm to implement the method. Using a simulation study with several settings of different spatial complexity and two real MEG examples, we show that the proposed method outperforms existing methods that use only a subset of the three penalty functions. © 2013 Springer Science+Business Media New York.

  11. Spatial Temporal Image Correlation Spectroscopy (STICS) for Flow Analysis with Application for Blood Flow Mapping (abstract)

    Science.gov (United States)

    Rossow, Molly; Mantulin, William M.; Gratton, Enrico

    2009-04-01

    It is important for surgeons to be able to measure blood flow in exposed arterioles during surgery. We report our progress in the development of an optical technique that will measure blood flow in surgically exposed blood vessels and enable previously difficult measurements. By monitoring optical fluctuations, the optical technique, based on Spatial Temporal Image Correlation (STICS), will directly measure the velocity of micron-scale particles-such as red blood cells. It will complement existing technology and provide qualitative measurements that were not previously possible. It relies on the concept that blood, when viewed on a small enough scale, is an inhomogeneous substance. Individual blood cells passing between a near-infrared light source and a detector will cause fluctuations in the transmitted optical signal. The speed, direction, and flow pattern of blood cells can be determined from these optical fluctuations. We present a series of computer simulations and experiments on phantom and animal systems to test this technique's ability to map complex flow patterns.

  12. Altered gene expression in human placentas after IVF/ICSI.

    Science.gov (United States)

    Nelissen, Ewka C M; Dumoulin, John C M; Busato, Florence; Ponger, Loïc; Eijssen, Lars M; Evers, Johannes L H; Tost, Jörg; van Montfoort, Aafke P A

    2014-12-01

    each group) to investigate the expression of non-imprinted genes as well. Both H19 and PHLDA2 showed a significant change, respectively, a 1.3-fold (P = 0.033) and 1.5-fold (P = 0.002) increase in mRNA expression in the IVF/ICSI versus control group. However, we found no indication that there is an increased frequency of LOI in IVF/ICSI placental samples. Genome-wide mRNA expression revealed 13 significantly overrepresented biological pathways involved in metabolism, immune response, transmembrane signalling and cell cycle control, which were mostly up-regulated in the IVF/ICSI placental samples. Only a subset of samples was found to be fully informative, which unavoidably led to lower sample numbers for our LOI analysis. Our study cannot distinguish whether the reported differences in the IVF/ICSI group are exclusively attributable to the IVF/ICSI technique itself or to the underlying subfertility of the patients. Whether these placental adaptations observed in pregnancies conceived by IVF/ICSI might be connected to an adverse perinatal outcome after IVF remains unknown. However, it is possible that these differences affect fetal development and long-term patterns of gene expression, as well as maternal gestational physiology. Partly funded by an unrestricted research grant by Organon BV (now MSD BV) and GROW School for Oncology and Developmental Biology without any role in study design, data collection and analysis or preparation of the manuscript. No conflict of interests to declare. Dutch Trial Registry (NTR) number 1298. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Telemetric Technologies for the Assay of Gene Expression

    Science.gov (United States)

    Paul, Anna-Lisa; Bamsey, Matthew; Berinstain, Alain; Neron, Philip; Graham, Thomas; Ferl, Robert

    Telemetric data collection has been widely used in spaceflight applications where human participation is limited (orbital mission payloads) or unfeasible (planetary landers, satellites, and probes). The transmission of digital data from electronic sensors of typical environmental parameters, growth patterns and physical properties of materials is routine telemetry, and even the collection and transmission of deep space images is a standard tool of astrophysics. But telemetric imaging for current biological payloads has thus far been limited to the collection of standard white-light photography that is largely confined to reporting the surface characteristics of the specimens involved. Advances in imaging technologies that facilitate the collection of a variety of light wavelengths will expand the science return on biological payloads to include evaluations of the molecular genetic response of organisms to the spaceflight or extraterrestrial environment, with minimal or no human intervention. Advanced imaging technology in combination with biologically engineered sensor organisms can create a system that can report via telemetry on the patterns of gene expression required to adapt to a novel environment. The utilization of genetically engineered plants as biosensors has made elegant strides in the recent years, providing keen insights into the health of plants in general and particularly in the nature and cellular location of stress responses. Moreover, molecular responses to gravitational vectors have been elegantly analyzed with fluorescent tools. Green Fluorescence Protein (GFP) and other fluorophores have made it possible for analyses of gene expression and biological responses to occur telemetrically, with the information potentially delivered to the investigator over large distances as simple, preprocessed fluorescence images. Having previously deployed transgenic plant biosensors to evaluate responses to orbital spaceflight, we wish to develop both the plants

  14. Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

    Directory of Open Access Journals (Sweden)

    Kleinjans Jos

    2008-09-01

    Full Text Available Abstract Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh, is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a

  15. Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution.

    Science.gov (United States)

    Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

    2008-09-02

    In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that

  16. Comparative modular analysis of gene expression in vertebrate organs

    Directory of Open Access Journals (Sweden)

    Piasecka Barbara

    2012-03-01

    Full Text Available Abstract Background The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Results Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Conclusions Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

  17. Comparative modular analysis of gene expression in vertebrate organs.

    Science.gov (United States)

    Piasecka, Barbara; Kutalik, Zoltán; Roux, Julien; Bergmann, Sven; Robinson-Rechavi, Marc

    2012-03-29

    The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

  18. Supervised classification of combined copy number and gene expression data

    Directory of Open Access Journals (Sweden)

    Riccadonna S.

    2007-12-01

    Full Text Available In this paper we apply a predictive profiling method to genome copy number aberrations (CNA in combination with gene expression and clinical data to identify molecular patterns of cancer pathophysiology. Predictive models and optimal feature lists for the platforms are developed by a complete validation SVM-based machine learning system. Ranked list of genome CNA sites (assessed by comparative genomic hybridization arrays – aCGH and of differentially expressed genes (assessed by microarray profiling with Affy HG-U133A chips are computed and combined on a breast cancer dataset for the discrimination of Luminal/ ER+ (Lum/ER+ and Basal-like/ER- classes. Different encodings are developed and applied to the CNA data, and predictive variable selection is discussed. We analyze the combination of profiling information between the platforms, also considering the pathophysiological data. A specific subset of patients is identified that has a different response to classification by chromosomal gains and losses and by differentially expressed genes, corroborating the idea that genomic CNA can represent an independent source for tumor classification.

  19. Genetic architecture of gene expression in the chicken

    Directory of Open Access Journals (Sweden)

    Stanley Dragana

    2013-01-01

    Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

  20. Gene Expression Measurement Module (GEMM) - A Fully Automated, Miniaturized Instrument for Measuring Gene Expression in Space

    Science.gov (United States)

    Pohorille, Andrew; Peyvan, Kia; Karouia, Fathi; Ricco, Antonio

    2012-01-01

    The capability to measure gene expression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. Supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with

  1. A robust approach based on Weibull distribution for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

    Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

  2. The RNAPII-CTD Maintains Genome Integrity through Inhibition of Retrotransposon Gene Expression and Transposition.

    Directory of Open Access Journals (Sweden)

    Maria J Aristizabal

    2015-10-01

    Full Text Available RNA polymerase II (RNAPII contains a unique C-terminal domain that is composed of heptapeptide repeats and which plays important regulatory roles during gene expression. RNAPII is responsible for the transcription of most protein-coding genes, a subset of non-coding genes, and retrotransposons. Retrotransposon transcription is the first step in their multiplication cycle, given that the RNA intermediate is required for the synthesis of cDNA, the material that is ultimately incorporated into a new genomic location. Retrotransposition can have grave consequences to genome integrity, as integration events can change the gene expression landscape or lead to alteration or loss of genetic information. Given that RNAPII transcribes retrotransposons, we sought to investigate if the RNAPII-CTD played a role in the regulation of retrotransposon gene expression. Importantly, we found that the RNAPII-CTD functioned to maintaining genome integrity through inhibition of retrotransposon gene expression, as reducing CTD length significantly increased expression and transposition rates of Ty1 elements. Mechanistically, the increased Ty1 mRNA levels in the rpb1-CTD11 mutant were partly due to Cdk8-dependent alterations to the RNAPII-CTD phosphorylation status. In addition, Cdk8 alone contributed to Ty1 gene expression regulation by altering the occupancy of the gene-specific transcription factor Ste12. Loss of STE12 and TEC1 suppressed growth phenotypes of the RNAPII-CTD truncation mutant. Collectively, our results implicate Ste12 and Tec1 as general and important contributors to the Cdk8, RNAPII-CTD regulatory circuitry as it relates to the maintenance of genome integrity.

  3. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  4. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-11-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  5. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  6. Whole-body gene expression pattern registration in Platynereis larvae.

    Science.gov (United States)

    Asadulina, Albina; Panzera, Aurora; Verasztó, Csaba; Liebig, Christian; Jékely, Gáspár

    2012-12-03

    Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the

  7. Whole-body gene expression pattern registration in Platynereis larvae

    Directory of Open Access Journals (Sweden)

    Asadulina Albina

    2012-12-01

    Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

  8. Garlic Influences Gene Expression In Vivo and In Vitro.

    Science.gov (United States)

    Charron, Craig S; Dawson, Harry D; Novotny, Janet A

    2016-02-01

    There is a large body of preclinical research aimed at understanding the roles of garlic and garlic-derived preparations in the promotion of human health. Most of this research has targeted the possible functions of garlic in maintaining cardiovascular health and in preventing and treating cancer. A wide range of outcome variables has been used to investigate the bioactivity of garlic, ranging from direct measures of health status such as cholesterol concentrations, blood pressure, and changes in tumor size and number, to molecular and biochemical measures such as mRNA gene expression, protein concentration, enzyme activity, and histone acetylation status. Determination of how garlic influences mRNA gene expression has proven to be a valuable approach to elucidating the mechanisms of garlic bioactivity. Preclinical studies investigating the health benefits of garlic far outnumber human studies and have made frequent use of mRNA gene expression measurement. There is an immediate need to understand mRNA gene expression in humans as well. Although safety and ethical constraints limit the types of available human tissue, peripheral whole blood is readily accessible, and measuring mRNA gene expression in whole blood may provide a unique window to understanding how garlic intake affects human health. © 2016 American Society for Nutrition.

  9. Pervasive Effects of Aging on Gene Expression in Wild Wolves

    Science.gov (United States)

    Charruau, Pauline; Johnston, Rachel A.; Stahler, Daniel R.; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W.; vonHoldt, Bridgett M.; Cole, Steven W.; Tung, Jenny; Wayne, Robert K.

    2016-01-01

    Abstract Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566

  10. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    International Nuclear Information System (INIS)

    Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

    2011-01-01

    The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

  11. Gene expression patterns in pancreatic tumors, cells and tissues.

    Directory of Open Access Journals (Sweden)

    Anson W Lowe

    2007-03-01

    Full Text Available Cancers of the pancreas originate from both the endocrine and exocrine elements of the organ, and represent a major cause of cancer-related death. This study provides a comprehensive assessment of gene expression for pancreatic tumors, the normal pancreas, and nonneoplastic pancreatic disease.DNA microarrays were used to assess the gene expression for surgically derived pancreatic adenocarcinomas, islet cell tumors, and mesenchymal tumors. The addition of normal pancreata, isolated islets, isolated pancreatic ducts, and pancreatic adenocarcinoma cell lines enhanced subsequent analysis by increasing the diversity in gene expression profiles obtained. Exocrine, endocrine, and mesenchymal tumors displayed unique gene expression profiles. Similarities in gene expression support the pancreatic duct as the origin of adenocarcinomas. In addition, genes highly expressed in other cancers and associated with specific signal transduction pathways were also found in pancreatic tumors.The scope of the present work was enhanced by the inclusion of publicly available datasets that encompass a wide spectrum of human tissues and enabled the identification of candidate genes that may serve diagnostic and therapeutic goals.

  12. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  13. Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Liying Yang

    2016-01-01

    Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

  14. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount ...

  15. Shrinkage Approach for Gene Expression Data Analysis

    Czech Academy of Sciences Publication Activity Database

    Haman, Jiří; Valenta, Zdeněk

    2013-01-01

    Roč. 9, č. 3 (2013), s. 2-8 ISSN 1801-5603 Grant - others:UK(CZ) SVV-2013-266517 Institutional support: RVO:67985807 Keywords : microarray technology * high dimensional data * mean squared error * James-Stein shrinkage estimator * mutual information Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2013/3/Haman_en.pdf

  16. Spatial-Temporal Hotspot Pattern Analysis of Provincial Environmental Pollution Incidents and Related Regional Sustainable Management in China in the Period 1995–2012

    Directory of Open Access Journals (Sweden)

    Lei Ding

    2015-10-01

    Full Text Available Spatial-temporal hotspot pattern analysis of environmental pollution incidents provides an indispensable source of information for the further development of incident prevention measures. In this study, the spatial-temporal patterns of environmental pollution incidents in China in the period of 1995–2012 were analyzed, using the Spatial Getis-Ord statistic and an Improved Prediction Accuracy Index (IAPI. The results show that, in this period, the occurrence of environmental incidents exhibited a dynamic growth pattern but then dropped and continued to drop after the year 2006, which was considered a crucial turning point. Not coincidentally, this corresponds to the year when the State Council issued its National Environmental Emergency Plan, and following the examination of major incidents, special actions were taken to strengthen the control of incidents and emergency responses. The results from Getis-Ord General G statistical analysis show that the spatial agglomeration phenomenon was statistically significant after 1999 and that the level of spatial agglomeration was rising, while the Getis-Ord Gi* statistical analysis reveals that environmental pollution incidents were mainly agglomerated in the Pan Yangtze River Delta and Pan Pearl River Delta regions. Accordingly, the spatial-temporal hotspot pattern based on the IAPI values at the provincial scale could be categorized into: stable hotspots, unstable hotspots, and cold-spot areas. The stable hotspots category was further divided into three subtypes: industrial distribution type, industrial transfer type, and extensive economic growth type. Finally, the corresponding measures for sustainable management were proposed: stable hotspots were classified as essential regions requiring the immediate prevention and control of environmental pollution incidents; unstable hotspots were characterized by their need for ongoing and continual prevention measures, and cold-spots were those areas that

  17. A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads.

    Directory of Open Access Journals (Sweden)

    Junqing Tang

    Full Text Available Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied "R4" resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR, but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and

  18. Malaria infection has spatial, temporal, and spatiotemporal heterogeneity in unstable malaria transmission areas in northwest Ethiopia.

    Directory of Open Access Journals (Sweden)

    Kassahun Alemu

    Full Text Available BACKGROUND: Malaria elimination requires successful nationwide control efforts. Detecting the spatiotemporal distribution and mapping high-risk areas are useful to effectively target pockets of malaria endemic regions for interventions. OBJECTIVE: The aim of the study was to identify patterns of malaria distribution by space and time in unstable malaria transmission areas in northwest Ethiopia. METHODS: Data were retrieved from the monthly reports stored in the district malaria offices for the period between 2003 and 2012. Eighteen districts in the highland and fringe malaria areas were included and geo-coded for the purpose of this study. The spatial data were created in ArcGIS10 for each district. The Poisson model was used by applying Kulldorff methods using the SaTScan™ software to analyze the purely temporal, spatial and space-time clusters of malaria at a district levels. RESULTS: The study revealed that malaria case distribution has spatial, temporal, and spatiotemporal heterogeneity in unstable transmission areas. Most likely spatial malaria clusters were detected at Dera, Fogera, Farta, Libokemkem and Misrak Este districts (LLR =197764.1, p<0.001. Significant spatiotemporal malaria clusters were detected at Dera, Fogera, Farta, Libokemkem and Misrak Este districts (LLR=197764.1, p<0.001 between 2003/1/1 and 2012/12/31. A temporal scan statistics identified two high risk periods from 2009/1/1 to 2010/12/31 (LLR=72490.5, p<0.001 and from 2003/1/1 to 2005/12/31 (LLR=26988.7, p<0.001. CONCLUSION: In unstable malaria transmission areas, detecting and considering the spatiotemporal heterogeneity would be useful to strengthen malaria control efforts and ultimately achieve elimination.

  19. Spatial-temporal distribution of phytoplankton pigments in relation to nutrient status in Jiaozhou Bay, China

    Science.gov (United States)

    Yao, Peng; Yu, Zhigang; Deng, Chunmei; Liu, Shuxia; Zhen, Yu

    2010-10-01

    We conducted studies of phytoplankton and hydrological variables in a semi-enclosed bay in northern China to understand the spatial-temporal variability and relationship between these variables. Samples were collected during seven cruises in Jiaozhou Bay from November 2003 to October 2004, and were analyzed for temperature, nutrients and phytoplankton pigments. Pigments from eight possible phytoplankton classes (Diatoms, Dinoflagellates, Chlorophyceae, Prasinophyceae, Chrysophyceae, Haptophyceae, Cryptophyceae and Caynophyceae) were detected in surface water by high performance liquid chromatography (HPLC). Phytoplankton pigment and nutrient concentrations in Jiaozhou Bay were spatially and temporally variable, and most of them were highest in the northern and eastern parts of the sampling regions in spring (May) and summer (August), close to areas of shellfish culturing, river estuaries, dense population and high industrialization, reflecting human activities. Chlorophyll a was recorded in all samples, with an annual mean concentration of 1.892 μg L -1, and fucoxanthin was the most abundant accessory pigment, with a mean concentration of 0.791 μg L -1. The highest concentrations of chlorophyll a (15.299 μg L -1) and fucoxanthin (9.417 μg L -1) were observed in May 2004 at the station close to the Qingdao Xiaogang Ferry, indicating a spring bloom of Diatoms in this area. Although chlorophyll a and other biomarker pigments showed significant correlations, none of them showed strong correlations with temperature and nutrients, suggesting an apparent de-coupling between the pigments and these hydrological variables. The nutrient composition and phytoplankton community composition of Jiaozhou Bay have changed significantly in the past several decades, reflecting the increasing nutrient concentrations and decline of phytoplankton cell abundance. The unchanged total chlorophyll a levels indicated that smaller species have filled the niche vacated by the larger

  20. Exploring spatial-temporal dynamics of fire regime features in mainland Spain

    Science.gov (United States)

    Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

    2017-10-01

    This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

  1. Gene expression and 18FDG uptake in atherosclerotic carotid plaques

    DEFF Research Database (Denmark)

    Pedersen, Sune Folke; Graebe, Martin; Fisker Hag, Anne Mette

    2010-01-01

    ) and an additional ipsilateral internal carotid artery stenosis of greater than 60% were recruited. FDG uptake in the carotids was determined by PET/computed tomography and expressed as mean and maximal standardized uptake values (SUVmean and SUVmax). The atherosclerotic plaques were subsequently recovered...... by carotid endarterectomy. The gene expression of markers of vulnerability - CD68, IL-18, matrix metalloproteinase 9, cathepsin K, GLUT-1, and hexokinase type II (HK2) - were measured in plaques by quantitative PCR. RESULTS: In a multivariate linear regression model, GLUT-1, CD68, cathepsin K, and HK2 gene...... expression remained in the final model as predictive variables of FDG accumulation calculated as SUVmean (R=0.26, PK, and HK2 gene expression as independent predictive variables of FDG accumulation calculated...

  2. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2005-01-01

    In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

  3. Time-Delay Effects on Constitutive Gene Expression*

    International Nuclear Information System (INIS)

    Feng Yan-Ling; Wang Dan; Tang Xu-Lei; Dong Jian-Min

    2017-01-01

    The dynamics of constitutive gene expression with delayed mRNA degradation is investigated, where the intrinsic noise caused by the small number of reactant molecules is introduced. It is found that the oscillatory behavior claimed in previous investigations does not appear in the approximation of small time delay, and the steady state distribution still follows the Poisson law. Furthermore, we introduce the extrinsic noise induced by surrounding environment to explore the effects of this noise and time delay on the Fano factor. Based on a delay Langevin equation and the corresponding Fokker–Planck equation, the distribution of mRNA copy-number is achieved analytically. The time delay and extrinsic noise play similar roles in the gene expression system, that is, they are able to result in the deviation of the Fano factor from 1 evidently. The measured Fano factor for constitutive gene expression is slightly larger than 1, which is perhaps attributed to the time-delay effect. (paper)

  4. Interdependence of cell growth and gene expression: origins and consequences.

    Science.gov (United States)

    Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M; Zhang, Zhongge; Hwa, Terence

    2010-11-19

    In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.

  5. Codon usage and amino acid usage influence genes expression level.

    Science.gov (United States)

    Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

    2018-02-01

    Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

  6. Finding gene regulatory network candidates using the gene expression knowledge base.

    Science.gov (United States)

    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  7. Geometry of the Gene Expression Space of Individual Cells.

    Directory of Open Access Journals (Sweden)

    Yael Korem

    2015-07-01

    Full Text Available There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a

  8. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    Energy Technology Data Exchange (ETDEWEB)

    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  9. Research on the Spatial-Temporal Distribution Pattern of the Network Attention of Fog and Haze in China

    Science.gov (United States)

    Weng, Lingyan; Han, Xugao

    2018-01-01

    Understanding the spatial-temporal distribution pattern of fog and haze is the base to deal with them by adjusting measures to local conditions. Taking 31 provinces in China mainland as the research areas, this paper collected data from Baidu index on the network attention of fog and haze in relevant areas from 2011 to 2016, and conducted an analysis of their spatial-temporal distribution pattern by using autocorrelation analysis. The results show that the network attention of fog and haze has an overall spatial distribution pattern of “higher in the eastern and central, lower in the western China”. There are regional differences in different provinces in terms of network attention. Network attention of fog and haze indicates an obvious geographical agglomeration phenomenon, which is a gradual enlargement of the agglomeration area of higher value with a slight shrinking of those lower value agglomeration areas.

  10. The Role of Nuclear Bodies in Gene Expression and Disease

    Science.gov (United States)

    Morimoto, Marie; Boerkoel, Cornelius F.

    2013-01-01

    This review summarizes the current understanding of the role of nuclear bodies in regulating gene expression. The compartmentalization of cellular processes, such as ribosome biogenesis, RNA processing, cellular response to stress, transcription, modification and assembly of spliceosomal snRNPs, histone gene synthesis and nuclear RNA retention, has significant implications for gene regulation. These functional nuclear domains include the nucleolus, nuclear speckle, nuclear stress body, transcription factory, Cajal body, Gemini of Cajal body, histone locus body and paraspeckle. We herein review the roles of nuclear bodies in regulating gene expression and their relation to human health and disease. PMID:24040563

  11. Spatial-Temporal Variations of Embodied Carbon Emission in Global Trade Flows: 41 Economies and 35 Sectors

    OpenAIRE

    Jing Tian; Hua Liao; Ce Wang

    2014-01-01

    The spatial-temporal variations of embodied carbon emissions in international trade at global scope are still unclear. This paper studies the variations of outflows and inflows of embodied carbon emissions at 35-disaggregated sectors level of 41 countries and regions, and an integrated world input-output model is employed. It also examines what would happen if there were not international trade flows in China, USA and Finland, the representatives of three different levels of the global balanc...

  12. Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN Framework

    Directory of Open Access Journals (Sweden)

    Tzai-Hung Wen

    2013-11-01

    Full Text Available Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

  13. Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

    Science.gov (United States)

    Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

    2013-11-27

    Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

  14. Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

    Science.gov (United States)

    Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

    2013-01-01

    Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

  15. Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

    Science.gov (United States)

    Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

    2013-12-01

    The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

  16. Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

    Directory of Open Access Journals (Sweden)

    Gao Shouguo

    2011-08-01

    Full Text Available Abstract Background Bayesian Network (BN is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable. Results We introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information. Conclusion our new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.

  17. Experimental and Modeling Approaches for Understanding the Effect of Gene Expression Noise in Biological Development

    Directory of Open Access Journals (Sweden)

    David M. Holloway

    2018-04-01

    Full Text Available Biological development involves numerous chemical and physical processes which must act in concert to reliably produce a cell, a tissue, or a body. To be successful, the developing organism must be robust to variability at many levels, such as the environment (e.g., temperature, moisture, upstream information (such as long-range positional information gradients, or intrinsic noise due to the stochastic nature of low concentration chemical kinetics. The latter is especially relevant to the regulation of gene expression in cell differentiation. The temporal stochasticity of gene expression has been studied in single celled organisms for nearly two decades, but only recently have techniques become available to gather temporally-resolved data across spatially-distributed gene expression patterns in developing multicellular organisms. These demonstrate temporal noisy “bursting” in the number of gene transcripts per cell, raising the question of how the transcript number defining a particular cell type is produced, such that one cell type can reliably be distinguished from a neighboring cell of different type along a tissue boundary. Stochastic spatio-temporal modeling of tissue-wide expression patterns can identify signatures for specific types of gene regulation, which can be used to extract regulatory mechanism information from experimental time series. This Perspective focuses on using this type of approach to study gene expression noise during the anterior-posterior segmentation of the fruit fly embryo. Advances in experimental and theoretical techniques will lead to an increasing quantification of expression noise that can be used to understand how regulatory mechanisms contribute to embryonic robustness across a range of developmental processes.

  18. Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

    Directory of Open Access Journals (Sweden)

    Benjamin Mayne

    2016-10-01

    Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

  19. Biclustering methods: biological relevance and application in gene expression analysis.

    Directory of Open Access Journals (Sweden)

    Ali Oghabian

    Full Text Available DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering methods where genes (or respectively samples are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes. An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1 we examine how well the considered (biclustering methods differentiate various sample types; (2 we evaluate how well the groups of genes discovered by the (biclustering methods are annotated with similar Gene Ontology categories; (3 we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4 we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

  20. Combining gene expression data from different generations of oligonucleotide arrays

    Directory of Open Access Journals (Sweden)

    Kong Sek

    2004-10-01

    Full Text Available Abstract Background One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. Results We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. Conclusions Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different

  1. Denitrification gene expression in clay-soil bacterial community

    Science.gov (United States)

    Pastorelli, R.; Landi, S.

    2009-04-01

    Our contribution in the Italian research project SOILSINK was focused on microbial denitrification gene expression in Mediterranean agricultural soils. In ecosystems with high inputs of nitrogen, such as agricultural soils, denitrification causes a net loss of nitrogen since nitrate is reduced to gaseous forms, which are released into the atmosphere. Moreover, incomplete denitrification can lead to emission of nitrous oxide, a potent greenhouse gas which contributes to global warming and destruction of ozone layer. A critical role in denitrification is played by microorganisms and the ability to denitrify is widespread among a variety of phylogenetically unrelated organisms. Data reported here are referred to wheat cultivation in a clay-rich soil under different environmental impact management (Agugliano, AN, Italy). We analysed the RNA directly extracted from soil to provide information on in situ activities of specific populations. The expression of genes coding for two nitrate reductases (narG and napA), two nitrite reductases (nirS and nirK), two nitric oxide reductases (cnorB and qnorB) and nitrous oxide reductase (nosZ) was analyzed by reverse transcription (RT)-nested PCR. Only napA, nirS, nirK, qnorB and nosZ were detected and fragments sequenced showed high similarity with the corresponding gene sequences deposited in GenBank database. These results suggest the suitability of the method for the qualitative detection of denitrifying bacteria in environmental samples and they offered us the possibility to perform the denaturing gradient gel electrophoresis (DGGE) analyzes for denitrification genes.. Earlier conclusions showed nirK gene is more widely distributed in soil environment than nirS gene. The results concerning the nosZ expression indicated that microbial activity was clearly present only in no-tilled and no-fertilized soils.

  2. a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

    Science.gov (United States)

    Huang, W.; Li, S.; Xu, S.

    2016-06-01

    How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the

  3. Spatial-temporal detection of risk factors for bacillary dysentery in Beijing, Tianjin and Hebei, China

    Directory of Open Access Journals (Sweden)

    Chengdong Xu

    2017-09-01

    Full Text Available Abstract Background Bacillary dysentery is the third leading notifiable disease and remains a major public health concern in China. The Beijing–Tianjin–Hebei urban region is the biggest urban agglomeration in northern China, and it is one of the areas in the country that is most heavily infected with bacillary dysentery. The objective of the study was to analyze the spatial-temporal pattern and to determine any contributory risk factors on the bacillary dysentery. Methods Bacillary dysentery case data from 1 January 2012 to 31 December 2012 in Beijing–Tianjin– Hebei were employed. GeoDetector method was used to determine the impact of potential risk factors, and to identify regions and seasons at high risk of the disease. Results There were 36,472 cases of bacillary dysentery in 2012 in the study region. The incidence of bacillary dysentery varies widely amongst different age groups; the higher incidence of bacillary dysentery mainly occurs in the population under the age of five. Bacillary dysentery presents apparent seasonal variance, with the highest incidence occurring from June to September. In terms of the potential meteorological risk factors, mean temperature, relative humidity, precipitation, mean wind speed and sunshine hours explain the time variant of bacillary dysentery at 83%, 31%, 25%, 17% and 13%, respectively. The interactive effect between temperature and humidity has an explanatory power of 87%, indicating that a hot and humid environment is more likely to lead to the occurrence of bacillary dysentery. Socio-economic factors affect the spatial distribution of bacillary dysentery. The top four factors are age group, per capita GDP, population density and rural population proportion, and their determinant powers are 61%, 27%, 25% and 21%, respectively. The interactive effect between age group and the other factors accounts for more than 60% of bacillary dysentery transmission. Conclusions Bacillary dysentery poses a

  4. A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Huang

    2016-06-01

    Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

  5. Digital gene-expression of alfalfa saponin extract on laying hens

    Directory of Open Access Journals (Sweden)

    Wenna Fan

    2015-03-01

    Full Text Available Cardiovascular disease is a major cause of death worldwide, so people are advised to limit their intake of dietary cholesterol [1]. Egg consumption has been seriously reduced because of the high levels of cholesterol [2]. The objective of this study was to evaluate the cholesterol metabolism effects of alfalfa saponin extract (ASE in liver and ovary tissues using digital gene-expression (DGE profiling analysis. The liver and ovary tissues were isolated from laying hens fed with ASE for RNA sequencing. Here, we provide detailed experimental methods and analysis pipeline in our study to identify digital gene expression of alfalfa saponin extract on laying hens and analysis pipeline published by Singh and colleagues in the PLOS ONE [3]. The data generated in our work provide meaningful information for understanding the molecular mechanisms underlying the cholesterol-lowering effects of ASE.

  6. Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

    Science.gov (United States)

    Ma, W; Zhang, T-F; Lu, P; Lu, S H

    2014-01-01

    Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

  7. Prioritizing orphan proteins for further study using phylogenomics and gene expression profiles in Streptomyces coelicolor

    Directory of Open Access Journals (Sweden)

    Takano Eriko

    2011-09-01

    Full Text Available Abstract Background Streptomyces coelicolor, a model organism of antibiotic producing bacteria, has one of the largest genomes of the bacterial kingdom, including 7825 predicted protein coding genes. A large number of these genes, nearly 34%, are functionally orphan (hypothetical proteins with unknown function. However, in gene expression time course data, many of these functionally orphan genes show interesting expression patterns. Results In this paper, we analyzed all functionally orphan genes of Streptomyces coelicolor and identified a list of "high priority" orphans by combining gene expression analysis and additional phylogenetic information (i.e. the level of evolutionary conservation of each protein. Conclusions The prioritized orphan genes are promising candidates to be examined experimentally in the lab for further characterization of their function.

  8. NORMAL NASAL GENE EXPRESSION LEVELS USING CDNA ARRAY TECHNOLOGY

    Science.gov (United States)

    Normal Nasal Gene Expression Levels Using cDNA Array Technology. The nasal epithelium is a target site for chemically-induced toxicity and carcinogenicity. To detect and analyze genetic events which contribute to nasal tumor development, we first defined the gene expressi...

  9. Songs about Cancer, Gene Expression, and the Biochemistry of Photosynthesis

    Science.gov (United States)

    Heineman, Richard H.

    2018-01-01

    These three biology songs can be used for educational purposes to teach about biochemical concepts. They touch on three different topics: (1) cancer progression and germ cells, (2) gene expression, promoters, and repressors, and (3) electronegativity and the biochemical basis of photosynthesis.

  10. Gene expression profiles in adenosine-treated human mast cells

    African Journals Online (AJOL)

    ajl yemi

    2011-10-26

    Oct 26, 2011 ... assignment (Ewing and Green, 1998a; Ewing et al., 1998b). The trace files were trimmed with trim-alt 0.05 (P-score>20). In addition, vector trimming was conducted with cross-match software. Each gene expression pattern was analyzed by clustering. (30 bp or more 94% homology) and assembly.

  11. The identification of functional motifs in temporal gene expression analysis

    Directory of Open Access Journals (Sweden)

    Michael G. Surette

    2005-01-01

    Full Text Available The identification of transcription factor binding sites is essential to the understanding of the regulation of gene expression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in gene expression, we propose a strategy to adopt false discovery rate (FDR and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal gene expression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis gene expression data is available from the first author upon request.

  12. Quick and sensitive determination of gene expression of fatty acid ...

    African Journals Online (AJOL)

    User

    2011-05-16

    May 16, 2011 ... from fatty acid synthase (FAS) with a different glucose level in ... By using the following formula, this study was able to quantify the mRNA expression of ... hypertension, heart disease and diabetes. ... regulation of gene expression has emerged in recent ... stages of adipocyte meta-bolism are relatively well.

  13. Isolation and characterization of LHY homolog gene expressed in ...

    African Journals Online (AJOL)

    STORAGESEVER

    2008-05-02

    May 2, 2008 ... responsible in negative feedback loop reaction of central oscillator in plant circadian clock system. The level of gene expression was found to be high four hours after dawn in flowering shoots and flower. This paper reported the isolation and characterization of the gene. Key words: LHY gene, circadian ...

  14. CHANGES IN NEUROTRANSMITTER GENE EXPRESSION IN THE AGING RETINA.

    Science.gov (United States)

    To understand mechanisms of neurotoxicity in susceptible populations, we examined age-related changes in constitutive gene expression in the retinas of young (4mos), middle-aged (11 mos) and aged (23 mos) male Long Evans rats. Derived from a pouch of the forebrain during develop...

  15. Screening for interaction effects in gene expression data.

    Directory of Open Access Journals (Sweden)

    Peter J Castaldi

    Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

  16. The evolution of gene expression QTL in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    James Ronald

    2007-08-01

    Full Text Available Understanding the evolutionary forces that influence patterns of gene expression variation will provide insights into the mechanisms of evolutionary change and the molecular basis of phenotypic diversity. To date, studies of gene expression evolution have primarily been made by analyzing how gene expression levels vary within and between species. However, the fundamental unit of heritable variation in transcript abundance is the underlying regulatory allele, and as a result it is necessary to understand gene expression evolution at the level of DNA sequence variation. Here we describe the evolutionary forces shaping patterns of genetic variation for 1206 cis-regulatory QTL identified in a cross between two divergent strains of Saccharomyces cerevisiae. We demonstrate that purifying selection against mildly deleterious alleles is the dominant force governing cis-regulatory evolution in S. cerevisiae and estimate the strength of selection. We also find that essential genes and genes with larger codon bias are subject to slightly stronger cis-regulatory constraint and that positive selection has played a role in the evolution of major trans-acting QTL.

  17. Gene expression profiles in adenosine-treated human mast cells ...

    African Journals Online (AJOL)

    Gene expression profiles in adenosine-treated human mast cells. ... SW Kang, JE Jeong, CH Kim, SH Choi, SH Chae, SA Jun, HJ Cha, JH Kim, YM Lee, YS ... beta 4, ring finger protein, high-mobility group, calmodulin 2, RAN binding protein, ...

  18. Genetic effects on gene expression across human tissues

    NARCIS (Netherlands)

    Battle, Alexis; Brown, Christopher D.; Engelhardt, Barbara E.; Montgomery, Stephen B.; Aguet, François; Ardlie, Kristin G.; Cummings, Beryl B.; Gelfand, Ellen T.; Getz, Gad; Hadley, Kane; Handsaker, Robert E.; Huang, Katherine H.; Kashin, Seva; Karczewski, Konrad J.; Lek, Monkol; Li, Xiao; MacArthur, Daniel G.; Nedzel, Jared L.; Nguyen, Duyen T.; Noble, Michael S.; Segrè, Ayellet V.; Trowbridge, Casandra A.; Tukiainen, Taru; Abell, Nathan S.; Balliu, Brunilda; Barshir, Ruth; Basha, Omer; Bogu, Gireesh K.; Brown, Andrew; Castel, Stephane E.; Chen, Lin S.; Chiang, Colby; Conrad, Donald F.; Cox, Nancy J.; Damani, Farhan N.; Davis, Joe R.; Delaneau, Olivier; Dermitzakis, Emmanouil T.; Eskin, Eleazar; Ferreira, Pedro G.; Frésard, Laure; Gamazon, Eric R.; Garrido-Martín, Diego; Gewirtz, Ariel D. H.; Gliner, Genna; Gloudemans, Michael J.; Guigo, Roderic; Hall, Ira M.; Han, Buhm; He, Yuan

    2017-01-01

    Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression

  19. Tetracycline-inducible gene expression system in Leishmania mexicana

    Czech Academy of Sciences Publication Activity Database

    Kraeva, N.; Ishemgulova, A.; Lukeš, Julius; Yurchenko, Vyacheslav

    2014-01-01

    Roč. 198, č. 1 (2014), s. 11-13 ISSN 0166-6851 R&D Projects: GA MŠk(CZ) EE2.3.30.0032 Institutional support: RVO:60077344 Keywords : Leishmania mexicana * Gene expression * Tet-inducible system Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.787, year: 2014

  20. Gene expression in the tanoak-Phytophthora ramorum interaction

    Science.gov (United States)

    Katherine J. Hayden; Matteo Garbelotto; Hardeep Fai; Brian Knaus; Richard Cronn; Jessica W. Wright

    2012-01-01

    Disease processes are dynamic, involving a suite of gene expression changes in both the host and the pathogen, all within a single tissue. As such, they lend themselves well to transcriptomic analysis. Here we focus on a generalist invasive pathogen (Phytophthora ramorum) and its most susceptible California Floristic Province native host, tanoak (...

  1. Vascular Gene Expression in Nonneoplastic and Malignant Brain

    Science.gov (United States)

    Madden, Stephen L.; Cook, Brian P.; Nacht, Mariana; Weber, William D.; Callahan, Michelle R.; Jiang, Yide; Dufault, Michael R.; Zhang, Xiaoming; Zhang, Wen; Walter-Yohrling, Jennifer; Rouleau, Cecile; Akmaev, Viatcheslav R.; Wang, Clarence J.; Cao, Xiaohong; St. Martin, Thia B.; Roberts, Bruce L.; Teicher, Beverly A.; Klinger, Katherine W.; Stan, Radu-Virgil; Lucey, Brenden; Carson-Walter, Eleanor B.; Laterra, John; Walter, Kevin A.

    2004-01-01

    Malignant gliomas are uniformly lethal tumors whose morbidity is mediated in large part by the angiogenic response of the brain to the invading tumor. This profound angiogenic response leads to aggressive tumor invasion and destruction of surrounding brain tissue as well as blood-brain barrier breakdown and life-threatening cerebral edema. To investigate the molecular mechanisms governing the proliferation of abnormal microvasculature in malignant brain tumor patients, we have undertaken a cell-specific transcriptome analysis from surgically harvested nonneoplastic and tumor-associated endothelial cells. SAGE-derived endothelial cell gene expression patterns from glioma and nonneoplastic brain tissue reveal distinct gene expression patterns and consistent up-regulation of certain glioma endothelial marker genes across patient samples. We define the G-protein-coupled receptor RDC1 as a tumor endothelial marker whose expression is distinctly induced in tumor endothelial cells of both brain and peripheral vasculature. Further, we demonstrate that the glioma-induced gene, PV1, shows expression both restricted to endothelial cells and coincident with endothelial cell tube formation. As PV1 provides a framework for endothelial cell caveolar diaphragms, this protein may serve to enhance glioma-induced disruption of the blood-brain barrier and transendothelial exchange. Additional characterization of this extensive brain endothelial cell gene expression database will provide unique molecular insights into vascular gene expression. PMID:15277233

  2. Flies selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete; Sørensen, Peter; Loeschcke, Volker

    2011-01-01

      We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the gene expression profile in young, middle-aged, and old male flies, finding that 530 genes were...

  3. Evaluation of suitable reference genes for gene expression studies ...

    Indian Academy of Sciences (India)

    2011-12-14

    Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring gene expression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

  4. The gene expressions of DNA methylation/demethylation enzymes ...

    African Journals Online (AJOL)

    user

    2011-01-31

    Jan 31, 2011 ... A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated gene expressions of DNA methyltransferases.

  5. Sugar signalling and gene expression in relation to carbohydrate ...

    Indian Academy of Sciences (India)

    Sucrose is required for plant growth and development. The sugar status of plant cells is sensed by sensor proteins. The signal generated by signal transduction cascades, which could involve mitogen-activated protein kinases, protein phosphatases, Ca2+ and calmodulins, results in appropriate gene expression. A variety of ...

  6. Genome polymorphism markers and stress genes expression for ...

    African Journals Online (AJOL)

    SAM

    2014-06-11

    Jun 11, 2014 ... RNA extraction and purification for SOD and PAL gene expression. Fresh leaf tissues (100 mg), from ... Data analysis. Gelquant program for quantification of protein, DNA and RNA gel. (version 1.8.2) was used for .... by reprogramming the expression of endogenous genes. Higher level of these antioxidant ...

  7. Gene expression profiling of chicken intestinal host responses

    NARCIS (Netherlands)

    Hemert, van S.

    2007-01-01

    Chicken lines differ in genetic disease susceptibility. The scope of the research described in this thesis was to identify genes involved in genetic disease resistance in the chicken intestine. Therefore gene expression in the jejunum was investigated using a microarray approach. An intestine

  8. Gene expression and adaptive noncoding changes during human evolution.

    Science.gov (United States)

    Babbitt, Courtney C; Haygood, Ralph; Nielsen, William J; Wray, Gregory A

    2017-06-05

    Despite evidence for adaptive changes in both gene expression and non-protein-coding, putatively regulatory regions of the genome during human evolution, the relationship between gene expression and adaptive changes in cis-regulatory regions remains unclear. Here we present new measurements of gene expression in five tissues of humans and chimpanzees, and use them to assess this relationship. We then compare our results with previous studies of adaptive noncoding changes, analyzing correlations at the level of gene ontology groups, in order to gain statistical power to detect correlations. Consistent with previous studies, we find little correlation between gene expression and adaptive noncoding changes at the level of individual genes; however, we do find significant correlations at the level of biological function ontology groups. The types of function include processes regulated by specific transcription factors, responses to genetic or chemical perturbations, and differentiation of cell types within the immune system. Among functional categories co-enriched with both differential expression and noncoding adaptation, prominent themes include cancer, particularly epithelial cancers, and neural development and function.

  9. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata

    2015-01-01

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...

  10. Effects of heat stress on gene expression in eggplant ( Solanum ...

    African Journals Online (AJOL)

    In order to identify differentially expressed genes involved in heat shock response, cDNA amplified fragment length polymorphism (cDNA-AFLP) and quantitative real-time polymerase chain reaction (QPCR) were used to study gene expression of eggplant seedlings subjected to 0, 6 and 12 h at 43°C. A total of 53 of over ...

  11. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

    Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

  12. Gene expression profile data for mouse facial development

    Directory of Open Access Journals (Sweden)

    Sonia M. Leach

    2017-08-01

    Full Text Available This article contains data related to the research articles "Spatial and Temporal Analysis of Gene Expression during Growth and Fusion of the Mouse Facial Prominences" (Feng et al., 2009 [1] and “Systems Biology of facial development: contributions of ectoderm and mesenchyme” (Hooper et al., 2017 In press [2]. Embryonic mammalian craniofacial development is a complex process involving the growth, morphogenesis, and fusion of distinct facial prominences into a functional whole. Aberrant gene regulation during this process can lead to severe craniofacial birth defects, including orofacial clefting. As a means to understand the genes involved in facial development, we had previously dissected the embryonic mouse face into distinct prominences: the mandibular, maxillary or nasal between E10.5 and E12.5. The prominences were then processed intact, or separated into ectoderm and mesenchyme layers, prior analysis of RNA expression using microarrays (Feng et al., 2009, Hooper et al., 2017 in press [1,2]. Here, individual gene expression profiles have been built from these datasets that illustrate the timing of gene expression in whole prominences or in the separated tissue layers. The data profiles are presented as an indexed and clickable list of the genes each linked to a graphical image of that gene׳s expression profile in the ectoderm, mesenchyme, or intact prominence. These data files will enable investigators to obtain a rapid assessment of the relative expression level of any gene on the array with respect to time, tissue, prominence, and expression trajectory.

  13. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

    Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

  14. Using PCR to Target Misconceptions about Gene Expression

    Directory of Open Access Journals (Sweden)

    Leslie K. Wright

    2013-02-01

    Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA and gene expression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression.

  15. Analysis and visualization of gene expression data using ...

    African Journals Online (AJOL)

    Several clustering and biclustering methods have been introduced to analyze the gene expression data by identifying the similar patterns and grouping genes into subsets that share biological significance. However, it is not clear how the different methods compare with each other with respect to the biological relevance of ...

  16. Application of four dyes in gene expression analyses by microarrays

    Directory of Open Access Journals (Sweden)

    van Schooten Frederik J

    2005-07-01

    Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

  17. Comparison of gene expression patterns between porcine cumulus ...

    African Journals Online (AJOL)

    These results suggest that the aberrant of gene expression patterns detected in the oocytes of NOs compared with COCs explains their reduced quality in terms of development and maturation. In conclusion, these differentially expressed mRNAs may be involved in cellular interactions between oocytes and cumulus cells ...

  18. Understanding gene expression in coronary artery disease through ...

    Indian Academy of Sciences (India)

    Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

  19. The gene expressions of DNA methylation/demethylation enzymes ...

    African Journals Online (AJOL)

    A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated gene expressions of DNA methyltransferases (Dnmts), DNA ...

  20. Novel redox nanomedicine improves gene expression of polyion complex vector

    Directory of Open Access Journals (Sweden)

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  1. Gene-expression Classifier in Papillary Thyroid Carcinoma

    DEFF Research Database (Denmark)

    Londero, Stefano Christian; Jespersen, Marie Louise; Krogdahl, Annelise

    2016-01-01

    BACKGROUND: No reliable biomarker for metastatic potential in the risk stratification of papillary thyroid carcinoma exists. We aimed to develop a gene-expression classifier for metastatic potential. MATERIALS AND METHODS: Genome-wide expression analyses were used. Development cohort: freshly...

  2. Gene expression of manganese superoxide dismutase in human glioma cells

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    Novi S. Hardiany

    2010-02-01

    Full Text Available Aim This study analyze the MnSOD gene expression as endogenous antioxidant in human glioma cells compared with leucocyte cells as control.Methods MnSOD gene expression of 20 glioma patients was analyzed by measuring the relative expression of mRNA and enzyme activity of MnSOD in brain and leucocyte cells. The relative expression of mRNA MnSOD was determined by using quantitative Real Time RT-PCR and the enzyme activity of MnSOD using biochemical kit assay (xantine oxidase inhibition. Statistic analysis for mRNA and enzyme activity of MnSOD was performed using Kruskal Wallis test.Results mRNA of MnSOD in glioma cells of 70% sample was 0.015–0.627 lower, 10% was 1.002-1.059 and 20% was 1.409-6.915 higher than in leucocyte cells. Also the specific activity of MnSOD enzyme in glioma cells of 80% sample showed 0,064-0,506 lower and 20% sample was 1.249-2.718 higher than in leucocyte cells.Conclusion MnSOD gene expression in human glioma cells are significantly lower than its expression in leucocytes cells. (Med J Indones 2010; 19:21-5Keywords : MnSOD, glioma, gene expression

  3. The application of DNA microarrays in gene expression analysis

    NARCIS (Netherlands)

    Hal, van N.L.W.; Vorst, O.; Houwelingen, van A.M.M.L.; Kok, E.J.; Peijnenburg, A.A.C.M.; Aharoni, A.; Tunen, van A.J.; Keijer, J.

    2000-01-01

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed.

  4. Understanding gene expression in coronary artery disease through ...

    Indian Academy of Sciences (India)

    Understanding gene expression in coronary artery disease through global profiling, network analysis ... A_33_P3249595 B-cell CLL/lymphoma 11A (zinc finger protein). BCL11A. 2.29 ..... It acts as a cytoplasmic sensor for viral infection and ...

  5. VESPUCCI: exploring patterns of gene expression in grapevine

    Directory of Open Access Journals (Sweden)

    Marco eMoretto

    2016-05-01

    Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  6. Rhythmic diel pattern of gene expression in juvenile maize leaf.

    Directory of Open Access Journals (Sweden)

    Maciej Jończyk

    Full Text Available BACKGROUND: Numerous biochemical and physiological parameters of living organisms follow a circadian rhythm. Although such rhythmic behavior is particularly pronounced in plants, which are strictly dependent on the daily photoperiod, data on the molecular aspects of the diurnal cycle in plants is scarce and mostly concerns the model species Arabidopsis thaliana. Here we studied the leaf transcriptome in seedlings of maize, an important C4 crop only distantly related to A. thaliana, throughout a cycle of 10 h darkness and 14 h light to look for rhythmic patterns of gene expression. RESULTS: Using DNA microarrays comprising ca. 43,000 maize-specific probes we found that ca. 12% of all genes showed clear-cut diel rhythms of expression. Cluster analysis identified 35 groups containing from four to ca. 1,000 genes, each comprising genes of similar expression patterns. Perhaps unexpectedly, the most pronounced and most common (concerning the highest number of genes expression maxima were observed towards and during the dark phase. Using Gene Ontology classification several meaningful functional associations were found among genes showing similar diel expression patterns, including massive induction of expression of genes related to gene expression, translation, protein modification and folding at dusk and night. Additionally, we found a clear-cut tendency among genes belonging to individual clusters to share defined transcription factor-binding sequences. CONCLUSIONS: Co-expressed genes belonging to individual clusters are likely to be regulated by common mechanisms. The nocturnal phase of the diurnal cycle involves gross induction of fundamental biochemical processes and should be studied more thoroughly than was appreciated in most earlier physiological studies. Although some general mechanisms responsible for the diel regulation of gene expression might be shared among plants, details of the diurnal regulation of gene expression seem to differ

  7. Equivalent Gene Expression Profiles between Glatopa™ and Copaxone®.

    Directory of Open Access Journals (Sweden)

    Josephine S D'Alessandro

    Full Text Available Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.

  8. Host genetic variation influences gene expression response to rhinovirus infection.

    Directory of Open Access Journals (Sweden)

    Minal Çalışkan

    2015-04-01

    Full Text Available Rhinovirus (RV is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs, namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5 and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3. The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

  9. Host genetic variation influences gene expression response to rhinovirus infection.

    Science.gov (United States)

    Çalışkan, Minal; Baker, Samuel W; Gilad, Yoav; Ober, Carole

    2015-04-01

    Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

  10. Preconceptional paternal glycidamide exposure affects embryonic gene expression: Single embryo gene expression study following in vitro fertilization

    Czech Academy of Sciences Publication Activity Database

    Brevik, A.; Rusňáková, Vendula; Duale, N.; Slagsvold, H.H.; Olsen, A.-K.; Storeng, R.; Kubista, Mikael; Brunborg, G.; Lindeman, B.

    2011-01-01

    Roč. 32, č. 4 (2011), s. 463-471 ISSN 0890-6238 R&D Projects: GA AV ČR(CZ) IAA500520809 Institutional research plan: CEZ:AV0Z50520701 Keywords : Single-cell gene expression * Glycidamide * Acrylamide Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.226, year: 2011

  11. Gene Expression Profile of Proton Beam Irradiated Breast Cancer Stem Cells

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Myung Hwan; Park, Jeong Chan [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-05-15

    Cancer stem cells (CSCs) possess characteristics associated with normal stem cells. The mechanisms regulating CSC radio-resistance, including to proton beam, remain unclear. They showed that a subset of cells expressing CD44 with weak or no CD24 expression could establish new tumors in xenograft mice. Recently, BCSC-targeting therapies have been evaluated by numerous groups. Strategies include targeting BCSC self-renewal, indirectly targeting the microenvironment, and directly killing BCSCs by chemical agents that induce differentiation, immunotherapy, and oncolytic viruses. However, the mechanisms regulating CSC radio-resistance, particularly proton beam resistance, remain unclear. The identification of CSC-related gene expression patterns would make up offer data for better understanding CSCs properties. In this study we investigated the gene expression profile of BCSCs isolation from MCF-7 cell line. Reducing BCSC resistance to pulsed proton beams is essential to improve therapeutic efficacy and decrease the 5-year recurrence rate. In this respect, the information of the level of gene expression patterns in BCSCs is attractive for understanding molecular mechanisms of radio-resistance of BCSCs.

  12. Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction.

    Science.gov (United States)

    Dukowic-Schulze, Stefanie; Liu, Chang; Chen, Changbin

    2018-01-01

    DNA methylation and histone modifications are epigenetic changes on a DNA molecule that alter the three-dimensional (3D) structure locally as well as globally, impacting chromatin looping and packaging on a larger scale. Epigenetic marks thus inform higher-order chromosome organization and placement in the nucleus. Conventional epigenetic marks are joined by chromatin modifiers like cohesins, condensins and membrane-anchoring complexes to support particularly 3D chromosome organization. The most popular consequences of epigenetic modifications are gene expression changes, but chromatin modifications have implications beyond this, particularly in actively dividing cells and during sexual reproduction. In this opinion paper, we will focus on epigenetic mechanisms and chromatin modifications during meiosis as part of plant sexual reproduction where 3D management of chromosomes and re-organization of chromatin are defining features and prime tasks in reproductive cells, not limited to modulating gene expression. Meiotic chromosome organization, pairing and synapsis of homologous chromosomes as well as distribution of meiotic double-strand breaks and resulting crossovers are presumably highly influenced by epigenetic mechanisms. Special mobile small RNAs have been described in anthers, where these so-called phasiRNAs seem to direct DNA methylation in meiotic cells. Intriguingly, many of the mentioned developmental processes make use of epigenetic changes and small RNAs in a manner other than gene expression changes. Widening our approaches and opening our mind to thinking three-dimensionally regarding epigenetics in plant development holds high promise for new discoveries and could give us a boost for further knowledge.

  13. Biofilm-Associated Gene Expression in Staphylococcus pseudintermedius on a Variety of Implant Materials.

    Science.gov (United States)

    Crawford, Evan C; Singh, Ameet; Gibson, Thomas W G; Scott Weese, J

    2016-05-01

    To evaluate the expression of biofilm-associated genes in Staphylococcus pseudintermedius on multiple clinically relevant surfaces. In vitro experimental study. Two strains of methicillin-resistant S. pseudintermedius isolated from clinical infections representing the most common international isolates. A quantitative polymerase chain reaction (qPCR) assay for expression of genes related to biofilm initial adhesion, formation/maturation, antimicrobial resistance, and intracellular communication was developed and validated. S. pseudintermedius biofilms were grown on 8 clinically relevant surfaces (polymethylmethacrylate, stainless steel, titanium, latex, silicone, polydioxanone, polystyrene, and glass) and samples of logarithmic and stationary growth phases were collected. Gene expression in samples was measured by qPCR. Significant differences in gene expression were identified between surfaces and between bacterial strains for most gene/strain/surface combinations studied. Expression of genes responsible for production of extracellular matrix were increased in biofilms. Expression of genes responsible for initial adhesion and intracellular communication was markedly variable. Antimicrobial resistance gene expression was increased on multiple surfaces, including stainless steel and titanium. A method for evaluation of expression of multiple biofilm-associated genes in S. pseudintermedius was successfully developed and applied to the study of biofilms on multiple surfaces. Variations in expression of these genes have a bearing on understanding the development and treatment of implant-associated biofilm infections and will inform future clinical research. © Copyright 2016 by The American College of Veterinary Surgeons.

  14. Analysis of hepatic gene expression during fatty liver change due to chronic ethanol administration in mice

    International Nuclear Information System (INIS)

    Yin, H.-Q.; Je, Young-Tae; Kim, Mingoo; Kim, Ju-Han; Kong, Gu; Kang, Kyung-Sun; Kim, Hyung-Lae; Yoon, Byung-IL; Lee, Mi-Ock; Lee, Byung-Hoon

    2009-01-01

    Chronic consumption of ethanol can cause cumulative liver damage that can ultimately lead to cirrhosis. To explore the mechanisms of alcoholic steatosis, we investigated the global intrahepatic gene expression profiles of livers from mice administered alcohol. Ethanol was administered by feeding the standard Lieber-DeCarli diet, of which 36% (high dose) and 3.6% (low dose) of the total calories were supplied from ethanol for 1, 2, or 4 weeks. Histopathological evaluation of the liver samples revealed fatty changes and punctate necrosis in the high-dose group and ballooning degeneration in the low-dose group. In total, 292 genes were identified as ethanol responsive, and several of these differed significantly in expression compared to those of control mice (two-way ANOVA; p < 0.05). Specifically, the expression levels of genes involved in hepatic lipid transport and metabolism were examined. An overall net increase in gene expression was observed for genes involved in (i) glucose transport and glycolysis, (ii) fatty acid influx and de novo synthesis, (iii) fatty acid esterification to triglycerides, and (iv) cholesterol transport, de novo cholesterol synthesis, and bile acid synthesis. Collectively, these data provide useful information concerning the global gene expression changes that occur due to alcohol intake and provide important insights into the comprehensive mechanisms of chronic alcoholic steatosis

  15. Pyrosequencing of Haliotis diversicolor transcriptomes: insights into early developmental molluscan gene expression.

    Directory of Open Access Journals (Sweden)

    Zi-Xia Huang

    Full Text Available BACKGROUND: The abalone Haliotis diversicolor is a good model for study of the settlement and metamorphosis, which are widespread marine ecological phenomena. However, information on the global gene backgrounds and gene expression profiles for the early development of abalones is lacking. METHODOLOGY/PRINCIPAL FINDINGS: In this study, eight non-normalized and multiplex barcode-labeled transcriptomes were sequenced using a 454 GS system to cover the early developmental stages of the abalone H. diversicolor. The assembly generated 35,415 unigenes, of which 7,566 were assigned GO terms. A global gene expression profile containing 636 scaffolds/contigs was constructed and was proven reliable using qPCR evaluation. It indicated that there may be existing dramatic phase transitions. Bioprocesses were proposed, including the 'lock system' in mature eggs, the collagen shells of the trochophore larvae and the development of chambered extracellular matrix (ECM structures within the earliest postlarvae. CONCLUSION: This study globally details the first 454 sequencing data for larval stages of H. diversicolor. A basic analysis of the larval transcriptomes and cluster of the gene expression profile indicates that each stage possesses a batch of specific genes that are indispensable during embryonic development, especially during the two-cell, trochophore and early postlarval stages. These data will provide a fundamental resource for future physiological works on abalones, revealing the mechanisms of settlement and metamorphosis at the molecular level.

  16. Life cycle analysis of kidney gene expression in male F344 rats.

    Directory of Open Access Journals (Sweden)

    Joshua C Kwekel

    Full Text Available Age is a predisposing condition for susceptibility to chronic kidney disease and progression as well as acute kidney injury that may arise due to the adverse effects of some drugs. Age-related differences in kidney biology, therefore, are a key concern in understanding drug safety and disease progression. We hypothesize that the underlying suite of genes expressed in the kidney at various life cycle stages will impact susceptibility to adverse drug reactions. Therefore, establishing changes in baseline expression data between these life stages is the first and necessary step in evaluating this hypothesis. Untreated male F344 rats were sacrificed at 2, 5, 6, 8, 15, 21, 78, and 104 weeks of age. Kidneys were collected for histology and gene expression analysis. Agilent whole-genome rat microarrays were used to query global expression profiles. An ANOVA (p1.5 in relative mRNA expression, was used to identify 3,724 unique differentially expressed genes (DEGs. Principal component analyses of these DEGs revealed three major divisions in life-cycle renal gene expression. K-means cluster analysis identified several groups of genes that shared age-specific patterns of expression. Pathway analysis of these gene groups revealed age-specific gene networks and functions related to renal function and aging, including extracellular matrix turnover, immune cell response, and renal tubular injury. Large age-related changes in expression were also demonstrated for the genes that code for qualified renal injury biomarkers KIM-1, Clu, and Tff3. These results suggest specific groups of genes that may underlie age-specific susceptibilities to adverse drug reactions and disease. This analysis of the basal gene expression patterns of renal genes throughout the life cycle of the rat will improve the use of current and future renal biomarkers and inform our assessments of kidney injury and disease.

  17. Gene expression in peripheral immune cells following cardioembolic stroke is sexually dimorphic.

    Directory of Open Access Journals (Sweden)

    Boryana Stamova

    Full Text Available Epidemiological studies suggest that sex has a role in the pathogenesis of cardioembolic stroke. Since stroke is a vascular disease, identifying sexually dimorphic gene expression changes in blood leukocytes can inform on sex-specific risk factors, response and outcome biology. We aimed to examine the sexually dimorphic immune response following cardioembolic stroke by studying the differential gene expression in peripheral white blood cells.Blood samples from patients with cardioembolic stroke were obtained at ≤3 hours (prior to treatment, 5 hours and 24 hours (after treatment after stroke onset (n = 23; 69 samples and compared with vascular risk factor controls without symptomatic vascular diseases (n = 23, 23 samples (ANCOVA, false discovery rate p≤0.05, |fold change| ≥1.2. mRNA levels were measured on whole-genome Affymetrix microarrays. There were more up-regulated than down-regulated genes in both sexes, and females had more differentially expressed genes than males following cardioembolic stroke. Female gene expression was associated with cell death and survival, cell-cell signaling and inflammation. Male gene expression was associated with cellular assembly, organization and compromise. Immune response pathways were over represented at ≤3, 5 and 24 h after stroke in female subjects but only at 24 h in males. Neutrophil-specific genes were differentially expressed at 3, 5 and 24 h in females but only at 5 h and 24 h in males.There are sexually dimorphic immune cell expression profiles following cardioembolic stroke. Future studies are needed to confirm the findings using qRT-PCR in an independent cohort, to determine how they relate to risk and outcome, and to compare to other causes of ischemic stroke.

  18. Gene expression profiling in rat kidney after intratracheal exposure to cadmium-doped nanoparticles

    Science.gov (United States)

    Coccini, Teresa; Roda, Elisa; Fabbri, Marco; Sacco, Maria Grazia; Gribaldo, Laura; Manzo, Luigi

    2012-08-01

    While nephrotoxicity of cadmium is well documented, very limited information exists on renal effects of exposure to cadmium-containing nanomaterials. In this work, "omics" methodologies have been used to assess the action of cadmium-containing silica nanoparticles (Cd-SiNPs) in the kidney of Sprague-Dawley rats exposed intratracheally. Groups of animals received a single dose of Cd-SiNPs (1 mg/rat), CdCl2 (400 μg/rat) or 0.1 ml saline (control). Renal gene expression was evaluated 7 and 30 days post exposure by DNA microarray technology using the Agilent Whole Rat Genome Microarray 4x44K. Gene modulating effects were observed in kidney at both time periods after treatment with Cd-SiNPs. The number of differentially expressed genes being 139 and 153 at the post exposure days 7 and 30, respectively. Renal gene expression changes were also observed in the kidney of CdCl2-treated rats with a total of 253 and 70 probes modulated at 7 and 30 days, respectively. Analysis of renal gene expression profiles at day 7 indicated in both Cd-SiNP and CdCl2 groups downregulation of several cluster genes linked to immune function, oxidative stress, and inflammation processes. Differing from day 7, the majority of cluster gene categories modified by nanoparticles in kidney 30 days after dosing were genes implicated in cell regulation and apoptosis. Modest renal gene expression changes were observed at day 30 in rats treated with CdCl2. These results indicate that kidney may be a susceptible target for subtle long-lasting molecular alterations produced by cadmium nanoparticles locally instilled in the lung.

  19. Gene expression profiling in rat kidney after intratracheal exposure to cadmium-doped nanoparticles

    International Nuclear Information System (INIS)

    Coccini, Teresa; Roda, Elisa; Fabbri, Marco; Sacco, Maria Grazia; Gribaldo, Laura; Manzo, Luigi

    2012-01-01

    While nephrotoxicity of cadmium is well documented, very limited information exists on renal effects of exposure to cadmium-containing nanomaterials. In this work, “omics” methodologies have been used to assess the action of cadmium-containing silica nanoparticles (Cd-SiNPs) in the kidney of Sprague-Dawley rats exposed intratracheally. Groups of animals received a single dose of Cd-SiNPs (1 mg/rat), CdCl 2 (400 μg/rat) or 0.1 ml saline (control). Renal gene expression was evaluated 7 and 30 days post exposure by DNA microarray technology using the Agilent Whole Rat Genome Microarray 4x44K. Gene modulating effects were observed in kidney at both time periods after treatment with Cd-SiNPs. The number of differentially expressed genes being 139 and 153 at the post exposure days 7 and 30, respectively. Renal gene expression changes were also observed in the kidney of CdCl 2 -treated rats with a total of 253 and 70 probes modulated at 7 and 30 days, respectively. Analysis of renal gene expression profiles at day 7 indicated in both Cd-SiNP and CdCl 2 groups downregulation of several cluster genes linked to immune function, oxidative stress, and inflammation processes. Differing from day 7, the majority of cluster gene categories modified by nanoparticles in kidney 30 days after dosing were genes implicated in cell regulation and apoptosis. Modest renal gene expression changes were observed at day 30 in rats treated with CdCl 2 . These results indicate that kidney may be a susceptible target for subtle long-lasting molecular alterations produced by cadmium nanoparticles locally instilled in the lung.

  20. Gene expression profiling of bone marrow mesenchymal stem cells from Osteogenesis Imperfecta patients during osteoblast differentiation.

    Science.gov (United States)

    Kaneto, Carla Martins; Pereira Lima, Patrícia S; Prata, Karen Lima; Dos Santos, Jane Lima; de Pina Neto, João Monteiro; Panepucci, Rodrigo Alexandre; Noushmehr, Houtan; Covas, Dimas Tadeu; de Paula, Francisco José Alburquerque; Silva, Wilson Araújo

    2017-06-01

    Mesenchymal stem cells (MSCs) are precursors present in adult bone marrow that are able to differentiate into osteoblasts, adipocytes and chondroblasts that have gained great importance as a source for cell therapy. Recently, a number of studies involving the analysis of gene expression of undifferentiated MSCs and of MSCs in the differentiation into multiple lineage processes were observed but there is no information concerning the gene expression of MSCs from Osteogenesis Imperfecta (OI) patients. Osteogenesis Imperfecta is characterized as a genetic disorder in which a generalized osteopenia leads to excessive bone fragility and severe bone deformities. The aim of this study was to analyze gene expression profile during osteogenic differentiation from BMMSCs (Bone Marrow Mesenchymal Stem Cells) obtained from patients with Osteogenesis Imperfecta and from control subjects. Bone marrow samples were collected from three normal subjects and five patients with OI. Mononuclear cells were isolated for obtaining mesenchymal cells that had been expanded until osteogenic differentiation was induced. RNA was harvested at seven time points during the osteogenic differentiation period (D0, D+1, D+2, D+7, D+12, D+17 and D+21). Gene expression analysis was performed by the microarray technique and identified several differentially expressed genes. Some important genes for osteoblast differentiation had lower expression in OI patients, suggesting a smaller commitment of these patient's MSCs with the osteogenic lineage. Other genes also had their differential expression confirmed by RT-qPCR. An increase in the expression of genes related to adipocytes was observed, suggesting an increase of adipogenic differentiation at the expense osteogenic differentiation. Copyright © 2017. Published by Elsevier Masson SAS.

  1. ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

    Science.gov (United States)

    Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

    2017-05-01

    Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various

  2. Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations.

    Directory of Open Access Journals (Sweden)

    Benjamin A Logsdon

    Full Text Available Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL, which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1, and genes involved in endocytosis (RCY1, the spindle checkpoint (BUB2, sulfonate catabolism (JLP1, and cell-cell communication (PRM7. Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data.

  3. Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage

    Directory of Open Access Journals (Sweden)

    Heather E. Driscoll

    2017-08-01

    Full Text Available Here we describe microarray expression data (raw and normalized, experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993, chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km2. We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875.

  4. A longitudinal study of gene expression in healthy individuals

    Directory of Open Access Journals (Sweden)

    Tessier Michel

    2009-06-01

    Full Text Available Abstract Background The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years and gender. Methods Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR, as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. Results Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF, 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. Conclusion This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated

  5. Argudas: lessons for argumentation in biology based on a gene expression use case.

    Science.gov (United States)

    McLeod, Kenneth; Ferguson, Gus; Burger, Albert

    2012-01-25

    In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both sides - the statement is true and, the statement is false - then the most powerful argument is used. In this work the computer is asked to debate whether or not a gene is expressed in a particular mouse anatomical structure. The information generated during the debate can be passed to the biological end-user, enabling their own decision-making process. This paper examines the evolution of a system, Argudas, which tests using computational argumentation in an in situ gene hybridisation gene expression use case. Argudas reasons using information extracted from several different online resources that publish gene expression information for the mouse. The development and evaluation of two prototypes is discussed. Throughout a number of issues shall be raised including the appropriateness of computational argumentation in biology and the challenges faced when integrating apparently similar online biological databases. From the work described in this paper it is clear that for argumentation to be effective in the biological domain the argumentation community need to develop further the tools and resources they provide. Additionally, the biological community must tackle the incongruity between overlapping and adjacent resources, thus facilitating the integration and modelling of biological information. Finally, this work highlights both the importance of, and difficulty in creating, a good model of the domain.

  6. Earthquake precursors: spatial-temporal gravity changes before the great earthquakes in the Sichuan-Yunnan area

    Science.gov (United States)

    Zhu, Yi-Qing; Liang, Wei-Feng; Zhang, Song

    2018-01-01

    Using multiple-scale mobile gravity data in the Sichuan-Yunnan area, we systematically analyzed the relationships between spatial-temporal gravity changes and the 2014 Ludian, Yunnan Province Ms6.5 earthquake and the 2014 Kangding Ms6.3, 2013 Lushan Ms7.0, and 2008 Wenchuan Ms8.0 earthquakes in Sichuan Province. Our main results are as follows. (1) Before the occurrence of large earthquakes, gravity anomalies occur in a large area around the epicenters. The directions of gravity change gradient belts usually agree roughly with the directions of the main fault zones of the study area. Such gravity changes might reflect the increase of crustal stress, as well as the significant active tectonic movements and surface deformations along fault zones, during the period of gestation of great earthquakes. (2) Continuous significant changes of the multiple-scale gravity fields, as well as greater gravity changes with larger time scales, can be regarded as medium-range precursors of large earthquakes. The subsequent large earthquakes always occur in the area where the gravity changes greatly. (3) The spatial-temporal gravity changes are very useful in determining the epicenter of coming large earthquakes. The large gravity networks are useful to determine the general areas of coming large earthquakes. However, the local gravity networks with high spatial-temporal resolution are suitable for determining the location of epicenters. Therefore, denser gravity observation networks are necessary for better forecasts of the epicenters of large earthquakes. (4) Using gravity changes from mobile observation data, we made medium-range forecasts of the Kangding, Ludian, Lushan, and Wenchuan earthquakes, with especially successful forecasts of the location of their epicenters. Based on the above discussions, we emphasize that medium-/long-term potential for large earthquakes might exist nowadays in some areas with significant gravity anomalies in the study region. Thus, the monitoring

  7. Cpt1a gene expression in peripheral blood mononuclear cells as an early biomarker of diet-related metabolic alterations

    KAUST Repository

    Diaz-Rua, Ruben

    2016-11-23

    Background: Research on biomarkers that provide early information about the development of future metabolic alterations is an emerging discipline. Gene expression analysis in peripheral blood mononuclear cells (PBMC) is a promising tool to identify subjects at risk of developing diet-related diseases.

  8. Gene expression signatures for colorectal cancer microsatellite status and HNPCC

    DEFF Research Database (Denmark)

    Kruhøffer, M; Jensen, J L; Laiho, P

    2005-01-01

    The majority of microsatellite instable (MSI) colorectal cancers are sporadic, but a subset belongs to the syndrome hereditary non-polyposis colorectal cancer (HNPCC). Microsatellite instability is caused by dysfunction of the mismatch repair (MMR) system that leads to a mutator phenotype, and MSI...... of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated...... is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression...

  9. Gene expression profiles in stages II and III colon cancers

    DEFF Research Database (Denmark)

    Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

    2012-01-01

    PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

  10. Repressor-mediated tissue-specific gene expression in plants

    Science.gov (United States)

    Meagher, Richard B [Athens, GA; Balish, Rebecca S [Oxford, OH; Tehryung, Kim [Athens, GA; McKinney, Elizabeth C [Athens, GA

    2009-02-17

    Plant tissue specific gene expression by way of repressor-operator complexes, has enabled outcomes including, without limitation, male sterility and engineered plants having root-specific gene expression of relevant proteins to clean environmental pollutants from soil and water. A mercury hyperaccumulation strategy requires that mercuric ion reductase coding sequence is strongly expressed. The actin promoter vector, A2pot, engineered to contain bacterial lac operator sequences, directed strong expression in all plant vegetative organs and tissues. In contrast, the expression from the A2pot construct was restricted primarily to root tissues when a modified bacterial repressor (LacIn) was coexpressed from the light-regulated rubisco small subunit promoter in above-ground tissues. Also provided are analogous repressor operator complexes for selective expression in other plant tissues, for example, to produce male sterile plants.

  11. Bayesian median regression for temporal gene expression data

    Science.gov (United States)

    Yu, Keming; Vinciotti, Veronica; Liu, Xiaohui; 't Hoen, Peter A. C.

    2007-09-01

    Most of the existing methods for the identification of biologically interesting genes in a temporal expression profiling dataset do not fully exploit the temporal ordering in the dataset and are based on normality assumptions for the gene expression. In this paper, we introduce a Bayesian median regression model to detect genes whose temporal profile is significantly different across a number of biological conditions. The regression model is defined by a polynomial function where both time and condition effects as well as interactions between the two are included. MCMC-based inference returns the posterior distribution of the polynomial coefficients. From this a simple Bayes factor test is proposed to test for significance. The estimation of the median rather than the mean, and within a Bayesian framework, increases the robustness of the method compared to a Hotelling T2-test previously suggested. This is shown on simulated data and on muscular dystrophy gene expression data.

  12. Dysregulation of RNA Mediated Gene Expression in Motor Neuron Diseases.

    Science.gov (United States)

    Gonçalves, Inês do Carmo G; Rehorst, Wiebke A; Kye, Min Jeong

    2016-01-01

    Recent findings indicate an important role for RNA-mediated gene expression in motor neuron diseases, including ALS (amyotrophic lateral sclerosis) and SMA (spinal muscular atrophy). ALS, also known as Lou Gehrig's disease, is an adult-onset progressive neurodegenerative disorder, whereby SMA or "children's Lou Gehrig's disease" is considered a pediatric neurodevelopmental disorder. Despite the difference in genetic causes, both ALS and SMA share common phenotypes; dysfunction/loss of motor neurons that eventually leads to muscle weakness and atrophy. With advanced techniques in molecular genetics and cell biology, current data suggest that these two distinct motor neuron diseases share more than phenotypes; ALS and SMA have similar cellular pathological mechanisms including mitochondrial dysfunction, oxidative stress and dysregulation in RNA-mediated gene expression. Here, we will discuss the current findings on these two diseases with specific focus on RNA-mediated gene regulation including miRNA expression, pre-mRNA processing and RNA binding proteins.

  13. Regulation of gene expression in Escherichia coli and its bacteriophage

    International Nuclear Information System (INIS)

    Higgins, C.F.

    1986-01-01

    This chapter reviews the study of prokaryotic gene expression beginning with a look at the regulation of the lactose operon and the mechanism of attenuation in the tryptophan operon to the more recent development of recombinant DNA technology. The chapter deals almost entirely with escherichia coli and its bacteriophage. The only experimental technique which the authors explore in some detail is the construction and use of gene and operon fusions which have revolutionized the study of gene expression. Various mechanisms by which E. Coli regulate the cellular levels of individual messenger-RNA species are described. Translational regulation of the cellular levels of messenger-RNA include signals encoded within the messenger-RNA molecule itself and regulatory molecules which interact with the messenger-RNA and alter it translational efficiency

  14. In silico gene expression profiling in Cannabis sativa.

    Science.gov (United States)

    Massimino, Luca

    2017-01-01

    The cannabis plant and its active ingredients (i.e., cannabinoids and terpenoids) have been socially stigmatized for half a century. Luckily, with more than 430,000 published scientific papers and about 600 ongoing and completed clinical trials, nowadays cannabis is employed for the treatment of many different medical conditions. Nevertheless, even if a large amount of high-throughput functional genomic data exists, most researchers feature a strong background in molecular biology but lack advanced bioinformatics skills. In this work, publicly available gene expression datasets have been analyzed giving rise to a total of 40,224 gene expression profiles taken from cannabis plant tissue at different developmental stages. The resource presented here will provide researchers with a starting point for future investigations with Cannabis sativa .

  15. Rethinking cell-cycle-dependent gene expression in Schizosaccharomyces pombe.

    Science.gov (United States)

    Cooper, Stephen

    2017-11-01

    Three studies of gene expression during the division cycle of Schizosaccharomyces pombe led to the proposal that a large number of genes are expressed at particular times during the S. pombe cell cycle. Yet only a small fraction of genes proposed to be expressed in a cell-cycle-dependent manner are reproducible in all three published studies. In addition to reproducibility problems, questions about expression amplitudes, cell-cycle timing of expression, synchronization artifacts, and the problem with methods for synchronizing cells must be considered. These problems and complications prompt the idea that caution should be used before accepting the conclusion that there are a large number of genes expressed in a cell-cycle-dependent manner in S. pombe.

  16. Spatial reconstruction of single-cell gene expression data.

    Science.gov (United States)

    Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

    2015-05-01

    Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

  17. Impact of Solar Radiation on Gene Expression in Bacteria

    Directory of Open Access Journals (Sweden)

    Sabine Matallana-Surget

    2013-07-01

    Full Text Available Microorganisms often regulate their gene expression at the level of transcription and/or translation in response to solar radiation. In this review, we present the use of both transcriptomics and proteomics to advance knowledge in the field of bacterial response to damaging radiation. Those studies pertain to diverse application areas such as fundamental microbiology, water treatment, microbial ecology and astrobiology. Even though it has been demonstrated that mRNA abundance is not always consistent with the protein regulation, we present here an exhaustive review on how bacteria regulate their gene expression at both transcription and translation levels to enable biomarkers identification and comparison of gene regulation from one bacterial species to another.

  18. Mediator and Cohesin Connect Gene Expression and Chromatin Architecture

    Science.gov (United States)

    Kagey, Michael H.; Newman, Jamie J.; Bilodeau, Steve; Zhan, Ye; Orlando, David A.; van Berkum, Nynke L.; Ebmeier, Christopher C.; Goossens, Jesse; Rahl, Peter B.; Levine, Stuart S.; Taatjes, Dylan J.; Dekker, Job; Young, Richard A.

    2010-01-01

    Summary Transcription factors control cell specific gene expression programs through interactions with diverse coactivators and the transcription apparatus. Gene activation may involve DNA loop formation between enhancer-bound transcription factors and the transcription apparatus at the core promoter, but this process is not well understood. We report here that Mediator and Cohesin physically and functionally connect the enhancers and core promoters of active genes in embryonic stem cells. Mediator, a transcriptional coactivator, forms a complex with Cohesin, which can form rings that connect two DNA segments. The Cohesin loading factor Nipbl is associated with Mediator/Cohesin complexes, providing a means to load Cohesin at promoters. DNA looping is observed between the enhancers and promoters occupied by Mediator and Cohesin. Mediator and Cohesin occupy different promoters in different cells, thus generating cell-type specific DNA loops linked to the gene expression program of each cell. PMID:20720539

  19. Pattern Recognition of Gene Expression with Singular Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Hossein Hassani

    2014-07-01

    Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid gene expression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering gene expression measurements for other applications.

  20. Adaptive differences in gene expression in European flounder ( Platichthys flesus )

    DEFF Research Database (Denmark)

    Larsen, Peter Foged; Eg Nielsen, Einar; Williams, T.D.

    2007-01-01

    levels of neutral genetic divergence, a high number of genes were significantly differentially expressed between North Sea and Baltic Sea flounders maintained in a long-term reciprocal transplantation experiment mimicking natural salinities. Several of the differentially regulated genes could be directly...... linked to fitness traits. These findings demonstrate that flounders, despite little neutral genetic divergence between populations, are differently adapted to local environmental conditions and imply that adaptation in gene expression could be common in other marine organisms with similar low levels...

  1. Blood Gene Expression Profiling of Breast Cancer Survivors Experiencing Fibrosis

    International Nuclear Information System (INIS)

    Landmark-Hoyvik, Hege; Dumeaux, Vanessa; Reinertsen, Kristin V.; Edvardsen, Hege; Fossa, Sophie D.; Borresen-Dale, Anne-Lise

    2011-01-01

    Purpose: To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing gene expression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3-7 years after end of radiotherapy treatment. Methods and Materials: Gene expression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3-7 years earlier. Analyses of transcriptional differences in blood gene expression between BC survivors with fibrosis (n = 31) and BC survivors without fibrosis (n = 223) were performed using R version 2.8.0 and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results: Substantial differences in blood gene expression between BC survivors with and without fibrosis were observed, and 87 differentially expressed genes were identified through linear analysis. Transforming growth factor-β1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion: Transforming growth factor-β1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.

  2. GECKO: a complete large-scale gene expression analysis platform

    Directory of Open Access Journals (Sweden)

    Heuer Michael

    2004-12-01

    Full Text Available Abstract Background Gecko (Gene Expression: Computation and Knowledge Organization is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Results Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing ~ 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph, in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (~ 100 users and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. Conclusions The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

  3. Embryo quality predictive models based on cumulus cells gene expression

    Directory of Open Access Journals (Sweden)

    Devjak R

    2016-06-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

  4. Oxygen and tissue culture affect placental gene expression.

    Science.gov (United States)

    Brew, O; Sullivan, M H F

    2017-07-01

    Placental explant culture is an important model for studying placental development and functions. We investigated the differences in placental gene expression in response to tissue culture, atmospheric and physiologic oxygen concentrations. Placental explants were collected from normal term (38-39 weeks of gestation) placentae with no previous uterine contractile activity. Placental transcriptomic expressions were evaluated with GeneChip ® Human Genome U133 Plus 2.0 arrays (Affymetrix). We uncovered sub-sets of genes that regulate response to stress, induction of apoptosis programmed cell death, mis-regulation of cell growth, proliferation, cell morphogenesis, tissue viability, and protection from apoptosis in cultured placental explants. We also identified a sub-set of genes with highly unstable pattern of expression after exposure to tissue culture. Tissue culture irrespective of oxygen concentration induced dichotomous increase in significant gene expression and increased enrichment of significant pathways and transcription factor targets (TFTs) including HIF1A. The effect was exacerbated by culture at atmospheric oxygen concentration, where further up-regulation of TFTs including PPARA, CEBPD, HOXA9 and down-regulated TFTs such as JUND/FOS suggest intrinsic heightened key biological and metabolic mechanisms such as glucose use, lipid biosynthesis, protein metabolism; apoptosis, inflammatory responses; and diminished trophoblast proliferation, differentiation, invasion, regeneration, and viability. These findings demonstrate that gene expression patterns differ between pre-culture and cultured explants, and the gene expression of explants cultured at atmospheric oxygen concentration favours stressed, pro-inflammatory and increased apoptotic transcriptomic response. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  6. Gene Expression and the Diversity of Identified Neurons

    OpenAIRE

    Buck, L.; Stein, R.; Palazzolo, M.; Anderson, D. J.; Axel, R.

    1983-01-01

    Nervous systems consist of diverse populations of neurons that are anatomically and functionally distinct. The diversity of neurons and the precision with which they are interconnected suggest that specific genes or sets of genes are activated in some neurons but not expressed in others. Experimentally, this problem may be considered at two levels. First, what is the total number of genes expressed in the brain, and how are they distributed among the different populations of neurons? Second, ...

  7. Genetics of sputum gene expression in chronic obstructive pulmonary disease.

    Directory of Open Access Journals (Sweden)

    Weiliang Qiu

    Full Text Available Previous expression quantitative trait loci (eQTL studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs. The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5, the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.

  8. Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

    Science.gov (United States)

    Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

    2011-01-01

    Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

  9. Emerging Use of Gene Expression Microarrays in Plant Physiology

    Directory of Open Access Journals (Sweden)

    Stephen P. Difazio

    2006-04-01

    Full Text Available Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  10. Assays for noninvasive imaging of reporter gene expression

    International Nuclear Information System (INIS)

    Gambhir, S.S.; Barrio, J.R.; Herschman, H.R.; Phelps, M.E.

    1999-01-01

    Repeated, noninvasive imaging of reporter gene expression is emerging as a valuable tool for monitoring the expression of genes in animals and humans. Monitoring of organ/cell transplantation in living animals and humans, and the assessment of environmental, behavioral, and pharmacologic modulation of gene expression in transgenic animals should soon be possible. The earliest clinical application is likely to be monitoring human gene therapy in tumors transduced with the herpes simplex virus type 1 thymidine kinase (HSV1-tk) suicide gene. Several candidate assays for imaging reporter gene expression have been studied, utilizing cytosine deaminase (CD), HSV1-tk, and dopamine 2 receptor (D2R) as reporter genes. For the HSV1-tk reporter gene, both uracil nucleoside derivatives (e.g., 5-iodo-2'-fluoro-2'-deoxy-1-β-D-arabinofuranosyl-5-iodouracil [FIAU] labeled with 124 I, 131 I ) and acycloguanosine derivatives {e.g., 8-[ 18 F]fluoro-9-[[2-hydroxy-1-(hydroxymethyl)ethoxy]methyl]guanine (8-[ 18 F]-fluoroganciclovir) ([ 18 F]FGCV), 9-[(3-[ 18 F]fluoro-1-hydroxy-2-propoxy)methyl]guanine ([ 18 F]FHPG)} have been investigated as reporter probes. For the D2R reporter gene, a derivative of spiperone {3-(2'-[ 18 F]-Fluoroethyl)spiperone ([ 18 F]FESP)} has been used with positron emission tomography (PET) imaging. In this review, the principles and specific assays for imaging reporter gene expression are presented and discussed. Specific examples utilizing adenoviral-mediated delivery of a reporter gene as well as tumors expressing reporter genes are discussed

  11. Developmental gene expression profiles of the human pathogen Schistosoma japonicum

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    McManus Donald P

    2009-03-01

    Full Text Available Abstract Background The schistosome blood flukes are complex trematodes and cause a chronic parasitic disease of significant public health importance worldwide, schistosomiasis. Their life cycle is characterised by distinct parasitic and free-living phases involving mammalian and snail hosts and freshwater. Microarray analysis was used to profile developmental gene expression in the Asian species, Schistosoma japonicum. Total RNAs were isolated from the three distinct environmental phases of the lifecycle – aquatic/snail (eggs, miracidia, sporocysts, cercariae, juvenile (lung schistosomula and paired but pre-egg laying adults and adult (paired, mature males and egg-producing females, both examined separately. Advanced analyses including ANOVA, principal component analysis, and hierarchal clustering provided a global synopsis of gene expression relationships among the different developmental stages of the schistosome parasite. Results Gene expression profiles were linked to the major environmental settings through which the developmental stages of the fluke have to adapt during the course of its life cycle. Gene ontologies of the differentially expressed genes revealed a wide range of functions and processes. In addition, stage-specific, differentially expressed genes were identified that were involved in numerous biological pathways and functions including calcium signalling, sphingolipid metabolism and parasite defence. Conclusion The findings provide a comprehensive database of gene expression in an important human pathogen, including transcriptional changes in genes involved in evasion of the host immune response, nutrient acquisition, energy production, calcium signalling, sphingolipid metabolism, egg production and tegumental function during development. This resource should help facilitate the identification and prioritization of new anti-schistosome drug and vaccine targets for the control of schistosomiasis.

  12. Gene expression of circulating tumour cells in breast cancer patients

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    Bölke E

    2009-09-01

    Full Text Available Abstract Background The diagnostic tools to predict the prognosis in patients suffering from breast cancer (BC need further improvements. New technological achievements like the gene profiling of circulating tumour cells (CTC could help identify new prognostic markers in the clinical setting. Furthermore, gene expression patterns of CTC might provide important informations on the mechanisms of tumour cell metastasation. Materials and methods We performed realtime-PCR and multiplex-PCR analyses following immunomagnetic separation of CTC. Peripheral blood (PB samples of 63 patients with breast cancer of various stages were analyzed and compared to a control group of 14 healthy individuals. After reverse-transcription, we performed multiplex PCR using primers for the genes ga733.3, muc-1 and c-erbB2. Mammaglobin1, spdef and c-erbB2 were analyzed applying realtime-PCR. Results ga733.2 overexpression was found in 12.7% of breast cancer cases, muc-1 in 15.9%, mgb1 in 9.1% and spdef in 12.1%. In this study, c-erbB2 did not show any significant correlation to BC, possibly due to a highly ambient expression. Besides single gene analyses, gene profiles were additionally evaluated. Highly significant correlations to BC were found in single gene analyses of ga733.2 and muc-1 and in gene profile analyses of ga733.3*muc-1 and GA7 ga733.3*muc-1*mgb1*spdef. Conclusion Our study reveals that the single genes ga733.3, muc-1 and the gene profiles ga733.3*muc-1 and ga733.3*3muc-1*mgb1*spdef can serve as markers for the detection of CTC in BC. The multigene analyses found highly positive levels in BC patients. Our study indicates that not single gene analyses but subtle patterns of multiple genes lead to rising accuracy and low loss of specificity in detection of breast cancer cases.

  13. Effects of Assisted Reproduction Technology on Placental Imprinted Gene Expression

    Science.gov (United States)

    Katagiri, Yukiko; Aoki, Chizu; Tamaki-Ishihara, Yuko; Fukuda, Yusuke; Kitamura, Mamoru; Matsue, Yoichi; So, Akiko; Morita, Mineto

    2010-01-01

    We used placental tissue to compare the imprinted gene expression of IGF2, H19, KCNQ1OT1, and CDKN1C of singletons conceived via assisted reproduction technology (ART) with that of spontaneously conceived (SC) singletons. Of 989 singletons examined (ART n = 65; SC n = 924), neonatal weight was significantly lower (P < .001) in the ART group than in the SC group, but placental weight showed no significant difference. Gene expression analyzed by real-time PCR was similar for both groups with appropriate-for-date (AFD) birth weight. H19 expression was suppressed in fetal growth retardation (FGR) cases in the ART and SC groups compared with AFD cases (P < .02 and P < .05, resp.). In contrast, CDKN1C expression was suppressed in FGR cases in the ART group (P < .01), while KCNQ1OT1 expression was hyperexpressed in FGR cases in the SC group (P < .05). As imprinted gene expression patterns differed between the ART and SC groups, we speculate that ART modifies epigenetic status even though the possibilities always exist. PMID:20706653

  14. Aging and gene expression in the primate brain.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2005-09-01

    Full Text Available It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

  15. Identification of highly synchronized subnetworks from gene expression data.

    Science.gov (United States)

    Gao, Shouguo; Wang, Xujing

    2013-01-01

    There has been a growing interest in identifying context-specific active protein-protein interaction (PPI) subnetworks through integration of PPI and time course gene expression data. However the interaction dynamics during the biological process under study has not been sufficiently considered previously. Here we propose a topology-phase locking (TopoPL) based scoring metric for identifying active PPI subnetworks from time series expression data. First the temporal coordination in gene expression changes is evaluated through phase locking analysis; The results are subsequently integrated with PPI to define an activity score for each PPI subnetwork, based on individual member expression, as well topological characteristics of the PPI network and of the expression temporal coordination network; Lastly, the subnetworks with the top scores in the whole PPI network are identified through simulated annealing search. Application of TopoPL to simulated data and to the yeast cell cycle data showed that it can more sensitively identify biologically meaningful subnetworks than the method that only utilizes the static PPI topology, or the additive scoring method. Using TopoPL we identified a core subnetwork with 49 genes important to yeast cell cycle. Interestingly, this core contains a protein complex known to be related to arrangement of ribosome subunits that exhibit extremely high gene expression synchronization. Inclusion of interaction dynamics is important to the identification of relevant gene networks.

  16. Divergent and nonuniform gene expression patterns in mouse brain

    Science.gov (United States)

    Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

    2010-01-01

    Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

  17. An incoherent feedforward loop facilitates adaptive tuning of gene expression.

    Science.gov (United States)

    Hong, Jungeui; Brandt, Nathan; Abdul-Rahman, Farah; Yang, Ally; Hughes, Tim; Gresham, David

    2018-04-05

    We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression. © 2018, Hong et al.

  18. A Classification Framework Applied to Cancer Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

  19. Changes in skeletal muscle gene expression following clenbuterol administration

    Directory of Open Access Journals (Sweden)

    McIntyre Lauren M

    2006-12-01

    Full Text Available Abstract Background Beta-adrenergic receptor agonists (BA induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. The Affymetrix platform was utilized to identify gene expression changes in mouse skeletal muscle 24 hours and 10 days after administration of the BA clenbuterol. Results Administration of clenbuterol stimulated anabolic activity, as indicated by decreased blood urea nitrogen (BUN; P P Conclusion Global evaluation of gene expression after administration of clenbuterol identified changes in gene expression and overrepresented functional categories of genes that may regulate BA-induced muscle hypertrophy. Changes in mRNA abundance of multiple genes associated with myogenic differentiation may indicate an important effect of BA on proliferation, differentiation, and/or recruitment of satellite cells into muscle fibers to promote muscle hypertrophy. Increased mRNA abundance of genes involved in the initiation of translation suggests that increased levels of protein synthesis often associated with BA administration may result from a general up-regulation of translational initiators. Additionally, numerous other genes and physiological pathways were identified that will be important targets for further investigations of the hypertrophic effect of BA on skeletal muscle.

  20. A Fisheye Viewer for microarray-based gene expression data.

    Science.gov (United States)

    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  1. A fisheye viewer for microarray-based gene expression data

    Directory of Open Access Journals (Sweden)

    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  2. Aging and Gene Expression in the Primate Brain

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Khaitovich, Philipp; Plotkin, Joshua B.; Paabo, Svante; Eisen, Michael B.

    2005-02-18

    It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

  3. Reproducibility of gene expression across generations of Affymetrix microarrays

    Directory of Open Access Journals (Sweden)

    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

  4. AGEMAP: a gene expression database for aging in mice.

    Directory of Open Access Journals (Sweden)

    Jacob M Zahn

    2007-11-01

    Full Text Available We present the AGEMAP (Atlas of Gene Expression in Mouse Aging Project gene expression database, which is a resource that catalogs changes in gene expression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1 a pattern common to neural tissues, (2 a pattern for vascular tissues, and (3 a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different.

  5. Gene expression in cerebral ischemia: a new approach for neuroprotection.

    Science.gov (United States)

    Millán, Mónica; Arenillas, Juan

    2006-01-01

    Cerebral ischemia is one of the strongest stimuli for gene induction in the brain. Hundreds of genes have been found to be induced by brain ischemia. Many genes are involved in neurodestructive functions such as excitotoxicity, inflammatory response and neuronal apoptosis. However, cerebral ischemia is also a powerful reformatting and reprogramming stimulus for the brain through neuroprotective gene expression. Several genes may participate in both cellular responses. Thus, isolation of candidate genes for neuroprotection strategies and interpretation of expression changes have been proven difficult. Nevertheless, many studies are being carried out to improve the knowledge of the gene activation and protein expression following ischemic stroke, as well as in the development of new therapies that modify biochemical, molecular and genetic changes underlying cerebral ischemia. Owing to the complexity of the process involving numerous critical genes expressed differentially in time, space and concentration, ongoing therapeutic efforts should be based on multiple interventions at different levels. By modification of the acute gene expression induced by ischemia or the apoptotic gene program, gene therapy is a promising treatment but is still in a very experimental phase. Some hurdles will have to be overcome before these therapies can be introduced into human clinical stroke trials. Copyright 2006 S. Karger AG, Basel.

  6. Gene expression in the aging human brain: an overview.

    Science.gov (United States)

    Mohan, Adith; Mather, Karen A; Thalamuthu, Anbupalam; Baune, Bernhard T; Sachdev, Perminder S

    2016-03-01

    The review aims to provide a summary of recent developments in the study of gene expression in the aging human brain. Profiling differentially expressed genes or 'transcripts' in the human brain over the course of normal aging has provided valuable insights into the biological pathways that appear activated or suppressed in late life. Genes mediating neuroinflammation and immune system activation in particular, show significant age-related upregulation creating a state of vulnerability to neurodegenerative and neuropsychiatric disease in the aging brain. Cellular ionic dyshomeostasis and age-related decline in a host of molecular influences on synaptic efficacy may underlie neurocognitive decline in later life. Critically, these investigations have also shed light on the mobilization of protective genetic responses within the aging human brain that help determine health and disease trajectories in older age. There is growing interest in the study of pre and posttranscriptional regulators of gene expression, and the role of noncoding RNAs in particular, as mediators of the phenotypic diversity that characterizes human brain aging. Gene expression studies in healthy brain aging offer an opportunity to unravel the intricately regulated cellular underpinnings of neurocognitive aging as well as disease risk and resiliency in late life. In doing so, new avenues for early intervention in age-related neurodegenerative disease could be investigated with potentially significant implications for the development of disease-modifying therapies.

  7. GOBO: gene expression-based outcome for breast cancer online.

    Directory of Open Access Journals (Sweden)

    Markus Ringnér

    Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

  8. Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.

    Science.gov (United States)

    Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L

    2016-10-10

    Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.

  9. Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

    Directory of Open Access Journals (Sweden)

    Liming Wang

    Full Text Available Dilated cardiomyopathy (DCM is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs and microRNAs (miRNAs of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family. Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1, potential TFs, as well as potential miRNAs, might be involved in DCM.

  10. A Gene Expression Classifier of Node-Positive Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Paul F. Meeh

    2009-10-01

    Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

  11. Gene expression characterizes different nutritional strategies among three mixotrophic protists.

    Science.gov (United States)

    Liu, Zhenfeng; Campbell, Victoria; Heidelberg, Karla B; Caron, David A

    2016-07-01

    Mixotrophic protists, i.e. protists that can carry out both phototrophy and heterotrophy, are a group of organisms with a wide range of nutritional strategies. The ecological and biogeochemical importance of these species has recently been recognized. In this study, we investigated and compared the gene expression of three mixotrophic protists, Prymnesium parvum, Dinobyron sp. and Ochromonas sp. under light and dark conditions in the presence of prey using RNA-Seq. Gene expression of the obligately phototrophic P. parvum and Dinobryon sp. changed significantly between light and dark treatments, while that of primarily heterotrophic Ochromonas sp. was largely unchanged. Gene expression of P. parvum and Dinobryon sp. shared many similarities, especially in the expression patterns of genes related to reproduction. However, key genes involved in central carbon metabolism and phagotrophy had different expression patterns between these two species, suggesting differences in prey consumption and heterotrophic nutrition in the dark. Transcriptomic data also offered clues to other physiological traits of these organisms such as preference of nitrogen sources and photo-oxidative stress. These results provide potential target genes for further exploration of the mechanisms of mixotrophic physiology and demonstrate the potential usefulness of molecular approaches in characterizing the nutritional modes of mixotrophic protists. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. PRAME Gene Expression in Acute Leukemia and Its Clinical Significance

    International Nuclear Information System (INIS)

    Ding, Kai; Wang, Xiao-ming; Fu, Rong; Ruan, Er-bao; Liu, Hui; Shao, Zong-hong

    2012-01-01

    To investigate the expression of the preferentially expressed antigen of melanoma (PRAME) gene in acute leukemia and its clinical significance. The level of expressed PRAME mRNA in bone marrow mononuclear cells from 34 patients with acute leukemia (AL) and in 12 bone marrow samples from healthy volunteers was measured via RT-PCR. Correlation analyses between PRAME gene expression and the clinical characteristics (gender, age, white blood count, immunophenotype of leukemia, percentage of blast cells, and karyotype) of the patients were performed. The PRAME gene was expressed in 38.2% of all 34 patients, in 40.7% of the patients with acute myelogenous leukemia (AML, n=27), and in 28.6% of the patients with acute lymphoblastic leukemia (ALL, n=7), but was not expressed in the healthy volunteers. The difference in the expression levels between AML and ALL patients was statistically significant. The rate of gene expression was 80% in M 3 , 33.3% in M 2 , and 28.6% in M 5 . Gene expression was also found to be correlated with CD15 and CD33 expression and abnormal karyotype, but not with age, gender, white blood count or percentage of blast cells. The PRAME gene is highly expressed in acute leukemia and could be a useful marker to monitor minimal residual disease. This gene is also a candidate target for the immunotherapy of acute leukemia

  13. DNA methylation and gene expression of HIF3A

    DEFF Research Database (Denmark)

    Main, Ailsa Maria; Gillberg, Linn; Jacobsen, Anna Louisa

    2016-01-01

    from 48 families, from whom we had SAT and muscle biopsies. DNA methylation of four CpG sites in the HIF3A promoter was analyzed in the blood and SAT by pyrosequencing, and HIF3A gene expression was analyzed in SAT and muscle by qPCR. An index of whole-body insulin sensitivity was estimated from oral...... individuals, and whether HIF3A gene expression in SAT and skeletal muscle biopsies showed associations with BMI and insulin resistance. Furthermore, we aimed to investigate gender specificity and heritability of these traits. METHODS: We studied 137 first-degree relatives of type 2 diabetes (T2D) patients...... glucose tolerance tests. RESULTS: BMI was associated with HIF3A methylation at one CpG site in the blood, and there was a positive association between the blood and SAT methylation levels at a different CpG site within the individuals. The SAT methylation level did not correlate with HIF3A gene expression...

  14. Smoking-induced gene expression changes in the bronchial airway are reflected in nasal and buccal epithelium

    Directory of Open Access Journals (Sweden)

    Zhang Xiaohui

    2008-05-01

    Full Text Available Abstract Background Cigarette smoking is a leading cause of preventable death and a significant cause of lung cancer and chronic obstructive pulmonary disease. Prior studies have demonstrated that smoking creates a field of molecular injury throughout the airway epithelium exposed to cigarette smoke. We have previously characterized gene expression in the bronchial epithelium of never smokers and identified the gene expression changes that occur in the mainstem bronchus in response to smoking. In this study, we explored relationships in whole-genome gene expression between extrathorcic (buccal and nasal and intrathoracic (bronchial epithelium in healthy current and never smokers. Results Using genes that have been previously defined as being expressed in the bronchial airway of never smokers (the "normal airway transcriptome", we found that bronchial and nasal epithelium from non-smokers were most similar in gene expression when compared to other epithelial and nonepithelial tissues, with several antioxidant, detoxification, and structural genes being highly expressed in both the bronchus and nose. Principle component analysis of previously defined smoking-induced genes from the bronchus suggested that smoking had a similar effect on gene expression in nasal epithelium. Gene set enrichment analysis demonstrated that this set of genes was also highly enriched among the genes most altered by smoking in both nasal and buccal epithelial samples. The expression of several detoxification genes was commonly altered by smoking in all three respiratory epithelial tissues, suggesting a common airway-wide response to tobacco exposure. Conclusion Our findings support a relationship between gene expression in extra- and intrathoracic airway epithelial cells and extend the concept of a smoking-induced field of injury to epithelial cells that line the mouth and nose. This relationship could potentially be utilized to develop a non-invasive biomarker for

  15. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  16. Neonatal maternal deprivation response and developmental changes in gene expression revealed by hypothalamic gene expression profiling in mice.

    Directory of Open Access Journals (Sweden)

    Feng Ding

    Full Text Available Neonatal feeding problems are observed in several genetic diseases including Prader-Willi syndrome (PWS. Later in life, individuals with PWS develop hyperphagia and obesity due to lack of appetite control. We hypothesized that failure to thrive in infancy and later-onset hyperphagia are related and could be due to a defect in the hypothalamus. In this study, we performed gene expression microarray analysis of the hypothalamic response to maternal deprivation in neonatal wild-type and Snord116del mice, a mouse model for PWS in which a cluster of imprinted C/D box snoRNAs is deleted. The neonatal starvation response in both strains was dramatically different from that reported in adult rodents. Genes that are affected by adult starvation showed no expression change in the hypothalamus of 5 day-old pups after 6 hours of maternal deprivation. Unlike in adult rodents, expression levels of Nanos2 and Pdk4 were increased, and those of Pgpep1, Ndp, Brms1l, Mett10d, and Snx1 were decreased after neonatal deprivation. In addition, we compared hypothalamic gene expression profiles at postnatal days 5 and 13 and observed significant developmental changes. Notably, the gene expression profiles of Snord116del deletion mice and wild-type littermates were very similar at all time points and conditions, arguing against a role of Snord116 in feeding regulation in the neonatal period.

  17. Spatial-temporal ultrasound imaging of residual cavitation bubbles around a fluid-tissue interface in histotripsy.

    Science.gov (United States)

    Hu, Hong; Xu, Shanshan; Yuan, Yuan; Liu, Runna; Wang, Supin; Wan, Mingxi

    2015-05-01

    Cavitation is considered as the primary mechanism of soft tissue fragmentation (histotripsy) by pulsed high-intensity focused ultrasound. The residual cavitation bubbles have a dual influence on the histotripsy pulses: these serve as nuclei for easy generation of new cavitation, and act as strong scatterers causing energy "shadowing." To monitor the residual cavitation bubbles in histotripsy, an ultrafast active cavitation imaging method with relatively high signal-to-noise ratio and good spatial-temporal resolution was proposed in this paper, which combined plane wave transmission, minimum variance beamforming, and coherence factor weighting. The spatial-temporal evolutions of residual cavitation bubbles around a fluid-tissue interface in histotripsy under pulse duration (PD) of 10-40 μs and pulse repetition frequency (PRF) of 0.67-2 kHz were monitored by this method. The integrated bubble area curves inside the tissue interface were acquired from the bubble image sequence, and the formation process of histotripsy damage was estimated. It was observed that the histotripsy efficiency decreased with both longer PDs and higher PRFs. A direct relationship with a coefficient of 1.0365 between histotripsy lesion area and inner residual bubble area was found. These results can assist in monitoring and optimization of the histotripsy treatment further.

  18. Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

    Directory of Open Access Journals (Sweden)

    Shi Chen

    Full Text Available Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density, subgroup clustering (modularity, triadic property (transitivity, and dyadic interactions (correlation coefficient from a quadratic assignment procedure at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level or temporal (aggregated at daily level resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc. also changed substantially at different time and locations. There were certain time (feeding and location (hay that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect disease transmission pathways.

  19. Development of Gene Expression Fingerprints for Identification of Environmental Contaminants Using cDNA Arrays

    National Research Council Canada - National Science Library

    Inouye, L

    2004-01-01

    ...) to develop cDNA array-based assays that map gene expression from contaminant exposures. Results substantiate that distinct gene expression profiles exist for major contaminant classes such as PARs, PCBs, and PCDD/Fs...

  20. Step into the groove : engineered transcription factors as modulators of gene expression

    NARCIS (Netherlands)

    Visser, A.E.; Verschure, P.J.; Gommans, W.M.; Haisma, H.J.; Rots, M.G.

    2006-01-01

    Increasing knowledge about the influence of dysregulated gene expression in causing numerous diseases opens up new possibilities for the development of innovative therapeutics. In this chapter, we first describe different mechanisms of misregulated gene expression resulting in various

  1. The Influence of Gene Expression Time Delays on Gierer–Meinhardt Pattern Formation Systems

    KAUST Repository

    Seirin Lee, S.; Gaffney, E. A.; Monk, N. A. M.

    2010-01-01

    investigations demonstrate that the behaviour of the Gierer-Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen

  2. Effects of chronic morphine and morphine withdrawal on gene expression in rat peripheral blood mononuclear cells.

    OpenAIRE

    Desjardins , Stephane; Belkai , Emilie; Crete , Dominique; Cordonnier , Laurie; Scherrmann , Jean-Michel; Noble , Florence; Marie-Claire , Cynthia

    2008-01-01

    International audience; Chronic morphine treatment alters gene expression in brain structures. There are increasing evidences showing a correlation, in gene expression modulation, between blood cells and brain in psychological troubles. To test whether gene expression regulation in blood cells could be found in drug addiction, we investigated gene expression profiles in peripheral blood mononuclear (PBMC) cells of saline and morphine-treated rats. In rats chronically treated with morphine, th...

  3. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  4. Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer

    DEFF Research Database (Denmark)

    Jensen, Lars Henrik; Kuramochi, Hidekazu; Crüger, Dorthe Gylling

    2011-01-01

    promoter was only detected in 14 samples and only at a low level with no correlation to gene expression. MSH2 gene expression was not a prognostic factor for overall survival in univariate or multivariate analysis. The gene expression of MSH2 is a potential quantitative marker ready for further clinical...

  5. DMPD: LPS induction of gene expression in human monocytes. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 11257452 LPS induction of gene expression in human monocytes. Guha M, Mackman N. Ce...ll Signal. 2001 Feb;13(2):85-94. (.png) (.svg) (.html) (.csml) Show LPS induction of gene expression in human... monocytes. PubmedID 11257452 Title LPS induction of gene expression in human monocytes. Authors Guha M, Ma

  6. Genome-wide gene expression regulation as a function of genotype and age in C. elegans

    NARCIS (Netherlands)

    Viñuela Rodriguez, A.; Snoek, L.B.; Riksen, J.A.G.; Kammenga, J.E.

    2010-01-01

    Gene expression becomes more variable with age, and it is widely assumed that this is due to a decrease in expression regulation. But currently there is no understanding how gene expression regulatory patterns progress with age. Here we explored genome-wide gene expression variation and regulatory

  7. Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks.

    Science.gov (United States)

    Bhattacharya, Aparajita; Desai, Harsh; DeMarse, Thomas B; Wheeler, Bruce C; Brewer, Gregory J

    2016-01-01

    Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times

  8. Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

    Science.gov (United States)

    Gerashchenko, Dmitry; Pasumarthi, Ravi K; Kilduff, Thomas S

    2017-07-01

    Experimental evidence suggests that restorative processes depend on synaptic plasticity changes in the brain during sleep. We used the expression of plasticity-related genes to assess synaptic plasticity changes during drug-induced sleep. We first characterized sleep induced by eszopiclone in mice during baseline conditions and during the recovery from sleep deprivation. We then compared the expression of 18 genes and two miRNAs critically involved in synaptic plasticity in these mice. Gene expression was assessed in the cerebral cortex and hippocampus by the TaqMan reverse transcription polymerase chain reaction and correlated with sleep parameters. Eszopiclone reduced the latency to nonrapid eye movement (NREM) sleep and increased NREM sleep amounts. Eszopiclone had no effect on slow wave activity (SWA) during baseline conditions but reduced the SWA increase during recovery sleep (RS) after sleep deprivation. Gene expression analyses revealed three distinct patterns: (1) four genes had higher expression either in the cortex or hippocampus in the group of mice with increased amounts of wakefulness; (2) a large proportion of plasticity-related genes (7 out of 18 genes) had higher expression during RS in the cortex but not in the hippocampus; and (3) six genes and the two miRNAs showed no significant changes across conditions. Even at a relatively high dose (20 mg/kg), eszopiclone did not reduce the expression of plasticity-related genes during RS period in the cortex. These results indicate that gene expression associated with synaptic plasticity occurs in the cortex in the presence of a hypnotic medication. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  9. Gravity-regulated gene expression in Arabidopsis thaliana

    Science.gov (United States)

    Sederoff, Heike; Brown, Christopher S.; Heber, Steffen; Kajla, Jyoti D.; Kumar, Sandeep; Lomax, Terri L.; Wheeler, Benjamin; Yalamanchili, Roopa

    Plant growth and development is regulated by changes in environmental signals. Plants sense environmental changes and respond to them by modifying gene expression programs to ad-just cell growth, differentiation, and metabolism. Functional expression of genes comprises many different processes including transcription, translation, post-transcriptional and post-translational modifications, as well as the degradation of RNA and proteins. Recently, it was discovered that small RNAs (sRNA, 18-24 nucleotides long), which are heritable and systemic, are key elements in regulating gene expression in response to biotic and abiotic changes. Sev-eral different classes of sRNAs have been identified that are part of a non-cell autonomous and phloem-mobile network of regulators affecting transcript stability, translational kinetics, and DNA methylation patterns responsible for heritable transcriptional silencing (epigenetics). Our research has focused on gene expression changes in response to gravistimulation of Arabidopsis roots. Using high-throughput technologies including microarrays and 454 sequencing, we iden-tified rapid changes in transcript abundance of genes as well as differential expression of small RNA in Arabidopsis root apices after minutes of reorientation. Some of the differentially regu-lated transcripts are encoded by genes that are important for the bending response. Functional mutants of those genes respond faster to reorientation than the respective wild type plants, indicating that these proteins are repressors of differential cell elongation. We compared the gravity responsive sRNAs to the changes in transcript abundances of their putative targets and identified several potential miRNA: target pairs. Currently, we are using mutant and transgenic Arabidopsis plants to characterize the function of those miRNAs and their putative targets in gravitropic and phototropic responses in Arabidopsis.

  10. Gene expression in cortex and hippocampus during acute pneumococcal meningitis

    Directory of Open Access Journals (Sweden)

    Wittwer Matthias

    2006-06-01

    Full Text Available Abstract Background Pneumococcal meningitis is associated with high mortality (~30% and morbidity. Up to 50% of survivors are affected by neurological sequelae due to a wide spectrum of brain injury mainly affecting the cortex and hippocampus. Despite this significant disease burden, the genetic program that regulates the host response leading to brain damage as a consequence of bacterial meningitis is largely unknown. We used an infant rat model of pneumococcal meningitis to assess gene expression profiles in cortex and hippocampus at 22 and 44 hours after infection and in controls at 22 h after mock-infection with saline. To analyze the biological significance of the data generated by Affymetrix DNA microarrays, a bioinformatics pipeline was used combining (i a literature-profiling algorithm to cluster genes based on the vocabulary of abstracts indexed in MEDLINE (NCBI and (ii the self-organizing map (SOM, a clustering technique based on covariance in gene expression kinetics. Results Among 598 genes differentially regulated (change factor ≥ 1.5; p ≤ 0.05, 77% were automatically assigned to one of 11 functional groups with 94% accuracy. SOM disclosed six patterns of expression kinetics. Genes associated with growth control/neuroplasticity, signal transduction, cell death/survival, cytoskeleton, and immunity were generally upregulated. In contrast, genes related to neurotransmission and lipid metabolism were transiently downregulated on the whole. The majority of the genes associated with ionic homeostasis, neurotransmission, signal transduction and lipid metabolism were differentially regulated specifically in the hippocampus. Of the cell death/survival genes found to be continuously upregulated only in hippocampus, the majority are pro-apoptotic, while those continuously upregulated only in cortex are anti-apoptotic. Conclusion Temporal and spatial analysis of gene expression in experimental pneumococcal meningitis identified potential

  11. Quantifying intrinsic and extrinsic variability in stochastic gene expression models.

    Science.gov (United States)

    Singh, Abhyudai; Soltani, Mohammad

    2013-01-01

    Genetically identical cell populations exhibit considerable intercellular variation in the level of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability in gene expression. More specifically, extrinsic noise is the expression variability that arises from cell-to-cell differences in cell-specific factors such as enzyme levels, cell size and cell cycle stage. In contrast, intrinsic noise is the expression variability that is not accounted for by extrinsic noise, and typically arises from the inherent stochastic nature of biochemical processes. Two-color reporter experiments are employed to decompose expression variability into its intrinsic and extrinsic noise components. Analytical formulas for intrinsic and extrinsic noise are derived for a class of stochastic gene expression models, where variations in cell-specific factors cause fluctuations in model parameters, in particular, transcription and/or translation rate fluctuations. Assuming mRNA production occurs in random bursts, transcription rate is represented by either the burst frequency (how often the bursts occur) or the burst size (number of mRNAs produced in each burst). Our analysis shows that fluctuations in the transcription burst frequency enhance extrinsic noise but do not affect the intrinsic noise. On the contrary, fluctuations in the transcription burst size or mRNA translation rate dramatically increase both intrinsic and extrinsic noise components. Interestingly, simultaneous fluctuations in transcription and translation rates arising from randomness in ATP abundance can decrease intrinsic noise measured in a two-color reporter assay. Finally, we discuss how these formulas can be combined with single-cell gene expression data from two-color reporter experiments for estimating model parameters.

  12. Time course of gene expression during mouse skeletal muscle hypertrophy.

    Science.gov (United States)

    Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

    2013-10-01

    The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

  13. Epigenetic regulation on the gene expression signature in esophagus adenocarcinoma.

    Science.gov (United States)

    Xi, Ting; Zhang, Guizhi

    2017-02-01

    Understanding the molecular mechanisms represents an important step in the development of diagnostic and therapeutic measures of esophagus adenocarcinoma (NOS). The objective of this study is to identify the epigenetic regulation on gene expression in NOS, shedding light on the molecular mechanisms of NOS. In this study, 78 patients with NOS were included and the data of mRNA, miRNA and DNA methylation of were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis between NOS and controls was performed in terms of gene expression, miRNA expression, and DNA methylation. Bioinformatic analysis was followed to explore the regulation mechanisms of miRNA and DNA methylationon gene expression. Totally, up to 1320 differentially expressed genes (DEGs) and 32 differentially expressed miRNAs were identified. 240 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. 101 DEGs were found to be highlymethylated in CpG islands. Then, 8 differentially methylated genes (DMGs) were selected, which showed down-regulated expression in NOS. Among of these genes, 6 genes including ADHFE1, DPP6, GRIA4, CNKSR2, RPS6KA6 and ZNF135 were target genes of differentially expressed miRNAs (hsa-mir-335, hsa-mir-18a, hsa-mir-93, hsa-mir-106b and hsa-mir-21). The identified altered miRNA, genes and DNA methylation site may be applied as biomarkers for diagnosis and prognosis of NOS. Copyright © 2016 Elsevier GmbH. All rights reserved.

  14. Analysis of meniscal degeneration and meniscal gene expression

    Directory of Open Access Journals (Sweden)

    Norton James H

    2010-01-01

    Full Text Available Abstract Background Menisci play a vital role in load transmission, shock absorption and joint stability. There is increasing evidence suggesting that OA menisci may not merely be bystanders in the disease process of OA. This study sought: 1 to determine the prevalence of meniscal degeneration in OA patients, and 2 to examine gene expression in OA meniscal cells compared to normal meniscal cells. Methods Studies were approved by our human subjects Institutional Review Board. Menisci and articular cartilage were collected during joint replacement surgery for OA patients and lower limb amputation surgery for osteosarcoma patients (normal control specimens, and graded. Meniscal cells were prepared from these meniscal tissues and expanded in monolayer culture. Differential gene expression in OA meniscal cells and normal meniscal cells was examined using Affymetrix microarray and real time RT-PCR. Results The grades of meniscal degeneration correlated with the grades of articular cartilage degeneration (r = 0.672; P HLA-DPA1, integrin, beta 2 (ITGB2, ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1, ankylosis, progressive homolog (ANKH and fibroblast growth factor 7 (FGF7, were expressed at significantly higher levels in OA meniscal cells compared to normal meniscal cells. Importantly, many of the genes that have been shown to be differentially expressed in other OA cell types/tissues, including ADAM metallopeptidase with thrombospondin type 1 motif 5 (ADAMTS5 and prostaglandin E synthase (PTGES, were found to be expressed at significantly higher levels in OA meniscal cells. This consistency suggests that many of the genes detected in our study are disease-specific. Conclusion Our findings suggest that OA is a whole joint disease. Meniscal cells may play an active role in the development of OA. Investigation of the gene expression profiles of OA meniscal cells may reveal new therapeutic targets for OA therapy and also may uncover novel

  15. Development of Gene Expression Signatures for Practical Radiation Biodosimetry

    International Nuclear Information System (INIS)

    Paul, Sunirmal; Amundson, Sally A.

    2008-01-01

    Purpose: In a large-scale radiologic emergency, estimates of exposure doses and radiation injury would be required for individuals without physical dosimeters. Current methods are inadequate for the task, so we are developing gene expression profiles for radiation biodosimetry. This approach could provide both an estimate of physical radiation dose and an indication of the extent of individual injury or future risk. Methods and Materials: We used whole genome microarray expression profiling as a discovery platform to identify genes with the potential to predict radiation dose across an exposure range relevant for medical decision making in a radiologic emergency. Human peripheral blood from 10 healthy donors was irradiated ex vivo, and global gene expression was measured both 6 and 24 h after exposure. Results: A 74-gene signature was identified that distinguishes between four radiation doses (0.5, 2, 5, and 8 Gy) and controls. More than one third of these genes are regulated by TP53. A nearest centroid classifier using these same 74 genes correctly predicted 98% of samples taken either 6 h or 24 h after treatment as unexposed, exposed to 0.5, 2, or ≥5 Gy. Expression patterns of five genes (CDKN1A, FDXR, SESN1, BBC3, and PHPT1) from this signature were also confirmed by real-time polymerase chain reaction. Conclusion: The ability of a single gene set to predict radiation dose throughout a window of time without need for individual pre-exposure controls represents an important advance in the development of gene expression for biodosimetry

  16. Cocoa polyphenols and fiber modify colonic gene expression in rats.

    Science.gov (United States)

    Massot-Cladera, Malen; Franch, Àngels; Castell, Margarida; Pérez-Cano, Francisco J

    2017-08-01

    Cocoa intake has been associated with health benefits, improving cardiovascular function and metabolism, as well as modulating intestinal immune function. The aim of this study was to take an in-depth look into the mechanisms affected by the cocoa intake by evaluating the colonic gene expression after nutritional intervention, and to ascertain the role of the fiber of cocoa in these effects. To achieve this, Wistar rats were fed for 3 weeks with either a reference diet, a diet containing 10 % cocoa (C10), a diet based on cocoa fiber (CF) or a diet containing inulin (I). At the end of the study, colon was excised to obtain the RNA to evaluate the differential gene expression by microarray. Results were validated by RT-PCR. The C10 group was the group with most changes in colonic gene expression, most of them down-regulated but a few in common with the CF diet. The C10 diet significantly up-regulated the expression of Scgb1a1 and Scnn1 g and down-regulated Tac4, Mcpt2, Fcer1a and Fabp1 by twofold, most of them related to lipid metabolism and immune function. The CF and I diets down-regulated the expression of Serpina10 and Apoa4 by twofold. Similar patterns of expression were found by PCR. Most of the effects attributed to cocoa consumption on genes related to the immune system (B cell and mast cell functionality) and lipid metabolism in the colon tissue were due not only to its fiber content, but also to the possible contribution of polyphenols and other compounds.

  17. Kinetic models of gene expression including non-coding RNAs

    Energy Technology Data Exchange (ETDEWEB)

    Zhdanov, Vladimir P., E-mail: zhdanov@catalysis.r

    2011-03-15

    In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

  18. Automatic Control of Gene Expression in Mammalian Cells.

    Science.gov (United States)

    Fracassi, Chiara; Postiglione, Lorena; Fiore, Gianfranco; di Bernardo, Diego

    2016-04-15

    Automatic control of gene expression in living cells is paramount importance to characterize both endogenous gene regulatory networks and synthetic circuits. In addition, such a technology can be used to maintain the expression of synthetic circuit components in an optimal range in order to ensure reliable performance. Here we present a microfluidics-based method to automatically control gene expression from the tetracycline-inducible promoter in mammalian cells in real time. Our approach is based on the negative-feedback control engineering paradigm. We validated our method in a monoclonal population of cells constitutively expressing a fluorescent reporter protein (d2EYFP) downstream of a minimal CMV promoter with seven tet-responsive operator motifs (CMV-TET). These cells also constitutively express the tetracycline transactivator protein (tTA). In cells grown in standard growth medium, tTA is able to bind the CMV-TET promoter, causing d2EYFP to be maximally expressed. Upon addition of tetracycline to the culture medium, tTA detaches from the CMV-TET promoter, thus preventing d2EYFP expression. We tested two different model-independent control algorithms (relay and proportional-integral (PI)) to force a monoclonal population of cells to express an intermediate level of d2EYFP equal to 50% of its maximum expression level for up to 3500 min. The control input is either tetracycline-rich or standard growth medium. We demonstrated that both the relay and PI controllers can regulate gene expression at the desired level, despite oscillations (dampened in the case of the PI controller) around the chosen set point.

  19. A comparative analysis of biclustering algorithms for gene expression data

    Science.gov (United States)

    Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.

    2013-01-01

    The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837

  20. Environmental control of plant nuclear gene expression by chloroplast redox signals

    Directory of Open Access Journals (Sweden)

    Jeannette ePfalz

    2012-11-01

    Full Text Available Plant photosynthesis takes place in specialised cell organelles, the chloroplasts, which perform all essential steps of this process. The proteins involved in photosynthesis are encoded by genes located on the plastid and nuclear genomes. Proper function and regulation of light harvesting and energy fixation thus requires a tight coordination of the gene expression machineries in the two genetic compartments. This is achieved by a bi-directional exchange of information between nucleus and plastids. Signals emerging from plastids report the functional and developmental state of the organelle to the nucleus and initiate distinct nuclear gene expression profiles, which trigger responses that support or improve plastid functions. Recent research indicated that this signalling is absolutely essential for plant growth and development. Reduction/oxidation (redox signals from photosynthesis are key players in this information network since they do report functional disturbances in photosynthesis, the primary energy source of plants. Such disturbances are caused by environmental fluctuations for instance in illumination, temperature or water availability. These environmental changes affect the linear electron flow of photosynthesis and result in changes of the redox state of the components involved (e.g. the plastoquinone pool or coupled to it (e.g. the thioredoxin pool. Thus, the changes in redox state directly reflect the environmental impact and serve as immediate plastidial signals to the nucleus. The triggered responses range from counterbalancing reactions within the physiological range up to severe stress responses including cell death. This review focuses on physiological redox signals from photosynthetic electron transport, their relation to the environment, potential transduction pathways to the nucleus and their impact on nuclear gene expression.

  1. Photobiomodulation changes type 1 collagen gene expression by pulp fibroblasts

    Science.gov (United States)

    Lourenço Ribeiro Vitor, Luciana; Tavares Oliveira Prado, Mariel; Lourenço Neto, Natalino; Cardoso de Oliveira, Rodrigo; Ferreira Santos, Carlos; Moreira Machado, Maria Aparecida Andrade; Marchini Oliveira, Thais

    2018-06-01

    This study aimed to evaluate type 1 collagen (COL1) gene expression by human pulp fibroblasts from primary teeth (HPF) after the variation of photobiomodulation (PBM) parameters. HPF were obtained from a biorepository, used at 4th passage, and irradiated (InGaAlP—660 nm) varying the power and application time according to the following groups: G1: 1.2 J cm‑2–05 mW–10 s G2: 2.5 J cm‑2–05 mW–20 s G3: 3.7 J cm‑2–05 mW–30 s G4: 5.0 J cm‑2–05 mW–40 s G5: 6.2 J cm‑2–05 mW–50 s G6: 2.5 J cm‑2–10 mW–10 s G7: 3.7 J cm‑2–15 mW–10 s G8: 5.0 J cm‑2–20 mW–10 s G9: 6.2 J cm‑2–25 mW–10 s. The control group (G10) was not irradiated and maintained with DMEM  +  10% SFB. RT-PCR was used to evaluate COL1 gene expression at 6, 12, and 24 h after irradiation. Intra- and intergroup comparisons were performed by two-way ANOVA followed by Tukey test (p  differences among periods (p  differences (p  >  0.05). The energy densities from 2.5 to 5 J cm‑2, regardless of the variation in PBM parameters, biomodulated the COL1 gene expression. At the energy density of 6.2 J cm‑2, longer application time and smaller power changed the pattern of COL1 gene expression by pulp fibroblasts from human primary teeth.

  2. Impact of methoxyacetic acid on mouse Leydig cell gene expression

    Directory of Open Access Journals (Sweden)

    Waxman David J

    2010-06-01

    Full Text Available Abstract Background Methoxyacetic acid (MAA is the active metabolite of the widely used industrial chemical ethylene glycol monomethyl ether, which is associated with various developmental and reproductive toxicities, including neural toxicity, blood and immune disorders, limb degeneration and testicular toxicity. Testicular toxicity is caused by degeneration of germ cells in association with changes in gene expression in both germ cells and Sertoli cells of the testis. This study investigates the impact of MAA on gene expression in testicular Leydig cells, which play a critical role in germ cell survival and male reproductive function. Methods Cultured mouse TM3 Leydig cells were treated with MAA for 3, 8, and 24 h and changes in gene expression were monitored by genome-wide transcriptional profiling. Results A total of 3,912 MAA-responsive genes were identified. Ingenuity Pathway analysis identified reproductive system disease, inflammatory disease and connective tissue disorder as the top biological functions affected by MAA. The MAA-responsive genes were classified into 1,366 early responders, 1,387 mid-responders, and 1,138 late responders, based on the time required for MAA to elicit a response. Analysis of enriched functional clusters for each subgroup identified 106 MAA early response genes involved in transcription regulation, including 32 genes associated with developmental processes. 60 DNA-binding proteins responded to MAA rapidly but transiently, and may contribute to the downstream effects of MAA seen for many mid and late response genes. Genes within the phosphatidylinositol/phospholipase C/calcium signaling pathway, whose activity is required for potentiation of nuclear receptor signaling by MAA, were also enriched in the set of early MAA response genes. In contrast, many of the genes responding to MAA at later time points encode membrane proteins that contribute to cell adhesion and membrane signaling. Conclusions These findings

  3. Mechanisms of gap gene expression canalization in the Drosophila blastoderm

    Directory of Open Access Journals (Sweden)

    Samsonova Maria G

    2011-07-01

    Full Text Available Abstract Background Extensive variation in early gap gene expression in the Drosophila blastoderm is reduced over time because of gap gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of gap gene expression can be understood as arising from the actions of attractors in the gap gene dynamical system. Results In order to better understand the processes of developmental robustness and canalization in the early Drosophila embryo, we investigated the dynamical effects of varying spatial profiles of Bicoid protein concentration on the formation of the expression border of the gap gene hunchback. At several positions on the anterior-posterior axis of the embryo, we analyzed attractors and their basins of attraction in a dynamical model describing expression of four gap genes with the Bicoid concentration profile accounted as a given input in the model equations. This model was tested against a family of Bicoid gradients obtained from individual embryos. These gradients were normalized by two independent methods, which are based on distinct biological hypotheses and provide different magnitudes for Bicoid spatial variability. We showed how the border formation is dictated by the biological initial conditions (the concentration gradient of maternal Hunchback protein being attracted to specific attracting sets in a local vicinity of the border. Different types of these attracting sets (point attractors or one dimensional attracting manifolds define several possible mechanisms of border formation. The hunchback border formation is associated with intersection of the spatial gradient of the maternal Hunchback protein and a boundary between the attraction basins of two different point attractors. We demonstrated how the positional variability for hunchback is related to the corresponding variability of the

  4. Gene expression profiling in hypertension research: a critical perspective

    Czech Academy of Sciences Publication Activity Database

    Pravenec, Michal; Wallace, C.; Aitman, T. J.; Kurtz, T. W.

    2003-01-01

    Roč. 41, č. 1 (2003), s. 3-8 ISSN 0194-911X R&D Projects: GA MŠk LN00A079; GA ČR GA301/01/0278; GA MZd NB6468 Grant - others:NIH(US) RO1 HL56028; NIH(US) RO1 HL56608; NIH(US) RO3 TW01236; NIH(US) RO1 HL63707 Institutional research plan: CEZ:AV0Z5011922 Keywords : gene expression * hypertension * genes Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.630, year: 2003

  5. Integration of biological networks and gene expression data using Cytoscape

    DEFF Research Database (Denmark)

    Cline, M.S.; Smoot, M.; Cerami, E.

    2007-01-01

    of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

  6. Control of gene expression by CRISPR-Cas systems

    Science.gov (United States)

    2013-01-01

    Clustered regularly interspaced short palindromic repeats (CRISPR) loci and their associated cas (CRISPR-associated) genes provide adaptive immunity against viruses (phages) and other mobile genetic elements in bacteria and archaea. While most of the early work has largely been dominated by examples of CRISPR-Cas systems directing the cleavage of phage or plasmid DNA, recent studies have revealed a more complex landscape where CRISPR-Cas loci might be involved in gene regulation. In this review, we summarize the role of these loci in the regulation of gene expression as well as the recent development of synthetic gene regulation using engineered CRISPR-Cas systems. PMID:24273648

  7. How does the extracellular matrix direct gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Bissell, M J; Hall, H G; Parry, G

    1982-01-01

    Based on the existing literature, a model is presented that postulates a ''dynamic reciprocity'' between the extracellular matrix (ECM) on the one hand and the cytoskeleton and the nuclear matrix on the other hand. The ECM is postulated to exert physical and chemical influences on the geometry and the biochemistry of the cell via transmembrane receptors so as to alter the pattern of gene expression by changing the association of the cytoskeleton with mRNA and the interaction of the chromatin with the nuclear matrix. This, in turn, would affect the ECM, which would affect the cell.

  8. The application of DNA microarrays in gene expression analysis.

    Science.gov (United States)

    van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

    2000-03-31

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

  9. A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

    Directory of Open Access Journals (Sweden)

    Wei Tu

    2015-10-01

    Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

  10. Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.

    Science.gov (United States)

    Moon, Myungjin; Nakai, Kenta

    2018-04-01

    Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.

  11. An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets.

    Science.gov (United States)

    Hosseini, Parsa; Tremblay, Arianne; Matthews, Benjamin F; Alkharouf, Nadim W

    2010-07-02

    The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data

  12. RETINOBASE: a web database, data mining and analysis platform for gene expression data on retina

    Directory of Open Access Journals (Sweden)

    Léveillard Thierry

    2008-05-01

    Full Text Available Abstract Background The retina is a multi-layered sensory tissue that lines the back of the eye and acts at the interface of input light and visual perception. Its main function is to capture photons and convert them into electrical impulses that travel along the optic nerve to the brain where they are turned into images. It consists of neurons, nourishing blood vessels and different cell types, of which neural cells predominate. Defects in any of these cells can lead to a variety of retinal diseases, including age-related macular degeneration, retinitis pigmentosa, Leber congenital amaurosis and glaucoma. Recent progress in genomics and microarray technology provides extensive opportunities to examine alterations in retinal gene expression profiles during development and diseases. However, there is no specific database that deals with retinal gene expression profiling. In this context we have built RETINOBASE, a dedicated microarray database for retina. Description RETINOBASE is a microarray relational database, analysis and visualization system that allows simple yet powerful queries to retrieve information about gene expression in retina. It provides access to gene expression meta-data and offers significant insights into gene networks in retina, resulting in better hypothesis framing for biological problems that can subsequently be tested in the laboratory. Public and proprietary data are automatically analyzed with 3 distinct methods, RMA, dChip and MAS5, then clustered using 2 different K-means and 1 mixture models method. Thus, RETINOBASE provides a framework to compare these methods and to optimize the retinal data analysis. RETINOBASE has three different modules, "Gene Information", "Raw Data System Analysis" and "Fold change system Analysis" that are interconnected in a relational schema, allowing efficient retrieval and cross comparison of data. Currently, RETINOBASE contains datasets from 28 different microarray experiments performed

  13. Cooperative binding of transcription factors promotes bimodal gene expression response.

    Directory of Open Access Journals (Sweden)

    Pablo S Gutierrez

    Full Text Available In the present work we extend and analyze the scope of our recently proposed stochastic model for transcriptional regulation, which considers an arbitrarily complex cis-regulatory system using only elementary reactions. Previously, we determined the role of cooperativity on the intrinsic fluctuations of gene expression for activating transcriptional switches, by means of master equation formalism and computer simulation. This model allowed us to distinguish between two cooperative binding mechanisms and, even though the mean expression levels were not affected differently by the acting mechanism, we showed that the associated fluctuations were different. In the present generalized model we include other regulatory functions in addition to those associated to an activator switch. Namely, we introduce repressive regulatory functions and two theoretical mechanisms that account for the biphasic response that some cis-regulatory systems show to the transcription factor concentration. We have also extended our previous master equation formalism in order to include protein production by stochastic translation of mRNA. Furthermore, we examine the graded/binary scenarios in the context of the interaction energy between transcription factors. In this sense, this is the first report to show that the cooperative binding of transcription factors to DNA promotes the "all-or-none" phenomenon observed in eukaryotic systems. In addition, we confirm that gene expression fluctuation levels associated with one of two cooperative binding mechanism never exceed the fluctuation levels of the other.

  14. Drosophila Myc is required for normal DREF gene expression

    International Nuclear Information System (INIS)

    Dang Thi Phuong Thao; Seto, Hirokazu; Yamaguchi, Masamitsu

    2008-01-01

    The Drosophila DNA replication-related element-binding factor (dDREF) is required for the expression of many proliferation-related genes carrying the DRE sequence, 5'-TATCGATA. Finding a canonical E-box, 5'-CACGTG, in the dDREF gene promoter prompted us to explore the possibility that the dDREF gene is a target of Drosophila Myc (dMyc). Luciferase transient expression assays combined with RNA interference in Drosophila S2 cells revealed that knockdown of dmyc reduced dDREF gene promoter activity by 35% to 82%, an effect at least partly mediated by the E-box in the promoter. dm 4 /Y hemizygous mutant larvae demonstrated no maternal dMyc and severe impairment of dDREF mRNA transcription. dMyc loss of function in dm 2 /dm 2 homozygous mutant follicle cell clones also resulted in loss of anti-dDREF immunostaining in nuclei. In contrast, co-expression of dMyc-dMax up-regulated dDREF promoter activity in S2 cells. Furthermore, dMyc over-expressing clones exhibited a high level of dDREF gene expression in wing and eye discs. These results taken together indicate that dMyc is indeed required for dDREF gene expression

  15. Global gene expression profile progression in Gaucher disease mouse models

    Directory of Open Access Journals (Sweden)

    Zhang Wujuan

    2011-01-01

    Full Text Available Abstract Background Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells in visceral organs and their abnormal functions are obscure. Results To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct Gba1 point-mutated mice (V394L/V394L and D409 V/null. About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change, representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk of INFγ-regulated pro-inflammatory (13 and IL-4-regulated anti-inflammatory (11 cytokine/mediator networks showed tissue differential profiles in the lung and liver of the Gba1 mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the Gba1 mutation. Conclusions Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.

  16. Aging: a portrait from gene expression profile in blood cells.

    Science.gov (United States)

    Calabria, Elisa; Mazza, Emilia Maria Cristina; Dyar, Kenneth Allen; Pogliaghi, Silvia; Bruseghini, Paolo; Morandi, Carlo; Salvagno, Gian Luca; Gelati, Matteo; Guidi, Gian Cesare; Bicciato, Silvio; Schiaffino, Stefano; Schena, Federico; Capelli, Carlo

    2016-08-01

    The availability of reliable biomarkers of aging is important not only to monitor the effect of interventions and predict the timing of pathologies associated with aging but also to understand the mechanisms and devise appropriate countermeasures. Blood cells provide an easily available tissue and gene expression profiles from whole blood samples appear to mirror disease states and some aspects of the aging process itself. We report here a microarray analysis of whole blood samples from two cohorts of healthy adult and elderly subjects, aged 43±3 and 68±4 years, respectively, to monitor gene expression changes in the initial phase of the senescence process. A number of significant changes were found in the elderly compared to the adult group, including decreased levels of transcripts coding for components of the mitochondrial respiratory chain, which correlate with a parallel decline in the maximum rate of oxygen consumption (VO2max), as monitored in the same subjects. In addition, blood cells show age-related changes in the expression of several markers of immunosenescence, inflammation and oxidative stress. These findings support the notion that the immune system has a major role in tissue homeostasis and repair, which appears to be impaired since early stages of the aging process.

  17. Post-transcriptional regulation of gene expression in Yersinia species

    Directory of Open Access Journals (Sweden)

    Chelsea A Schiano

    2012-11-01

    Full Text Available Proper regulation of gene expression is required by bacterial pathogens to respond to continually changing environmental conditions and the host response during the infectious process. While transcriptional regulation is perhaps the most well understood form of controlling gene expression, recent studies have demonstrated the importance of post-transcriptional mechanisms of gene regulation that allow for more refined management of the bacterial response to host conditions. Yersinia species of bacteria are known to use various forms of post-transcriptional regulation for control of many virulence-associated genes. These include regulation by cis- and trans-acting small non-coding RNAs, RNA-binding proteins, RNases, and thermoswitches. The effects of these and other regulatory mechanisms on Yersinia physiology can be profound and have been shown to influence type III secretion, motility, biofilm formation, host cell invasion, intracellular survival and replication, and more. In this review, we will discuss these and other post-transcriptional mechanisms and their influence on virulence gene regulation, with a particular emphasis on how these processes influence the virulence of Yersinia in the host.

  18. Beta-Glucan Synthase Gene Expression in Pleurotus sp

    International Nuclear Information System (INIS)

    Azhar Mohamad; Nie, H.J.

    2016-01-01

    Pleurotus sp. is a popular edible mushroom, containing various functional component, in particular, Beta-glucan. Beta-glucans is a part of glucan family of polysaccharides and supposedly contribute to medicinal and nutritional value of Pleurotus.sp. In order to understand the distribution of Beta-glucan in Pleurotus.sp, the Beta-glucan synthase gene expression was determined and compared in different part of Pleurotus, namely mycelium, stripe and cap. The Pleurotus.sp RNA was extracted using commercial kit, employing Tissuelyser ll (Qiagen, USA) to disrupt the cell walls. Then the RNA was quantified by Nano drop (Thermo Fisher, USA) and visualized using denaturing agarose gel. RNA with good OD 260.280 reading (∼2.0) was chosen and converted to cDNA. Using Laccase synthase gene as home keeping gene, Beta-glucan synthase gene expression was quantified using CFX 96 Real Time PCR detection system (Biorad, USA). Preliminary result shows that Beta-glucan synthase was relatively expressed the most in stripe, followed by mycelium and barely in cap. (author)

  19. Integrative sparse principal component analysis of gene expression data.

    Science.gov (United States)

    Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

    2017-12-01

    In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

  20. Chemical memory reactions induced bursting dynamics in gene expression.

    Science.gov (United States)

    Tian, Tianhai

    2013-01-01

    Memory is a ubiquitous phenomenon in biological systems in which the present system state is not entirely determined by the current conditions but also depends on the time evolutionary path of the system. Specifically, many memorial phenomena are characterized by chemical memory reactions that may fire under particular system conditions. These conditional chemical reactions contradict to the extant stochastic approaches for modeling chemical kinetics and have increasingly posed significant challenges to mathematical modeling and computer simulation. To tackle the challenge, I proposed a novel theory consisting of the memory chemical master equations and memory stochastic simulation algorithm. A stochastic model for single-gene expression was proposed to illustrate the key function of memory reactions in inducing bursting dynamics of gene expression that has been observed in experiments recently. The importance of memory reactions has been further validated by the stochastic model of the p53-MDM2 core module. Simulations showed that memory reactions is a major mechanism for realizing both sustained oscillations of p53 protein numbers in single cells and damped oscillations over a population of cells. These successful applications of the memory modeling framework suggested that this innovative theory is an effective and powerful tool to study memory process and conditional chemical reactions in a wide range of complex biological systems.

  1. Early signatures of regime shifts in gene expression dynamics

    Science.gov (United States)

    Pal, Mainak; Pal, Amit Kumar; Ghosh, Sayantari; Bose, Indrani

    2013-06-01

    Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis. We consider two alternative models, models 1 and 2, of competence development in the bacterial population B. subtilis and determine some early signatures of the regime shifts between competence and noncompetence. We use both deterministic and stochastic formalisms for the purpose of our study. The early signatures studied include the critical slowing down as a transition point is approached, rising variance and the lag-1 autocorrelation function, skewness and a ratio of two mean first passage times. Some of the signatures could provide the experimental basis for distinguishing between bistability and excitability as the correct mechanism for the development of competence.

  2. Gene Expression Correlation for Cancer Diagnosis: A Pilot Study

    Directory of Open Access Journals (Sweden)

    Binbing Ling

    2014-01-01

    Full Text Available Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68≤r≤1.0 were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.

  3. Regulation of gene expression and pain states by epigenetic mechanisms.

    Science.gov (United States)

    Géranton, Sandrine M; Tochiki, Keri K

    2015-01-01

    The induction of inflammatory or neuropathic pain states is known to involve molecular activity in the spinal superficial dorsal horn and dorsal root ganglia, including intracellular signaling events which lead to changes in gene expression. These changes ultimately cause alterations in macromolecular synthesis, synaptic transmission, and structural architecture which support central sensitization, a process required for the establishment of long-term pain states. Epigenetic mechanisms are essential for long-term synaptic plasticity and modulation of gene expression. This is because epigenetic modifications are known to regulate gene transcription by aiding the physical relaxation or condensation of chromatin. These processes are therefore potential regulators of the molecular changes underlying permanent pain states. A handful of studies have emerged in the field of pain epigenetics; however, the field is still very much in its infancy. This chapter draws upon other specialities which have extensively investigated epigenetic mechanisms, such as learning and memory and oncology. After defining epigenetics as well as the recent field of "neuroepigenetics" and the main molecular mechanisms involved, this chapter describes the role of these mechanisms in the synaptic plasticity seen in learning and memory, and address those epigenetic mechanisms that have been linked with the development of acute and prolonged pain states. Finally, the idea that long-lasting epigenetic modifications could contribute to the transition from acute to chronic pain states by supporting maladaptive molecular changes is discussed. © 2015 Elsevier Inc. All rights reserved.

  4. Capturing heterogeneity in gene expression studies by surrogate variable analysis.

    Directory of Open Access Journals (Sweden)

    Jeffrey T Leek

    2007-09-01

    Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

  5. Gene expression profiles of mouse spermatogenesis during recovery from irradiation

    DEFF Research Database (Denmark)

    Shah, Fozia J; Tanaka, Masami; Nielsen, John E

    2009-01-01

    BACKGROUND: Irradiation or chemotherapy that suspend normal spermatogenesis is commonly used to treat various cancers. Fortunately, spermatogenesis in many cases can be restored after such treatments but knowledge is limited about the re-initiation process. Earlier studies have described the cell......BACKGROUND: Irradiation or chemotherapy that suspend normal spermatogenesis is commonly used to treat various cancers. Fortunately, spermatogenesis in many cases can be restored after such treatments but knowledge is limited about the re-initiation process. Earlier studies have described...... the cellular changes that happen during recovery from irradiation by means of histology. We have earlier generated gene expression profiles during induction of spermatogenesis in mouse postnatal developing testes and found a correlation between profiles and the expressing cell types. The aim of the present...... work was to utilize the link between expression profile and cell types to follow the cellular changes that occur during post-irradiation recovery of spermatogenesis in order to describe recovery by means of gene expression. METHODS: Adult mouse testes were subjected to irradiation with 1 Gy...

  6. Correlation between Gene Expression and Osteoarthritis Progression in Human.

    Science.gov (United States)

    Zhong, Leilei; Huang, Xiaobin; Karperien, Marcel; Post, Janine N

    2016-07-14

    Osteoarthritis (OA) is a multifactorial disease characterized by gradual degradation of joint cartilage. This study aimed to quantify major pathogenetic factors during OA progression in human cartilage. Cartilage specimens were isolated from OA patients and scored 0-5 according to the Osteoarthritis Research Society International (OARSI) guidelines. Protein and gene expressions were measured by immunohistochemistry and qPCR, respectively. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays were used to detect apoptotic cells. Cartilage degeneration in OA is a gradual progress accompanied with gradual loss of collagen type II and a gradual decrease in mRNA expression of SOX9, ACAN and COL2A1. Expression of WNT antagonists DKK1 and FRZB was lost, while hypertrophic markers (RUNX2, COL10A1 and IHH) increased during OA progression. Moreover, DKK1 and FRZB negatively correlated with OA grading, while RUNX2 and IHH showed a significantly positive correlation with OA grading. The number of apoptotic cells was increased with the severity of OA. Taken together, our results suggested that genetic profiling of the gene expression could be used as markers for staging OA at the molecular level. This helps to understand the molecular pathology of OA and may lead to the development of therapies based on OA stage.

  7. Correlation between Gene Expression and Osteoarthritis Progression in Human

    Directory of Open Access Journals (Sweden)

    Leilei Zhong

    2016-07-01

    Full Text Available Osteoarthritis (OA is a multifactorial disease characterized by gradual degradation of joint cartilage. This study aimed to quantify major pathogenetic factors during OA progression in human cartilage. Cartilage specimens were isolated from OA patients and scored 0–5 according to the Osteoarthritis Research Society International (OARSI guidelines. Protein and gene expressions were measured by immunohistochemistry and qPCR, respectively. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL assays were used to detect apoptotic cells. Cartilage degeneration in OA is a gradual progress accompanied with gradual loss of collagen type II and a gradual decrease in mRNA expression of SOX9, ACAN and COL2A1. Expression of WNT antagonists DKK1 and FRZB was lost, while hypertrophic markers (RUNX2, COL10A1 and IHH increased during OA progression. Moreover, DKK1 and FRZB negatively correlated with OA grading, while RUNX2 and IHH showed a significantly positive correlation with OA grading. The number of apoptotic cells was increased with the severity of OA. Taken together, our results suggested that genetic profiling of the gene expression could be used as markers for staging OA at the molecular level. This helps to understand the molecular pathology of OA and may lead to the development of therapies based on OA stage.

  8. Interplay of bistable kinetics of gene expression during cellular growth

    International Nuclear Information System (INIS)

    Zhdanov, Vladimir P

    2009-01-01

    In cells, the bistable kinetics of gene expression can be observed on the level of (i) one gene with positive feedback between protein and mRNA production, (ii) two genes with negative mutual feedback between protein and mRNA production, or (iii) in more complex cases. We analyse the interplay of two genes of type (ii) governed by a gene of type (i) during cellular growth. In particular, using kinetic Monte Carlo simulations, we show that in the case where gene 1, operating in the bistable regime, regulates mutually inhibiting genes 2 and 3, also operating in the bistable regime, the latter genes may eventually be trapped either to the state with high transcriptional activity of gene 2 and low activity of gene 3 or to the state with high transcriptional activity of gene 3 and low activity of gene 2. The probability to get to one of these states depends on the values of the model parameters. If genes 2 and 3 are kinetically equivalent, the probability is equal to 0.5. Thus, our model illustrates how different intracellular states can be chosen at random with predetermined probabilities. This type of kinetics of gene expression may be behind complex processes occurring in cells, e.g., behind the choice of the fate by stem cells

  9. Nanobarcode gene expression monitoring system for potential miniaturized space applications

    Science.gov (United States)

    Ruan, Weiming; Eastman, P. Scott; Cooke, Patrick A.; Park, Jennifer S.; Chu, Julia S. F.; Gray, Joe W.; Li, Song; Chen, Fanqing Frank

    Manned mission to space has been threatened by various cosmos risks including radiation, mirogravity, vacuum, confinement, etc., which may cause genetic variations of astronauts and eventually lead to damages of their health. Thus, the development of small biomedical devices, which can monitor astronaut gene expression changes, is useful for future long-term space missions. Using magnetic microbeads packed with nanocrystal quantum dots at controlled ratios, we were able to generate highly multiplexed nanobarcodes, which can encode a flexible panel of genes. Also, by using a reporter quantum dot, this nanobarcode platform can monitor and quantify gene expression level with improved speed and sensitivity. As a comparison, we studied TGF-β1 induced transcription changes in human bone marrow mesenchymal stem cells with both the nanobarcode microbead system and the Affymetrix GeneChip ® HTA system, which is currently considered as the industrial standard. Though using only 1/20 of the sample RNA, the nanobarcode system showed sensitivity equivalent to Affymetrix GeneChip ® system. The coefficient of variation, dynamic range, and accuracy of the nanobarcodes measurement is equivalent to that of the GeneChip ® HTA system. Therefore, this newly invented nanobarcode microbead platform is thought to be sensitive, flexible, cost-effective and accurate in a level equivalent to the conventional methods. As an extension of the use of this new platform, spacecrafts may carry this miniaturized system as a diagnostic tool for the astronauts.

  10. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  11. Changes in gene expression during male meiosis in Petunia hybrida.

    Science.gov (United States)

    Cnudde, Filip; Hedatale, Veena; de Jong, Hans; Pierson, Elisabeth S; Rainey, Daphne Y; Zabeau, Marc; Weterings, Koen; Gerats, Tom; Peters, Janny L

    2006-01-01

    We analyzed changes in gene expression during male meiosis in Petunia by combining the meiotic staging of pollen mother cells from a single anther with cDNA-AFLP transcript profiling of mRNA from the synchronously developing sister anthers. The transcript profiling experiments focused on the identification of genes with a modulated expression profile during meiosis, while premeiotic archesporial cells and postmeiotic microspores served as a reference. About 8000 transcript tags, estimated at 30% of the total transcriptome, were generated, of which around 6% exhibited a modulated gene expression pattern at meiosis. Cluster analysis revealed a transcriptional cascade that coincides with the initiation and progression through all stages of the two meiotic divisions. Fragments that exhibited high expression specifically during meiosis I were characterized further by sequencing; 90 out of the 293 sequenced fragments showed homology with known genes, belonging to a wide range of gene classes, including previously characterized meiotic genes. In-situ hybridization experiments were performed to determine the spatial expression pattern for five selected transcript tags. Its concurrence with cDNA-AFLP transcript profiles indicates that this is an excellent approach to study genes involved in specialized processes such as meiosis. Our data set provides the potential to unravel unique meiotic genes that are as yet elusive to reverse genetics approaches.

  12. Anterior-posterior regionalized gene expression in the Ciona notochord.

    Science.gov (United States)

    Reeves, Wendy; Thayer, Rachel; Veeman, Michael

    2014-04-01

    In the simple ascidian chordate Ciona, the signaling pathways and gene regulatory networks giving rise to initial notochord induction are largely understood and the mechanisms of notochord morphogenesis are being systematically elucidated. The notochord has generally been thought of as a non-compartmentalized or regionalized organ that is not finely patterned at the level of gene expression. Quantitative imaging methods have recently shown, however, that notochord cell size, shape, and behavior vary consistently along the anterior-posterior (AP) axis. Here we screen candidate genes by whole mount in situ hybridization for potential AP asymmetry. We identify 4 genes that show non-uniform expression in the notochord. Ezrin/radixin/moesin (ERM) is expressed more strongly in the secondary notochord lineage than the primary. CTGF is expressed stochastically in a subset of notochord cells. A novel calmodulin-like gene (BCamL) is expressed more strongly at both the anterior and posterior tips of the notochord. A TGF-β ortholog is expressed in a gradient from posterior to anterior. The asymmetries in ERM, BCamL, and TGF-β expression are evident even before the notochord cells have intercalated into a single-file column. We conclude that the Ciona notochord is not a homogeneous tissue but instead shows distinct patterns of regionalized gene expression. Copyright © 2013 Wiley Periodicals, Inc.

  13. Contact inhibition and interferon (IFN)-modulated gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Kulesh, D.A.

    1986-01-01

    The relationship between cell morphology, proliferation and contact inhibition was studied in normal and malignant human cells which varied in their sensitivity to contact inhibition. Their ability to proliferate was examined under conditions where the cells were constrained into different shapes. Cell proliferation was quantitated by labeling indices, which were inferred by autoradiography, and by total cell counts. The normal cells (JHU-1, IMR-90) were dependent on cell shape for proliferation capability while the transformed cells (RT4, HT1080) were shape-dependent for proliferation. Interferon (IFN) induced shape-dependent proliferation and contact inhibition in the transformed cells when used at subantiproliferative concentrations. This ability of B-IFN to confer a level of proliferation control which is characteristic of normal fibroblasts suggests a possible relationship between gene expression mediated by IFN and those genes involved in the maintenance of regulated cell proliferation. To evaluate this possibility, cDNA libraries were constructed from IFN-treated and untreated HT1080 cells. The resulting 10 IFN-induced and 11 IFN-repressed sequences were then differentially rescreened using /sup 32/P-cDNA probes. This screening resulted in the identification of at least four cDNA sequences which appeared to be proliferation regulated as well as IFN-modulated. These cloned, regulated cDNA sequences were then used as /sup 32/P-labeled probes to study both the gene expression at the mRNA level employing Northern blotting and slot blotting techniques.

  14. Ebola virus infection induces irregular dendritic cell gene expression.

    Science.gov (United States)

    Melanson, Vanessa R; Kalina, Warren V; Williams, Priscilla

    2015-02-01

    Filoviruses subvert the human immune system in part by infecting and replicating in dendritic cells (DCs). Using gene arrays, a phenotypic profile of filovirus infection in human monocyte-derived DCs was assessed. Monocytes from human donors were cultured in GM-CSF and IL-4 and were infected with Ebola virus Kikwit variant for up to 48 h. Extracted DC RNA was analyzed on SuperArray's Dendritic and Antigen Presenting Cell Oligo GEArray and compared to uninfected controls. Infected DCs exhibited increased expression of cytokine, chemokine, antiviral, and anti-apoptotic genes not seen in uninfected controls. Significant increases of intracellular antiviral and MHC I and II genes were also noted in EBOV-infected DCs. However, infected DCs failed to show any significant difference in co-stimulatory T-cell gene expression from uninfected DCs. Moreover, several chemokine genes were activated, but there was sparse expression of chemokine receptors that enabled activated DCs to home to lymph nodes. Overall, statistically significant expression of several intracellular antiviral genes was noted, which may limit viral load but fails to stop replication. EBOV gene expression profiling is of vital importance in understanding pathogenesis and devising novel therapeutic treatments such as small-molecule inhibitors.

  15. Population and sex differences in Drosophila melanogaster brain gene expression

    Directory of Open Access Journals (Sweden)

    Catalán Ana

    2012-11-01

    Full Text Available Abstract Background Changes in gene regulation are thought to be crucial for the adaptation of organisms to their environment. Transcriptome analyses can be used to identify candidate genes for ecological adaptation, but can be complicated by variation in gene expression between tissues, sexes, or individuals. Here we use high-throughput RNA sequencing of a single Drosophila melanogaster tissue to detect brain-specific differences in gene expression between the sexes and between two populations, one from the ancestral species range in sub-Saharan Africa and one from the recently colonized species range in Europe. Results Relatively few genes (Cyp6g1 and CHKov1. Conclusions Analysis of the brain transcriptome revealed many genes differing in expression between populations that were not detected in previous studies using whole flies. There was little evidence for sex-specific regulatory adaptation in the brain, as most expression differences between populations were observed in both males and females. The enrichment of genes with sexually dimorphic expression on the X chromosome is consistent with dosage compensation mechanisms affecting sex-biased expression in somatic tissues.

  16. Early signatures of regime shifts in gene expression dynamics

    International Nuclear Information System (INIS)

    Pal, Mainak; Pal, Amit Kumar; Ghosh, Sayantari; Bose, Indrani

    2013-01-01

    Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis. We consider two alternative models, models 1 and 2, of competence development in the bacterial population B. subtilis and determine some early signatures of the regime shifts between competence and noncompetence. We use both deterministic and stochastic formalisms for the purpose of our study. The early signatures studied include the critical slowing down as a transition point is approached, rising variance and the lag-1 autocorrelation function, skewness and a ratio of two mean first passage times. Some of the signatures could provide the experimental basis for distinguishing between bistability and excitability as the correct mechanism for the development of competence. (paper)

  17. Domestication rewired gene expression and nucleotide diversity patterns in tomato.

    Science.gov (United States)

    Sauvage, Christopher; Rau, Andrea; Aichholz, Charlotte; Chadoeuf, Joël; Sarah, Gautier; Ruiz, Manuel; Santoni, Sylvain; Causse, Mathilde; David, Jacques; Glémin, Sylvain

    2017-08-01

    Plant domestication has led to considerable phenotypic modifications from wild species to modern varieties. However, although changes in key traits have been well documented, less is known about the underlying molecular mechanisms, such as the reduction of molecular diversity or global gene co-expression patterns. In this study, we used a combination of gene expression and population genetics in wild and crop tomato to decipher the footprints of domestication. We found a set of 1729 differentially expressed genes (DEG) between the two genetic groups, belonging to 17 clusters of co-expressed DEG, suggesting that domestication affected not only individual genes but also regulatory networks. Five co-expression clusters were enriched in functional terms involving carbohydrate metabolism or epigenetic regulation of gene expression. We detected differences in nucleotide diversity between the crop and wild groups specific to DEG. Our study provides an extensive profiling of the rewiring of gene co-expression induced by the domestication syndrome in one of the main crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  18. Sleep Deprivation Influences Circadian Gene Expression in the Lateral Habenula.

    Science.gov (United States)

    Zhang, Beilin; Gao, Yanxia; Li, Yang; Yang, Jing; Zhao, Hua

    2016-01-01

    Sleep is governed by homeostasis and the circadian clock. Clock genes play an important role in the generation and maintenance of circadian rhythms but are also involved in regulating sleep homeostasis. The lateral habenular nucleus (LHb) has been implicated in sleep-wake regulation, since LHb gene expression demonstrates circadian oscillation characteristics. This study focuses on the participation of LHb clock genes in regulating sleep homeostasis, as the nature of their involvement is unclear. In this study, we observed changes in sleep pattern following sleep deprivation in LHb-lesioned rats using EEG recording techniques. And then the changes of clock gene expression (Per1, Per2, and Bmal1) in the LHb after 6 hours of sleep deprivation were detected by using real-time quantitative PCR (qPCR). We found that sleep deprivation increased the length of Non-Rapid Eye Movement Sleep (NREMS) and decreased wakefulness. LHb-lesioning decreased the amplitude of reduced wake time and increased NREMS following sleep deprivation in rats. qPCR results demonstrated that Per2 expression was elevated after sleep deprivation, while the other two genes were unaffected. Following sleep recovery, Per2 expression was comparable to the control group. This study provides the basis for further research on the role of LHb Per2 gene in the regulation of sleep homeostasis.

  19. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2004-12-31

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

  20. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2006-01-16

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and r