Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments.

Science.gov (United States)

Bi, Ran; Liu, Peng

2016-03-31

RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments. In this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method. Our proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network ( http://cran.r-project.org ).

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

Science.gov (United States)

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Applied analysis and differential equations

CERN Document Server

Cârj, Ovidiu

2007-01-01

This volume contains refereed research articles written by experts in the field of applied analysis, differential equations and related topics. Well-known leading mathematicians worldwide and prominent young scientists cover a diverse range of topics, including the most exciting recent developments. A broad range of topics of recent interest are treated: existence, uniqueness, viability, asymptotic stability, viscosity solutions, controllability and numerical analysis for ODE, PDE and stochastic equations. The scope of the book is wide, ranging from pure mathematics to various applied fields such as classical mechanics, biomedicine, and population dynamics.

Social network analysis applied to team sports analysis

CERN Document Server

Clemente, Filipe Manuel; Mendes, Rui Sousa

2016-01-01

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

Science.gov (United States)

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed

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

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

Applied survival analysis using R

CERN Document Server

Moore, Dirk F

2016-01-01

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics...

Applied regression analysis a research tool

CERN Document Server

Pantula, Sastry; Dickey, David

1998-01-01

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

Science.gov (United States)

Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

2017-08-15

Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

Science.gov (United States)

Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Conversation Analysis in Applied Linguistics

DEFF Research Database (Denmark)

Kasper, Gabriele; Wagner, Johannes

2014-01-01

on applied CA, the application of basic CA's principles, methods, and findings to the study of social domains and practices that are interactionally constituted. We consider three strands—foundational, social problem oriented, and institutional applied CA—before turning to recent developments in CA research...... on learning and development. In conclusion, we address some emerging themes in the relationship of CA and applied linguistics, including the role of multilingualism, standard social science methods as research objects, CA's potential for direct social intervention, and increasing efforts to complement CA......For the last decade, conversation analysis (CA) has increasingly contributed to several established fields in applied linguistics. In this article, we will discuss its methodological contributions. The article distinguishes between basic and applied CA. Basic CA is a sociological endeavor concerned...

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

Science.gov (United States)

Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Serial analysis of gene expression (SAGE) in rat liver regeneration

International Nuclear Information System (INIS)

Cimica, Velasco; Batusic, Danko; Haralanova-Ilieva, Borislava; Chen, Yonglong; Hollemann, Thomas; Pieler, Tomas; Ramadori, Giuliano

2007-01-01

We have applied serial analysis of gene expression for studying the molecular mechanism of the rat liver regeneration in the model of 70% partial hepatectomy. We generated three SAGE libraries from a normal control liver (NL library: 52,343 tags), from a sham control operated liver (Sham library: 51,028 tags), and from a regenerating liver (PH library: 53,061 tags). By SAGE bioinformatics analysis we identified 40 induced genes and 20 repressed genes during the liver regeneration. We verified temporal expression of such genes by real time PCR during the regeneration process and we characterized 13 induced genes and 3 repressed genes. We found connective tissue growth factor transcript and protein induced very early at 4 h after PH operation before hepatocytes proliferation is triggered. Our study suggests CTGF as a growth factor signaling mediator that could be involved directly in the mechanism of liver regeneration induction

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

Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

Science.gov (United States)

Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

2016-01-01

Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

Concept analysis of culture applied to nursing.

Science.gov (United States)

Marzilli, Colleen

2014-01-01

Culture is an important concept, especially when applied to nursing. A concept analysis of culture is essential to understanding the meaning of the word. This article applies Rodgers' (2000) concept analysis template and provides a definition of the word culture as it applies to nursing practice. This article supplies examples of the concept of culture to aid the reader in understanding its application to nursing and includes a case study demonstrating components of culture that must be respected and included when providing health care.

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.

Moving Forward: Positive Behavior Support and Applied Behavior Analysis

Science.gov (United States)

Tincani, Matt

2007-01-01

A controversy has emerged about the relationship between positive behavior support and applied behavior analysis. Some behavior analysts suggest that positive behavior support and applied behavior analysis are the same (e.g., Carr & Sidener, 2002). Others argue that positive behavior support is harmful to applied behavior analysis (e.g., Johnston,…

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

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

Effects of in ovo electroporation on endogenous gene expression: genome-wide analysis

Directory of Open Access Journals (Sweden)

Chambers David

2011-04-01

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Directory of Open Access Journals (Sweden)

Gabriela D A Guardia

Full Text Available Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Science.gov (United States)

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

PCR Expression Analysis Of the Estrogeninducible Gene Bcei in Gastrointestinal and Other Human Tumors

Directory of Open Access Journals (Sweden)

Iris Wundrack

1994-01-01

Full Text Available A polymerase chain reaction (PCR assay was developed to test for tumor cell specific expression of the BCEI gene. This new marker gene, reported at first for human breast cancer, was found specifically active in various gastrointestinal carcinomas by previously applying immunohistochemistry and RNA (Northern blot analysis. Presently, by using reverse transcription -PCR analysis, a series of primary tumor tissues and established tumor cell lines were testcd for BCEI transcription. This approach was compared to immunostaining achieved by an antibody directed against the BCEI gene’s product. The result demonstrate the superior sensitivity of PCR by indicating the gene’ s expression in cases where immunohistochemical testing remained negative.

A Study of Applied Strategies in Translating Idiomatic Expressions in Two Movie Subtitles: Bring It On & Mean Girls

Directory of Open Access Journals (Sweden)

Mahmood Hashemian

2017-10-01

Full Text Available Idiomatic expressions are considered as a part of everyday language. In other words, they are the essence of each language and one of the most problematic parts to cope with, especially in the process of interlingual translation. Furthermore, there is sometimes no one-to-one equivalent for the idioms of the source language (SL in the target language (TL. This study aimed at investigating the applied strategies in the translation of idiomatic expressions in 2 American subtitled movies, namely Mean Girls (2004 and Bring It On! (2009, through using Baker’s (1992 proposed procedures in translating idiomatic expressions in translation studies. To this aim, the idiomatic expressions were extracted from the original versions of the movies and compared with the subtitled translations in Persian. Analysis of the relevant data indicated that the chi-square results were not significant at χ2 (3, N = 2 = 1.188, p = 0, considering p ˂ 0.05. Therefore, Baker’s (1992 strategies were not distributed equally between these two movies. Moreover, the “omission” strategy with the frequency of 40 was the topmost used strategy in these movies.

Simplified inelastic analysis methods applied to fast breeder reactor core design

International Nuclear Information System (INIS)

Abo-El-Ata, M.M.

1978-01-01

The paper starts with a review of some currently available simplified inelastic analysis methods used in elevated temperature design for evaluating plastic and thermal creep strains. The primary purpose of the paper is to investigate how these simplified methods may be applied to fast breeder reactor core design where neutron irradiation effects are significant. One of the problems discussed is irradiation-induced creep and its effect on shakedown, ratcheting, and plastic cycling. Another problem is the development of swelling-induced stress which is an additional loading mechanism and must be taken into account. In this respect an expression for swelling-induced stress in the presence of irradiation creep is derived and a model for simplifying the stress analysis under these conditions is proposed. As an example, the effects of irradiation creep and swelling induced stress on the analysis of a thin walled tube under constant internal pressure and intermittent heat fluxes, simulating a fuel pin, is presented

Matrix suites applying when making the commercial-company-activity-andfinancial-risks-express-diagnostics

Directory of Open Access Journals (Sweden)

Valentina Petrovn Neganova

2011-09-01

Full Text Available This paper describes an original technique and peculiarities of its use for the express diagnostics of a company and analysis of financial risks. The feature of this technique is potential Russian reality accountance of optimizational transformations of statements in order to minimize taxation and refract the information field of a business system for the apperception. It is based on the conceptual principle of studies of the University of Ghent, according to which, these three cycles affect stability of the companies to the important risk - the risk of bankruptcy. It is noted that the use of matrix analysis can become an additional powerful tool for solving the conceptual verification problem of financial permanence of business systems operation in the marketplace because it allows to determine the internal nature of the underlying processes that occur within an atomic business system and to make every effort to minimize potential and actual manifestations of instability of the external and internal environment of the business system. This method satisfies the multiple set of conditions-equations: apperceptive, asymptotic and simplificational functions that form the basis of calculations for model creation. The technique can be applied by commercial banks in the analysis of the elements of their loan portfolio. Application of this technique allows analyzing the performance of a commercial company in the features of Russian life with minimal iterations.

Analysis of differences between Western and East-Asian faces based on facial region segmentation and PCA for facial expression recognition

Science.gov (United States)

Benitez-Garcia, Gibran; Nakamura, Tomoaki; Kaneko, Masahide

2017-01-01

Darwin was the first one to assert that facial expressions are innate and universal, which are recognized across all cultures. However, recent some cross-cultural studies have questioned this assumed universality. Therefore, this paper presents an analysis of the differences between Western and East-Asian faces of the six basic expressions (anger, disgust, fear, happiness, sadness and surprise) focused on three individual facial regions of eyes-eyebrows, nose and mouth. The analysis is conducted by applying PCA for two feature extraction methods: appearance-based by using the pixel intensities of facial parts, and geometric-based by handling 125 feature points from the face. Both methods are evaluated using 4 standard databases for both racial groups and the results are compared with a cross-cultural human study applied to 20 participants. Our analysis reveals that differences between Westerns and East-Asians exist mainly on the regions of eyes-eyebrows and mouth for expressions of fear and disgust respectively. This work presents important findings for a better design of automatic facial expression recognition systems based on the difference between two racial groups.

An information-theoretic machine learning approach to expression QTL analysis.

Directory of Open Access Journals (Sweden)

Tao Huang

Full Text Available Expression Quantitative Trait Locus (eQTL analysis is a powerful tool to study the biological mechanisms linking the genotype with gene expression. Such analyses can identify genomic locations where genotypic variants influence the expression of genes, both in close proximity to the variant (cis-eQTL, and on other chromosomes (trans-eQTL. Many traditional eQTL methods are based on a linear regression model. In this study, we propose a novel method by which to identify eQTL associations with information theory and machine learning approaches. Mutual Information (MI is used to describe the association between genetic marker and gene expression. MI can detect both linear and non-linear associations. What's more, it can capture the heterogeneity of the population. Advanced feature selection methods, Maximum Relevance Minimum Redundancy (mRMR and Incremental Feature Selection (IFS, were applied to optimize the selection of the affected genes by the genetic marker. When we applied our method to a study of apoE-deficient mice, it was found that the cis-acting eQTLs are stronger than trans-acting eQTLs but there are more trans-acting eQTLs than cis-acting eQTLs. We compared our results (mRMR.eQTL with R/qtl, and MatrixEQTL (modelLINEAR and modelANOVA. In female mice, 67.9% of mRMR.eQTL results can be confirmed by at least two other methods while only 14.4% of R/qtl result can be confirmed by at least two other methods. In male mice, 74.1% of mRMR.eQTL results can be confirmed by at least two other methods while only 18.2% of R/qtl result can be confirmed by at least two other methods. Our methods provide a new way to identify the association between genetic markers and gene expression. Our software is available from supporting information.

Asians' Facial Responsiveness to Basic Tastes by Automated Facial Expression Analysis System.

Science.gov (United States)

Zhi, Ruicong; Cao, Lianyu; Cao, Gang

2017-03-01

Growing evidence shows that consumer choices in real life are mostly driven by unconscious mechanisms rather than conscious. The unconscious process could be measured by behavioral measurements. This study aims to apply automatic facial expression analysis technique for consumers' emotion representation, and explore the relationships between sensory perception and facial responses. Basic taste solutions (sourness, sweetness, bitterness, umami, and saltiness) with 6 levels plus water were used, which could cover most of the tastes found in food and drink. The other contribution of this study is to analyze the characteristics of facial expressions and correlation between facial expressions and perceptive hedonic liking for Asian consumers. Up until now, the facial expression application researches only reported for western consumers, while few related researches investigated the facial responses during food consuming for Asian consumers. Experimental results indicated that facial expressions could identify different stimuli with various concentrations and different hedonic levels. The perceived liking increased at lower concentrations and decreased at higher concentrations, while samples with medium concentrations were perceived as the most pleasant except sweetness and bitterness. High correlations were founded between perceived intensities of bitterness, umami, saltiness, and facial reactions of disgust and fear. Facial expression disgust and anger could characterize emotion "dislike," and happiness could characterize emotion "like," while neutral could represent "neither like nor dislike." The identified facial expressions agree with the perceived sensory emotions elicited by basic taste solutions. The correlation analysis between hedonic levels and facial expression intensities obtained in this study are in accordance with that discussed for western consumers. © 2017 Institute of Food Technologists®.

Building an applied activation analysis centre

International Nuclear Information System (INIS)

Bartosek, J.; Kasparec, I.; Masek, J.

1972-01-01

Requirements are defined and all available background material is reported and discussed for the building up of a centre of applied activation analysis in Czechoslovakia. A detailed analysis of potential users and the centre's envisaged availability is also presented as part of the submitted study. A brief economic analysis is annexed. The study covers the situation up to the end of 1972. (J.K.)

DATE analysis: A general theory of biological change applied to microarray data.

Science.gov (United States)

Rasnick, David

2009-01-01

In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

Caldwell University's Department of Applied Behavior Analysis.

Science.gov (United States)

Reeve, Kenneth F; Reeve, Sharon A

2016-05-01

Since 2004, faculty members at Caldwell University have developed three successful graduate programs in Applied Behavior Analysis (i.e., PhD, MA, non-degree programs), increased program faculty from two to six members, developed and operated an on-campus autism center, and begun a stand-alone Applied Behavior Analysis Department. This paper outlines a number of strategies used to advance these initiatives, including those associated with an extensive public relations campaign. We also outline challenges that have limited our programs' growth. These strategies, along with a consideration of potential challenges, might prove useful in guiding academicians who are interested in starting their own programs in behavior analysis.

Spectral Analysis on Time-Course Expression Data: Detecting Periodic Genes Using a Real-Valued Iterative Adaptive Approach

Directory of Open Access Journals (Sweden)

Kwadwo S. Agyepong

2013-01-01

Full Text Available Time-course expression profiles and methods for spectrum analysis have been applied for detecting transcriptional periodicities, which are valuable patterns to unravel genes associated with cell cycle and circadian rhythm regulation. However, most of the proposed methods suffer from restrictions and large false positives to a certain extent. Additionally, in some experiments, arbitrarily irregular sampling times as well as the presence of high noise and small sample sizes make accurate detection a challenging task. A novel scheme for detecting periodicities in time-course expression data is proposed, in which a real-valued iterative adaptive approach (RIAA, originally proposed for signal processing, is applied for periodogram estimation. The inferred spectrum is then analyzed using Fisher’s hypothesis test. With a proper -value threshold, periodic genes can be detected. A periodic signal, two nonperiodic signals, and four sampling strategies were considered in the simulations, including both bursts and drops. In addition, two yeast real datasets were applied for validation. The simulations and real data analysis reveal that RIAA can perform competitively with the existing algorithms. The advantage of RIAA is manifested when the expression data are highly irregularly sampled, and when the number of cycles covered by the sampling time points is very reduced.

Analysis of the interaction between experimental and applied behavior analysis.

Science.gov (United States)

Virues-Ortega, Javier; Hurtado-Parrado, Camilo; Cox, Alison D; Pear, Joseph J

2014-01-01

To study the influences between basic and applied research in behavior analysis, we analyzed the coauthorship interactions of authors who published in JABA and JEAB from 1980 to 2010. We paid particular attention to authors who published in both JABA and JEAB (dual authors) as potential agents of cross-field interactions. We present a comprehensive analysis of dual authors' coauthorship interactions using social networks methodology and key word analysis. The number of dual authors more than doubled (26 to 67) and their productivity tripled (7% to 26% of JABA and JEAB articles) between 1980 and 2010. Dual authors stood out in terms of number of collaborators, number of publications, and ability to interact with multiple groups within the field. The steady increase in JEAB and JABA interactions through coauthors and the increasing range of topics covered by dual authors provide a basis for optimism regarding the progressive integration of basic and applied behavior analysis. © Society for the Experimental Analysis of Behavior.

The Roles of Age and Gender in Applying Proverbs and Expressions in Daily Conversations of Shirazians

Directory of Open Access Journals (Sweden)

Mohammad Saber Khaghaninejad

2017-01-01

Full Text Available Change and transformation are the basic characteristics of languages. Each community incorporates different generations with different ideologies toward life and obviously use different dialects. The difference in dialects among different generations in Iran is so drastic that it seems people speak different languages. This research has attempted to study the amount of applying proverbs and expressions in different age-groups of the society. Therefore, two groups of 24 respondents were randomly selected from both male and female as the statistical population so that investigating age and sex factors in the type and amount of applying proverbs and expressions in the daily conversations become possible. All participants were interviewed individually and their sentences were transcribed accurately. By counting the number of proverbs and expressions in the sentences of Middle-aged and teenager groups, and also by counting the male and female participants, and considering their Expression Density; i.e., the proportion of the number of proverbs and expressions to the total number of the words of each sentence, and by using the method of inferential non-parametric statistics, these results have been achieved: 1.The Middle-aged Group use more proverbs and expressions than teenagers. Perhaps, because they are more familiar with the culture and literature, and they are much more aware of the delicacies of language and literature. 2.Teenagers also use proverbs and expressions; however, these are of the type of words which were inserted suddenly into the lexicon of the society through printed matters or media and cyber networks. 3.Moreover, men totally use more proverbs and expressions than women in their daily conversations.

dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder.

Science.gov (United States)

Zhang, Shuyun; Deng, Libin; Jia, Qiyue; Huang, Shaoting; Gu, Junwang; Zhou, Fankun; Gao, Meng; Sun, Xinyi; Feng, Chang; Fan, Guangqin

2017-11-16

Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders.

Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

Directory of Open Access Journals (Sweden)

Hagedorn Peter H

2011-02-01

Full Text Available Abstract Background Several approaches have been developed for miRNA target prediction, including methods that incorporate expression profiling. However the methods are still in need of improvements due to a high false discovery rate. So far, none of the methods have used independent component analysis (ICA. Here, we developed a novel target prediction method based on ICA that incorporates both seed matching and expression profiling of miRNA and mRNA expressions. The method was applied on a cellular model of type 1 diabetes. Results Microrray profiling identified eight miRNAs (miR-124/128/192/194/204/375/672/708 with differential expression. Applying ICA on the mRNA profiling data revealed five significant independent components (ICs correlating to the experimental conditions. The five ICs also captured the miRNA expressions by explaining >97% of their variance. By using ICA, seven of the eight miRNAs showed significant enrichment of sequence predicted targets, compared to only four miRNAs when using simple negative correlation. The ICs were enriched for miRNA targets that function in diabetes-relevant pathways e.g. type 1 and type 2 diabetes and maturity onset diabetes of the young (MODY. Conclusions In this study, ICA was applied as an attempt to separate the various factors that influence the mRNA expression in order to identify miRNA targets. The results suggest that ICA is better at identifying miRNA targets than negative correlation. Additionally, combining ICA and pathway analysis constitutes a means for prioritizing between the predicted miRNA targets. Applying the method on a model of type 1 diabetes resulted in identification of eight miRNAs that appear to affect pathways of relevance to disease mechanisms in diabetes.

Analysis of Facial Expression by Taste Stimulation

Science.gov (United States)

Tobitani, Kensuke; Kato, Kunihito; Yamamoto, Kazuhiko

In this study, we focused on the basic taste stimulation for the analysis of real facial expressions. We considered that the expressions caused by taste stimulation were unaffected by individuality or emotion, that is, such expressions were involuntary. We analyzed the movement of facial muscles by taste stimulation and compared real expressions with artificial expressions. From the result, we identified an obvious difference between real and artificial expressions. Thus, our method would be a new approach for facial expression recognition.

Applied Behavior Analysis and Statistical Process Control?

Science.gov (United States)

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

mESAdb: microRNA expression and sequence analysis database.

Science.gov (United States)

Kaya, Koray D; Karakülah, Gökhan; Yakicier, Cengiz M; Acar, Aybar C; Konu, Ozlen

2011-01-01

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

Applied multivariate statistical analysis

CERN Document Server

Härdle, Wolfgang Karl

2015-01-01

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

Automatic emotional expression analysis from eye area

Science.gov (United States)

Akkoç, Betül; Arslan, Ahmet

2015-02-01

Eyes play an important role in expressing emotions in nonverbal communication. In the present study, emotional expression classification was performed based on the features that were automatically extracted from the eye area. Fırst, the face area and the eye area were automatically extracted from the captured image. Afterwards, the parameters to be used for the analysis through discrete wavelet transformation were obtained from the eye area. Using these parameters, emotional expression analysis was performed through artificial intelligence techniques. As the result of the experimental studies, 6 universal emotions consisting of expressions of happiness, sadness, surprise, disgust, anger and fear were classified at a success rate of 84% using artificial neural networks.

Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration

Directory of Open Access Journals (Sweden)

Kelemen Arpad

2008-08-01

Full Text Available Abstract Background This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascades to therapeutic doses in multiple tissues such as liver, skeletal muscle, and kidney from the same animals. Affymetrix time course gene expression data U34A are obtained from three different tissues including kidney, liver and muscle. Our goal is not only to find the concordance of gene in different tissues, identify the common differentially expressed genes over time and also examine the reproducibility of the findings by integrating the results through meta analysis from multiple tissues in order to gain a significant increase in the power of detecting differentially expressed genes over time and to find the differential differences of three tissues responding to the drug. Results and conclusion Bayesian categorical model for estimating the proportion of the 'call' are used for pre-screening genes. Hierarchical Bayesian Mixture Model is further developed for the identifications of differentially expressed genes across time and dynamic clusters. Deviance information criterion is applied to determine the number of components for model comparisons and selections. Bayesian mixture model produces the gene-specific posterior probability of differential/non-differential expression and the 95% credible interval, which is the basis for our further Bayesian meta-inference. Meta-analysis is performed in order to identify commonly expressed genes from multiple tissues that may serve as ideal targets for novel treatment strategies and to integrate the results across separate studies. We have found the common expressed genes in the three tissues. However, the up/down/no regulations of these common genes are different at different time points. Moreover, the most differentially expressed genes were found in the liver, then in kidney, and then in muscle.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

Science.gov (United States)

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological

Lessons learned in applying function analysis

International Nuclear Information System (INIS)

Mitchel, G.R.; Davey, E.; Basso, R.

2001-01-01

This paper summarizes the lessons learned in undertaking and applying function analysis based on the recent experience of utility, AECL and international design and assessment projects. Function analysis is an analytical technique that can be used to characterize and asses the functions of a system and is widely recognized as an essential component of a 'systematic' approach to design, on that integrated operational and user requirements into the standard design process. (author)

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

Directory of Open Access Journals (Sweden)

Borlawsky Tara B

2010-10-01

Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

Applying homotopy analysis method for solving differential-difference equation

International Nuclear Information System (INIS)

Wang Zhen; Zou Li; Zhang Hongqing

2007-01-01

In this Letter, we apply the homotopy analysis method to solving the differential-difference equations. A simple but typical example is applied to illustrate the validity and the great potential of the generalized homotopy analysis method in solving differential-difference equation. Comparisons are made between the results of the proposed method and exact solutions. The results show that the homotopy analysis method is an attractive method in solving the differential-difference equations

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

Science.gov (United States)

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Identification and validation of Asteraceae miRNAs by the expressed sequence tag analysis.

Science.gov (United States)

Monavar Feshani, Aboozar; Mohammadi, Saeed; Frazier, Taylor P; Abbasi, Abbas; Abedini, Raha; Karimi Farsad, Laleh; Ehya, Farveh; Salekdeh, Ghasem Hosseini; Mardi, Mohsen

2012-02-10

MicroRNAs (miRNAs) are small non-coding RNA molecules that play a vital role in the regulation of gene expression. Despite their identification in hundreds of plant species, few miRNAs have been identified in the Asteraceae, a large family that comprises approximately one tenth of all flowering plants. In this study, we used the expressed sequence tag (EST) analysis to identify potential conserved miRNAs and their putative target genes in the Asteraceae. We applied quantitative Real-Time PCR (qRT-PCR) to confirm the expression of eight potential miRNAs in Carthamus tinctorius and Helianthus annuus. We also performed qRT-PCR analysis to investigate the differential expression pattern of five newly identified miRNAs during five different cotyledon growth stages in safflower. Using these methods, we successfully identified and characterized 151 potentially conserved miRNAs, belonging to 26 miRNA families, in 11 genus of Asteraceae. EST analysis predicted that the newly identified conserved Asteraceae miRNAs target 130 total protein-coding ESTs in sunflower and safflower, as well as 433 additional target genes in other plant species. We experimentally confirmed the existence of seven predicted miRNAs, (miR156, miR159, miR160, miR162, miR166, miR396, and miR398) in safflower and sunflower seedlings. We also observed that five out of eight miRNAs are differentially expressed during cotyledon development. Our results indicate that miRNAs may be involved in the regulation of gene expression during seed germination and the formation of the cotyledons in the Asteraceae. The findings of this study might ultimately help in the understanding of miRNA-mediated gene regulation in important crop species. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

International Nuclear Information System (INIS)

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

Spatial gene expression quantification: a tool for analysis of in situ hybridizations in sea anemone Nematostella vectensis

Directory of Open Access Journals (Sweden)

Botman Daniel

2012-10-01

Full Text Available Abstract Background Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly Drosophila melanogaster is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom. In the sea anemone Nematostella vectensis the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. Nematostella is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques. Findings Our new quantification method produces standardized gene expression profiles from raw or annotated Nematostella in situ hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation. Conclusions We created a standard format for gene expression data, which enables quantitative analysis of in situ hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar Nematostella morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.

Gene expression analysis to identify molecular correlates of pre- and post-conditioning derived neuroprotection.

Science.gov (United States)

Prasad, Shiv S; Russell, Marsha; Nowakowska, Margeryta; Williams, Andrew; Yauk, Carole

2012-06-01

Mild ischaemic exposures before or after severe injurious ischaemia that elicit neuroprotective responses are referred to as preconditioning and post-conditioning. The corresponding molecular mechanisms of neuroprotection are not completely understood. Identification of the genes and associated pathways of corresponding neuroprotection would provide insight into neuronal survival, potential therapeutic approaches and assessments of therapies for stroke. The objectives of this study were to use global gene expression approach to infer the molecular mechanisms in pre- and post-conditioning-derived neuroprotection in cortical neurons following oxygen and glucose deprivation (OGD) in vitro and then to apply these findings to predict corresponding functional pathways. To this end, microarray analysis was applied to rat cortical neurons with or without the pre- and post-conditioning treatments at 3-h post-reperfusion, and differentially expressed transcripts were subjected to statistical, hierarchical clustering and pathway analyses. The expression patterns of 3,431 genes altered under all conditions of ischaemia (with and without pre- or post-conditioning). We identified 1,595 genes that were commonly regulated within both the pre- and post-conditioning treatments. Cluster analysis revealed that transcription profiles clustered tightly within controls, non-conditioned OGD and neuroprotected groups. Two clusters defining neuroprotective conditions associated with up- and downregulated genes were evident. The five most upregulated genes within the neuroprotective clusters were Tagln, Nes, Ptrf, Vim and Adamts9, and the five most downregulated genes were Slc7a3, Bex1, Brunol4, Nrxn3 and Cpne4. Pathway analysis revealed that the intracellular and second messenger signalling pathways in addition to cell death were predominantly associated with downregulated pre- and post-conditioning associated genes, suggesting that modulation of cell death and signal transduction pathways

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

Directory of Open Access Journals (Sweden)

María Ballester

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

Energy Technology Data Exchange (ETDEWEB)

Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

2013-10-01

The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol and saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.

Prognostic value of stromal decorin expression in patients with breast cancer: a meta-analysis.

Science.gov (United States)

Li, Shuang-Jiang; Chen, Da-Li; Zhang, Wen-Biao; Shen, Cheng; Che, Guo-Wei

2015-11-01

Numbers of studies have investigated the biological functions of decorin (DCN) in oncogenesis, tumor progression, angiogenesis and metastasis. Although many of them aim to highlight the prognostic value of stromal DCN expression in breast cancer, some controversial results still exist and a consensus has not been reached until now. Therefore, our meta-analysis aims to determine the prognostic significance of stromal DCN expression in breast cancer patients. PubMed, EMBASE, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for full-text literatures met out inclusion criteria. We applied the hazard ratio (HR) with 95% confidence interval (CI) as the appropriate summarized statistics. Q-test and I(2) statistic were employed to estimate the level of heterogeneity across the included studies. Sensitivity analysis was conducted to further identify the possible origins of heterogeneity. The publication bias was detected by Begg's test and Egger's test. There were three English literatures (involving 6 studies) included into our meta-analysis. On the one hand, both the summarized outcomes based on univariate analysis (HR: 0.513; 95% CI: 0.406-0.648; Panalysis (HR: 0.544; 95% CI: 0.388-0.763; Panalysis (HR: 0.504; 95% CI: 0.389-0.651; Panalysis (HR: 0.568; 95% CI: 0.400-0.806; P=0.002) also indicated that stromal DCN expression was positively associated with high disease-free survival (DFS) of breast cancer patients. No significant heterogeneity or publication bias was observed within this meta-analysis. The present evidences indicate that high stromal DCN expression can significantly predict the good prognosis in patients with breast cancer. The discoveries from our meta-analysis have better be confirmed in the updated review pooling more relevant investigations in the future.

cDNA-SRAP and Its Application in Differential Gene Expression Analysis: A Case Study in Erianthus arundinaceum

Directory of Open Access Journals (Sweden)

Youxiong Que

2012-01-01

Full Text Available Erianthus arundinaceum is a wild relative species of sugarcane. The aim of this research was to demonstrate the feasibility of cDNA-SRAP for differential gene expression and to explore the molecular mechanism of drought resistance in E. arundinaceum. cDNA-SRAP technique, for the first time, was applied in the analysis of differential gene expression in E. arundinaceum under drought stress. In total, eight differentially expressed genes with length of 185–427 bp were successfully isolated (GenBank Accession numbers: EU071770, EU071772, EU071774, EU071776, EU071777, EU071779, EU071780, and EU071781. Based on their homologies with genes in GenBank, these genes were assumed to encode ribonuclease III, vacuolar protein, ethylene insensitive protein, aerobactin biosynthesis protein, photosystem II protein, glucose transporter, leucine-rich repeat protein, and ammonia monooxygenase. Real-time PCR analysis on the expression profiling of gene (EU071774 encoding ethylene-insensitive protein and gene (EU071781 encoding ammonia monooxygenase revealed that the expression of these two genes was upregulated both by PEG and ABA treatments, suggesting that they may involve in the drought resistance of E. arundinaceum. This study constitutes the first report of genes activated in E. arundinaceum by drought stress and opens up the application of cDNA-SRAP in differential gene expression analysis in E. arundinaceum under certain stress conditions.

New trends in applied harmonic analysis sparse representations, compressed sensing, and multifractal analysis

CERN Document Server

Cabrelli, Carlos; Jaffard, Stephane; Molter, Ursula

2016-01-01

This volume is a selection of written notes corresponding to courses taught at the CIMPA School: "New Trends in Applied Harmonic Analysis: Sparse Representations, Compressed Sensing and Multifractal Analysis". New interactions between harmonic analysis and signal and image processing have seen striking development in the last 10 years, and several technological deadlocks have been solved through the resolution of deep theoretical problems in harmonic analysis. New Trends in Applied Harmonic Analysis focuses on two particularly active areas that are representative of such advances: multifractal analysis, and sparse representation and compressed sensing. The contributions are written by leaders in these areas, and covers both theoretical aspects and applications. This work should prove useful not only to PhD students and postdocs in mathematics and signal and image processing, but also to researchers working in related topics.

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

Science.gov (United States)

Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

Problems of Understanding English Ironic Expressions by M.A. Students of Applied Linguistics at Mu'tah University in Jordan

Science.gov (United States)

Al Khawaldeh, Suhaib

2015-01-01

The present study attempts to investigate the problems of understanding English ironic expressions M.A. of Applied Linguistics students at Mu'tah University in Jordan. This quantitative and qualitative study includes 15 of M.A. students of Applied Linguistics at Mu'tah University. The participants were selected randomly. Two research instruments…

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.

Applied research of environmental monitoring using instrumental neutron activation analysis

Energy Technology Data Exchange (ETDEWEB)

Chung, Young Sam; Moon, Jong Hwa; Chung, Young Ju

1997-08-01

This technical report is written as a guide book for applied research of environmental monitoring using Instrumental Neutron Activation Analysis. The contents are as followings; sampling and sample preparation as a airborne particulate matter, analytical methodologies, data evaluation and interpretation, basic statistical methods of data analysis applied in environmental pollution studies. (author). 23 refs., 7 tabs., 9 figs.

The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

DEFF Research Database (Denmark)

Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

2006-01-01

be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

Science.gov (United States)

Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

2013-01-01

While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

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

Genome-wide expression analysis of salt-stressed diploid and autotetraploid Paulownia tomentosa.

Directory of Open Access Journals (Sweden)

Zhenli Zhao

Full Text Available Paulownia tomentosa is a fast-growing tree species with multiple uses. It is grown worldwide, but is native to China, where it is widely cultivated in saline regions. We previously confirmed that autotetraploid P. tomentosa plants are more stress-tolerant than the diploid plants. However, the molecular mechanism underlying P. tomentosa salinity tolerance has not been fully characterized. Using the complete Paulownia fortunei genome as a reference, we applied next-generation RNA-sequencing technology to analyze the effects of salt stress on diploid and autotetraploid P. tomentosa plants. We generated 175 million clean reads and identified 15,873 differentially expressed genes (DEGs from four P. tomentosa libraries (two diploid and two autotetraploid. Functional annotations of the differentially expressed genes using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases revealed that plant hormone signal transduction and photosynthetic activities are vital for plant responses to high-salt conditions. We also identified several transcription factors, including members of the AP2/EREBP, bHLH, MYB, and NAC families. Quantitative real-time PCR analysis validated the expression patterns of eight differentially expressed genes. Our findings and the generated transcriptome data may help to accelerate the genetic improvement of cultivated P. tomentosa and other plant species for enhanced growth in saline soils.

The Significance of Regional Analysis in Applied Geography.

Science.gov (United States)

Sommers, Lawrence M.

Regional analysis is central to applied geographic research, contributing to better planning and policy development for a variety of societal problems facing the United States. The development of energy policy serves as an illustration of the capabilities of this type of analysis. The United States has had little success in formulating a national…

Shaped 3D Singular Spectrum Analysis for Quantifying Gene Expression, with Application to the Early Zebrafish Embryo

Directory of Open Access Journals (Sweden)

Alex Shlemov

2015-01-01

Full Text Available Recent progress in microscopy technologies, biological markers, and automated processing methods is making possible the development of gene expression atlases at cellular-level resolution over whole embryos. Raw data on gene expression is usually very noisy. This noise comes from both experimental (technical/methodological and true biological sources (from stochastic biochemical processes. In addition, the cells or nuclei being imaged are irregularly arranged in 3D space. This makes the processing, extraction, and study of expression signals and intrinsic biological noise a serious challenge for 3D data, requiring new computational approaches. Here, we present a new approach for studying gene expression in nuclei located in a thick layer around a spherical surface. The method includes depth equalization on the sphere, flattening, interpolation to a regular grid, pattern extraction by Shaped 3D singular spectrum analysis (SSA, and interpolation back to original nuclear positions. The approach is demonstrated on several examples of gene expression in the zebrafish egg (a model system in vertebrate development. The method is tested on several different data geometries (e.g., nuclear positions and different forms of gene expression patterns. Fully 3D datasets for developmental gene expression are becoming increasingly available; we discuss the prospects of applying 3D-SSA to data processing and analysis in this growing field.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Directory of Open Access Journals (Sweden)

Anna A. Igolkina

2018-06-01

Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

Applied decision analysis and risk evaluation

International Nuclear Information System (INIS)

Ferse, W.; Kruber, S.

1995-01-01

During 1994 the workgroup 'Applied Decision Analysis and Risk Evaluation; continued the work on the knowledge based decision support system XUMA-GEFA for the evaluation of the hazard potential of contaminated sites. Additionally a new research direction was started which aims at the support of a later stage of the treatment of contaminated sites: The clean-up decision. For the support of decisions arising at this stage, the methods of decision analysis will be used. Computational aids for evaluation and decision support were implemented and a case study at a waste disposal site in Saxony which turns out to be a danger for the surrounding groundwater ressource was initiated. (orig.)

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

Science.gov (United States)

Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

Directory of Open Access Journals (Sweden)

Jie Luo

2018-04-01

Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Animal Research in the "Journal of Applied Behavior Analysis"

Science.gov (United States)

Edwards, Timothy L.; Poling, Alan

2011-01-01

This review summarizes the 6 studies with nonhuman animal subjects that have appeared in the "Journal of Applied Behavior Analysis" and offers suggestions for future research in this area. Two of the reviewed articles described translational research in which pigeons were used to illustrate and examine behavioral phenomena of applied significance…

Modern problems in applied analysis

CERN Document Server

Rogosin, Sergei

2018-01-01

This book features a collection of recent findings in Applied Real and Complex Analysis that were presented at the 3rd International Conference “Boundary Value Problems, Functional Equations and Applications” (BAF-3), held in Rzeszow, Poland on 20-23 April 2016. The contributions presented here develop a technique related to the scope of the workshop and touching on the fields of differential and functional equations, complex and real analysis, with a special emphasis on topics related to boundary value problems. Further, the papers discuss various applications of the technique, mainly in solid mechanics (crack propagation, conductivity of composite materials), biomechanics (viscoelastic behavior of the periodontal ligament, modeling of swarms) and fluid dynamics (Stokes and Brinkman type flows, Hele-Shaw type flows). The book is addressed to all readers who are interested in the development and application of innovative research results that can help solve theoretical and real-world problems.

Fourier convergence analysis applied to neutron diffusion Eigenvalue problem

International Nuclear Information System (INIS)

Lee, Hyun Chul; Noh, Jae Man; Joo, Hyung Kook

2004-01-01

Fourier error analysis has been a standard technique for the stability and convergence analysis of linear and nonlinear iterative methods. Though the methods can be applied to Eigenvalue problems too, all the Fourier convergence analyses have been performed only for fixed source problems and a Fourier convergence analysis for Eigenvalue problem has never been reported. Lee et al proposed new 2-D/1-D coupling methods and they showed that the new ones are unconditionally stable while one of the two existing ones is unstable at a small mesh size and that the new ones are better than the existing ones in terms of the convergence rate. In this paper the convergence of method A in reference 4 for the diffusion Eigenvalue problem was analyzed by the Fourier analysis. The Fourier convergence analysis presented in this paper is the first one applied to a neutronics eigenvalue problem to the best of our knowledge

Digital gene expression analysis of corky split vein caused by boron deficiency in 'Newhall' Navel Orange (Citrus sinensis Osbeck for selecting differentially expressed genes related to vascular hypertrophy.

Directory of Open Access Journals (Sweden)

Cheng-Quan Yang

Full Text Available Corky split vein caused by boron (B deficiency in 'Newhall' Navel Orange was studied in the present research. The boron-deficient citrus exhibited a symptom of corky split vein in mature leaves. Morphologic and anatomical surveys at four representative phases of corky split veins showed that the symptom was the result of vascular hypertrophy. Digital gene expression (DGE analysis was performed based on the Illumina HiSeq™ 2000 platform, which was applied to analyze the gene expression profilings of corky split veins at four morphologic phases. Over 5.3 million clean reads per library were successfully mapped to the reference database and more than 22897 mapped genes per library were simultaneously obtained. Analysis of the differentially expressed genes (DEGs revealed that the expressions of genes associated with cytokinin signal transduction, cell division, vascular development, lignin biosynthesis and photosynthesis in corky split veins were all affected. The expressions of WOL and ARR12 involved in the cytokinin signal transduction pathway were up-regulated at 1(st phase of corky split vein development. Furthermore, the expressions of some cell cycle genes, CYCs and CDKB, and vascular development genes, WOX4 and VND7, were up-regulated at the following 2(nd and 3(rd phases. These findings indicated that the cytokinin signal transduction pathway may play a role in initiating symptom observed in our study.

A comparative study of techniques for differential expression analysis on RNA-Seq data.

Directory of Open Access Journals (Sweden)

Zong Hong Zhang

Full Text Available Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

Analysis of Market Opportunities for Chinese Private Express Delivery Industry

Science.gov (United States)

Jiang, Changbing; Bai, Lijun; Tong, Xiaoqing

China's express delivery market has become the arena in which each express enterprise struggles to chase due to the huge potential demand and high profitable prospects. So certain qualitative and quantitative forecast for the future changes of China's express delivery market will help enterprises understand various types of market conditions and social changes in demand and adjust business activities to enhance their competitiveness timely. The development of China's express delivery industry is first introduced in this chapter. Then the theoretical basis of the regression model is overviewed. We also predict the demand trends of China's express delivery market by using Pearson correlation analysis and regression analysis from qualitative and quantitative aspects, respectively. Finally, we draw some conclusions and recommendations for China's express delivery industry.

Animal research in the Journal of Applied Behavior Analysis.

Science.gov (United States)

Edwards, Timothy L; Poling, Alan

2011-01-01

This review summarizes the 6 studies with nonhuman animal subjects that have appeared in the Journal of Applied Behavior Analysis and offers suggestions for future research in this area. Two of the reviewed articles described translational research in which pigeons were used to illustrate and examine behavioral phenomena of applied significance (say-do correspondence and fluency), 3 described interventions that changed animals' behavior (self-injury by a baboon, feces throwing and spitting by a chimpanzee, and unsafe trailer entry by horses) in ways that benefited the animals and the people in charge of them, and 1 described the use of trained rats that performed a service to humans (land-mine detection). We suggest that each of these general research areas merits further attention and that the Journal of Applied Behavior Analysis is an appropriate outlet for some of these publications.

Kolmogorov-Smirnov statistical test for analysis of ZAP-70 expression in B-CLL, compared with quantitative PCR and IgV(H) mutation status.

Science.gov (United States)

Van Bockstaele, Femke; Janssens, Ann; Piette, Anne; Callewaert, Filip; Pede, Valerie; Offner, Fritz; Verhasselt, Bruno; Philippé, Jan

2006-07-15

ZAP-70 has been proposed as a surrogate marker for immunoglobulin heavy-chain variable region (IgV(H)) mutation status, which is known as a prognostic marker in B-cell chronic lymphocytic leukemia (CLL). The flow cytometric analysis of ZAP-70 suffers from difficulties in standardization and interpretation. We applied the Kolmogorov-Smirnov (KS) statistical test to make analysis more straightforward. We examined ZAP-70 expression by flow cytometry in 53 patients with CLL. Analysis was performed as initially described by Crespo et al. (New England J Med 2003; 348:1764-1775) and alternatively by application of the KS statistical test comparing T cells with B cells. Receiver-operating-characteristics (ROC)-curve analyses were performed to determine the optimal cut-off values for ZAP-70 measured by the two approaches. ZAP-70 protein expression was compared with ZAP-70 mRNA expression measured by a quantitative PCR (qPCR) and with the IgV(H) mutation status. Both flow cytometric analyses correlated well with the molecular technique and proved to be of equal value in predicting the IgV(H) mutation status. Applying the KS test is reproducible, simple, straightforward, and overcomes a number of difficulties encountered in the Crespo-method. The KS statistical test is an essential part of the software delivered with modern routine analytical flow cytometers and is well suited for analysis of ZAP-70 expression in CLL. (c) 2006 International Society for Analytical Cytology.

Applied Behavior Analysis: Beyond Discrete Trial Teaching

Science.gov (United States)

Steege, Mark W.; Mace, F. Charles; Perry, Lora; Longenecker, Harold

2007-01-01

We discuss the problem of autism-specific special education programs representing themselves as Applied Behavior Analysis (ABA) programs when the only ABA intervention employed is Discrete Trial Teaching (DTT), and often for limited portions of the school day. Although DTT has many advantages to recommend its use, it is not well suited to teach…

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.

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

Iterated Process Analysis over Lattice-Valued Regular Expressions

DEFF Research Database (Denmark)

Midtgaard, Jan; Nielson, Flemming; Nielson, Hanne Riis

2016-01-01

We present an iterated approach to statically analyze programs of two processes communicating by message passing. Our analysis operates over a domain of lattice-valued regular expressions, and computes increasingly better approximations of each process's communication behavior. Overall the work e...... extends traditional semantics-based program analysis techniques to automatically reason about message passing in a manner that can simultaneously analyze both values of variables as well as message order, message content, and their interdependencies.......We present an iterated approach to statically analyze programs of two processes communicating by message passing. Our analysis operates over a domain of lattice-valued regular expressions, and computes increasingly better approximations of each process's communication behavior. Overall the work...

Positive Behavior Support and Applied Behavior Analysis

Science.gov (United States)

Johnston, J. M.; Foxx, R. M.; Jacobson, J. W.; Green, G.; Mulick, J. A.

2006-01-01

This article reviews the origins and characteristics of the positive behavior support (PBS) movement and examines those features in the context of the field of applied behavior analysis (ABA). We raise a number of concerns about PBS as an approach to delivery of behavioral services and its impact on how ABA is viewed by those in human services. We…

Progressive-Ratio Schedules and Applied Behavior Analysis

Science.gov (United States)

Poling, Alan

2010-01-01

Establishing appropriate relations between the basic and applied areas of behavior analysis has been of long and persistent interest to the author. In this article, the author illustrates that there is a direct relation between how hard an organism will work for access to an object or activity, as indexed by the largest ratio completed under a…

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

Directory of Open Access Journals (Sweden)

Eils Roland

2005-11-01

Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity.

Science.gov (United States)

Chepelev, Nikolai L; Meek, M E Bette; Yauk, Carole Lyn

2014-11-01

Reliable quantification of gene and protein expression has potential to contribute significantly to the characterization of hypothesized modes of action (MOA) or adverse outcome pathways for critical effects of toxicants. Quantitative analysis of gene expression by benchmark dose (BMD) modeling has been facilitated by the development of effective software tools. In contrast, protein expression is still generally quantified by a less robust effect level (no or lowest [adverse] effect levels) approach, which minimizes its potential utility in the consideration of dose-response and temporal concordance for key events in hypothesized MOAs. BMD modeling is applied here to toxicological data on testicular toxicity to investigate its potential utility in analyzing protein expression relevant to the proposed MOA to inform human health risk assessment. The results illustrate how the BMD analysis of protein expression in animal tissues in response to toxicant exposure: (1) complements other toxicity data, and (2) contributes to consideration of the empirical concordance of dose-response relationships, as part of the weight of evidence for hypothesized MOAs to facilitate consideration and application in regulatory risk assessment. Lack of BMD analysis in proteomics has likely limited its use for these purposes. This paper illustrates the added value of BMD modeling to support and strengthen hypothetical MOAs as a basis to facilitate the translation and uptake of the results of proteomic research into risk assessment. Copyright © 2014 Her Majesty the Queen in Right of Canada. Journal of Applied Toxicology © 2014 John Wiley & Sons, Ltd.

Strategic decision analysis applied to borehole seismology

International Nuclear Information System (INIS)

Menke, M.M.; Paulsson, B.N.P.

1994-01-01

Strategic Decision Analysis (SDA) is the evolving body of knowledge on how to achieve high quality in the decision that shapes an organization's future. SDA comprises philosophy, process concepts, methodology, and tools for making good decisions. It specifically incorporates many concepts and tools from economic evaluation and risk analysis. Chevron Petroleum Technology Company (CPTC) has applied SDA to evaluate and prioritize a number of its most important and most uncertain R and D projects, including borehole seismology. Before SDA, there were significant issues and concerns about the value to CPTC of continuing to work on borehole seismology. The SDA process created a cross-functional team of experts to structure and evaluate this project. A credible economic model was developed, discrete risks and continuous uncertainties were assessed, and an extensive sensitivity analysis was performed. The results, even applied to a very restricted drilling program for a few years, were good enough to demonstrate the value of continuing the project. This paper explains the SDA philosophy concepts, and process and demonstrates the methodology and tools using the borehole seismology project example. SDA is useful in the upstream industry not just in the R and D/technology decisions, but also in major exploration and production decisions. Since a major challenge for upstream companies today is to create and realize value, the SDA approach should have a very broad applicability

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

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

Spectral map-analysis: a method to analyze gene expression data

OpenAIRE

Bijnens, Luc J.M.; Lewi, Paul J.; Göhlmann, Hinrich W.; Molenberghs, Geert; Wouters, Luc

2004-01-01

bioinformatics; biplot; correspondence factor analysis; data mining; data visualization; gene expression data; microarray data; multivariate exploratory data analysis; principal component analysis; Spectral map analysis

A practical guide to propensity score analysis for applied clinical research.

Science.gov (United States)

Lee, Jaehoon; Little, Todd D

2017-11-01

Observational studies are often the only viable options in many clinical settings, especially when it is unethical or infeasible to randomly assign participants to different treatment régimes. In such case propensity score (PS) analysis can be applied to accounting for possible selection bias and thereby addressing questions of causal inference. Many PS methods exist, yet few guidelines are available to aid applied researchers in their conduct and evaluation of a PS analysis. In this article we give an overview of available techniques for PS estimation and application, balance diagnostic, treatment effect estimation, and sensitivity assessment, as well as recent advances. We also offer a tutorial that can be used to emulate the steps of PS analysis. Our goal is to provide information that will bring PS analysis within the reach of applied clinical researchers and practitioners. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Weighted gene co-expression network analysis in biomedicine research].

Science.gov (United States)

Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

Interactive analysis of systems biology molecular expression data

Directory of Open Access Journals (Sweden)

Prabhakar Sunil

2008-02-01

Full Text Available Abstract Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. Results Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. Conclusion The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe in growth media (an ionomics dataset. This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.

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.

An Inverse Kinematic Approach Using Groebner Basis Theory Applied to Gait Cycle Analysis

Science.gov (United States)

2013-03-01

AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS Anum Barki AFIT-ENP-13-M-02 DEPARTMENT OF THE AIR...copyright protection in the United States. AFIT-ENP-13-M-02 AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS...APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS Anum Barki, BS Approved: Dr. Ronald F. Tuttle (Chairman) Date Dr. Kimberly Kendricks

Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma

Science.gov (United States)

2013-01-01

Background Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally. Results In this paper, we develop a gene module based method for differential gene expression analysis, named network-based differential gene expression (nDGE) analysis, a one-step integrative process for prioritizing deregulated genes and grouping them into gene modules. We demonstrate that nDGE outperforms existing methods in prioritizing deregulated genes and discovering deregulated gene modules using simulated data sets. When tested on a series of smoker and non-smoker lung adenocarcinoma data sets, we show that top differentially regulated genes identified by the rank sum test in different sets are not consistent while top ranked genes defined by nDGE in different data sets significantly overlap. nDGE results suggest that a differentially regulated gene module, which is enriched for cell cycle related genes and E2F1 targeted genes, plays a role in the molecular differences between smoker and non-smoker lung adenocarcinoma. Conclusions In this paper, we develop nDGE to prioritize

Applied spectrophotometry: analysis of a biochemical mixture.

Science.gov (United States)

Trumbo, Toni A; Schultz, Emeric; Borland, Michael G; Pugh, Michael Eugene

2013-01-01

Spectrophotometric analysis is essential for determining biomolecule concentration of a solution and is employed ubiquitously in biochemistry and molecular biology. The application of the Beer-Lambert-Bouguer Lawis routinely used to determine the concentration of DNA, RNA or protein. There is however a significant difference in determining the concentration of a given species (RNA, DNA, protein) in isolation (a contrived circumstance) as opposed to determining that concentration in the presence of other species (a more realistic situation). To present the student with a more realistic laboratory experience and also to fill a hole that we believe exists in student experience prior to reaching a biochemistry course, we have devised a three week laboratory experience designed so that students learn to: connect laboratory practice with theory, apply the Beer-Lambert-Bougert Law to biochemical analyses, demonstrate the utility and limitations of example quantitative colorimetric assays, demonstrate the utility and limitations of UV analyses for biomolecules, develop strategies for analysis of a solution of unknown biomolecular composition, use digital micropipettors to make accurate and precise measurements, and apply graphing software. Copyright © 2013 Wiley Periodicals, Inc.

Applied Drama and the Higher Education Learning Spaces: A Reflective Analysis

Science.gov (United States)

Moyo, Cletus

2015-01-01

This paper explores Applied Drama as a teaching approach in Higher Education learning spaces. The exploration takes a reflective analysis approach by first examining the impact that Applied Drama has had on my career as a Lecturer/Educator/Teacher working in Higher Education environments. My engagement with Applied Drama practice and theory is…

Molecular cloning and expression analysis of annexin A2 gene in sika deer antler tip

Directory of Open Access Journals (Sweden)

Yanling Xia

2018-04-01

Full Text Available Objective Molecular cloning and bioinformatics analysis of annexin A2 (ANXA2 gene in sika deer antler tip were conducted. The role of ANXA2 gene in the growth and development of the antler were analyzed initially. Methods The reverse transcriptase polymerase chain reaction (RT-PCR was used to clone the cDNA sequence of the ANXA2 gene from antler tip of sika deer (Cervus Nippon hortulorum and the bioinformatics methods were applied to analyze the amino acid sequence of Anxa2 protein. The mRNA expression levels of the ANXA2 gene in different growth stages were examined by real time reverse transcriptase polymerase chain reaction (real time RT-PCR. Results The nucleotide sequence analysis revealed an open reading frame of 1,020 bp encoding 339 amino acids long protein of calculated molecular weight 38.6 kDa and isoelectric point 6.09. Homologous sequence alignment and phylogenetic analysis indicated that the Anxa2 mature protein of sika deer had the closest genetic distance with Cervus elaphus and Bos mutus. Real time RT-PCR results showed that the gene had differential expression levels in different growth stages, and the expression level of the ANXA2 gene was the highest at metaphase (rapid growing period. Conclusion ANXA2 gene may promote the cell proliferation, and the finding suggested Anxa2 as an important candidate for regulating the growth and development of deer antler.

Functional Data Analysis Applied in Chemometrics

DEFF Research Database (Denmark)

Muller, Martha

nutritional status and metabolic phenotype. We want to understand how metabolomic spectra can be analysed using functional data analysis to detect the in uence of dierent factors on specic metabolites. These factors can include, for example, gender, diet culture or dietary intervention. In Paper I we apply...... representation of each spectrum. Subset selection of wavelet coecients generates the input to mixed models. Mixed-model methodology enables us to take the study design into account while modelling covariates. Bootstrap-based inference preserves the correlation structure between curves and enables the estimation...

Super-delta: a new differential gene expression analysis procedure with robust data normalization.

Science.gov (United States)

Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing

2017-12-21

Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super

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.

A novel statistical algorithm for gene expression analysis helps differentiate pregnane X receptor-dependent and independent mechanisms of toxicity.

Directory of Open Access Journals (Sweden)

M Ann Mongan

Full Text Available Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1 We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2 We compared the number of samples satisfying criteria in step 1 between the treated and control groups to estimate the statistical significance based on a null distribution established by sample permutations. The method captures group effect without being too sensitive to anomalies as it allows tolerance for potential non-responders in the treatment group and outliers in the control group. Performance and results of this method were compared with the Significant Analysis of Microarrays (SAM method. These two methods were applied to investigate hepatic transcriptional responses of wild-type (PXR(+/+ and pregnane X receptor-knockout (PXR(-/- mice after 96 h exposure to CMP013, an inhibitor of β-secretase (β-site of amyloid precursor protein cleaving enzyme 1 or BACE1. Our results showed that CMP013 led to transcriptional changes in hallmark PXR-regulated genes and induced a cascade of gene expression changes that explained the hepatomegaly observed only in PXR(+/+ animals. Comparison of concordant expression changes between PXR(+/+ and PXR(-/- mice also suggested a PXR-independent association between CMP013 and perturbations to cellular stress, lipid metabolism, and biliary transport.

Applied Behavior Analysis: Current Myths in Public Education

Science.gov (United States)

Fielding, Cheryl; Lowdermilk, John; Lanier, Lauren L.; Fannin, Abigail G.; Schkade, Jennifer L.; Rose, Chad A.; Simpson, Cynthia G.

2013-01-01

The effective use of behavior management strategies and related policies continues to be a debated issue in public education. Despite overwhelming evidence espousing the benefits of the implementation of procedures derived from principles based on the science of applied behavior analysis (ABA), educators often indicate many common misconceptions…

Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells.

Science.gov (United States)

Wu, Liang; Zhang, Xiaolong; Zhao, Zhikun; Wang, Ling; Li, Bo; Li, Guibo; Dean, Michael; Yu, Qichao; Wang, Yanhui; Lin, Xinxin; Rao, Weijian; Mei, Zhanlong; Li, Yang; Jiang, Runze; Yang, Huan; Li, Fuqiang; Xie, Guoyun; Xu, Liqin; Wu, Kui; Zhang, Jie; Chen, Jianghao; Wang, Ting; Kristiansen, Karsten; Zhang, Xiuqing; Li, Yingrui; Yang, Huanming; Wang, Jian; Hou, Yong; Xu, Xun

2015-01-01

Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

Microarray Study of Pathway Analysis Expression Profile Associated with MicroRNA-29a with Regard to Murine Cholestatic Liver Injuries

Directory of Open Access Journals (Sweden)

Sung-Chou Li

2016-03-01

Full Text Available Accumulating evidence demonstrates that microRNA-29 (miR-29 expression is prominently decreased in patients with hepatic fibrosis, which consequently stimulates hepatic stellate cells’ (HSCs activation. We used a cDNA microarray study to gain a more comprehensive understanding of genome-wide gene expressions by adjusting miR-29a expression in a bile duct-ligation (BDL animal model. Methods: Using miR-29a transgenic mice and wild-type littermates and applying the BDL mouse model, we characterized the function of miR-29a with regard to cholestatic liver fibrosis. Pathway enrichment analysis and/or specific validation were performed for differentially expressed genes found within the comparisons. Results: Analysis of the microarray data identified a number of differentially expressed genes due to the miR-29a transgene, BDL, or both. Additional pathway enrichment analysis revealed that TGF-β signaling had a significantly differential activated pathway depending on the occurrence of miR-29a overexpression or the lack thereof. Furthermore, overexpression was found to elicit changes in Wnt/β-catenin after BDL. Conclusion: This study verified that an elevated miR-29a level could alleviate liver fibrosis caused by cholestasis. Furthermore, the protective effects of miR-29a correlate with the downregulation of TGF-β and associated with Wnt/β-catenin signal pathway following BDL.

Protein expression based multimarker analysis of breast cancer samples

International Nuclear Information System (INIS)

Presson, Angela P; Horvath, Steve; Yoon, Nam K; Bagryanova, Lora; Mah, Vei; Alavi, Mohammad; Maresh, Erin L; Rajasekaran, Ayyappan K; Goodglick, Lee; Chia, David

2011-01-01

Tissue microarray (TMA) data are commonly used to validate the prognostic accuracy of tumor markers. For example, breast cancer TMA data have led to the identification of several promising prognostic markers of survival time. Several studies have shown that TMA data can also be used to cluster patients into clinically distinct groups. Here we use breast cancer TMA data to cluster patients into distinct prognostic groups. We apply weighted correlation network analysis (WGCNA) to TMA data consisting of 26 putative tumor biomarkers measured on 82 breast cancer patients. Based on this analysis we identify three groups of patients with low (5.4%), moderate (22%) and high (50%) mortality rates, respectively. We then develop a simple threshold rule using a subset of three markers (p53, Na-KATPase-β1, and TGF β receptor II) that can approximately define these mortality groups. We compare the results of this correlation network analysis with results from a standard Cox regression analysis. We find that the rule-based grouping variable (referred to as WGCNA*) is an independent predictor of survival time. While WGCNA* is based on protein measurements (TMA data), it validated in two independent Affymetrix microarray gene expression data (which measure mRNA abundance). We find that the WGCNA patient groups differed by 35% from mortality groups defined by a more conventional stepwise Cox regression analysis approach. We show that correlation network methods, which are primarily used to analyze the relationships between gene products, are also useful for analyzing the relationships between patients and for defining distinct patient groups based on TMA data. We identify a rule based on three tumor markers for predicting breast cancer survival outcomes

Meta-analysis of differentiating mouse embryonic stem cell gene expression kinetics reveals early change of a small gene set.

Directory of Open Access Journals (Sweden)

Clive H Glover

2006-11-01

Full Text Available Stem cell differentiation involves critical changes in gene expression. Identification of these should provide endpoints useful for optimizing stem cell propagation as well as potential clues about mechanisms governing stem cell maintenance. Here we describe the results of a new meta-analysis methodology applied to multiple gene expression datasets from three mouse embryonic stem cell (ESC lines obtained at specific time points during the course of their differentiation into various lineages. We developed methods to identify genes with expression changes that correlated with the altered frequency of functionally defined, undifferentiated ESC in culture. In each dataset, we computed a novel statistical confidence measure for every gene which captured the certainty that a particular gene exhibited an expression pattern of interest within that dataset. This permitted a joint analysis of the datasets, despite the different experimental designs. Using a ranking scheme that favored genes exhibiting patterns of interest, we focused on the top 88 genes whose expression was consistently changed when ESC were induced to differentiate. Seven of these (103728_at, 8430410A17Rik, Klf2, Nr0b1, Sox2, Tcl1, and Zfp42 showed a rapid decrease in expression concurrent with a decrease in frequency of undifferentiated cells and remained predictive when evaluated in additional maintenance and differentiating protocols. Through a novel meta-analysis, this study identifies a small set of genes whose expression is useful for identifying changes in stem cell frequencies in cultures of mouse ESC. The methods and findings have broader applicability to understanding the regulation of self-renewal of other stem cell types.

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.

Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

Directory of Open Access Journals (Sweden)

Marie Mooney

Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

Molecular characterization and expression analysis of fat mass and ...

Indian Academy of Sciences (India)

Keywords. fat mass and obesity-associated gene (FTO); rabbit; mRNA expression patterns; sequence analysis; Oryctolagus cuniculus. ... In this work, the molecular characterization and expression features of rabbit (Oryctolagus cuniculus) FTO cDNA were analysed. The rabbit FTO cDNA with a size of 2158 bp was cloned, ...

Spectral analysis and filter theory in applied geophysics

CERN Document Server

Buttkus, Burkhard

2000-01-01

This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli­ cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval­ uated, and instructions provided for their practical application. Be­ sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob­ served data, maximum-entropy spectral analysis and maximum-like­ lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation­ ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil­ ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...

Automated image analysis of cyclin D1 protein expression in invasive lobular breast carcinoma provides independent prognostic information.

Science.gov (United States)

Tobin, Nicholas P; Lundgren, Katja L; Conway, Catherine; Anagnostaki, Lola; Costello, Sean; Landberg, Göran

2012-11-01

The emergence of automated image analysis algorithms has aided the enumeration, quantification, and immunohistochemical analyses of tumor cells in both whole section and tissue microarray samples. To date, the focus of such algorithms in the breast cancer setting has been on traditional markers in the common invasive ductal carcinoma subtype. Here, we aimed to optimize and validate an automated analysis of the cell cycle regulator cyclin D1 in a large collection of invasive lobular carcinoma and relate its expression to clinicopathologic data. The image analysis algorithm was trained to optimally match manual scoring of cyclin D1 protein expression in a subset of invasive lobular carcinoma tissue microarray cores. The algorithm was capable of distinguishing cyclin D1-positive cells and illustrated high correlation with traditional manual scoring (κ=0.63). It was then applied to our entire cohort of 483 patients, with subsequent statistical comparisons to clinical data. We found no correlation between cyclin D1 expression and tumor size, grade, and lymph node status. However, overexpression of the protein was associated with reduced recurrence-free survival (P=.029), as was positive nodal status (Pinvasive lobular carcinoma. Finally, high cyclin D1 expression was associated with increased hazard ratio in multivariate analysis (hazard ratio, 1.75; 95% confidence interval, 1.05-2.89). In conclusion, we describe an image analysis algorithm capable of reliably analyzing cyclin D1 staining in invasive lobular carcinoma and have linked overexpression of the protein to increased recurrence risk. Our findings support the use of cyclin D1 as a clinically informative biomarker for invasive lobular breast cancer. Copyright © 2012 Elsevier Inc. All rights reserved.

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.; Mallick, B. K.

2013-01-01

graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which

Research in applied mathematics, numerical analysis, and computer science

Science.gov (United States)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Applied behavior analysis: understanding and changing behavior in the community-a representative review.

Science.gov (United States)

Luyben, Paul D

2009-01-01

Applied behavior analysis, a psychological discipline, has been characterized as the science of behavior change (Chance, 2006). Research in applied behavior analysis has been published for approximately 40 years since the initial publication of the Journal of Applied Behavior Analysis in 1968. The field now encompasses a wide range of human behavior. Although much of the published research centers on problem behaviors that occur in schools and among people with disabilities, a substantial body of knowledge has emerged in community settings. This article provides a review of the behavioral community research published in the Journal of Applied Behavior Analysis as representative of this work, including research in the areas of home and family, health, safety, community involvement and the environment, recreation and sports, crime and delinquency, and organizations. In the interest of space, research in schools and with people with disabilities has been excluded from this review.

B. F. Skinner's Contributions to Applied Behavior Analysis

Science.gov (United States)

Morris, Edward K.; Smith, Nathaniel G.; Altus, Deborah E.

2005-01-01

Our paper reviews and analyzes B. F. Skinner's contributions to applied behavior analysis in order to assess his role as the field's originator and founder. We found, first, that his contributions fall into five categorizes: the style and content of his science, his interpretations of typical and atypical human behavior, the implications he drew…

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

Science.gov (United States)

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Transcriptome analysis of Schistosoma mansoni larval development using serial analysis of gene expression (SAGE).

Science.gov (United States)

Taft, A S; Vermeire, J J; Bernier, J; Birkeland, S R; Cipriano, M J; Papa, A R; McArthur, A G; Yoshino, T P

2009-04-01

Infection of the snail, Biomphalaria glabrata, by the free-swimming miracidial stage of the human blood fluke, Schistosoma mansoni, and its subsequent development to the parasitic sporocyst stage is critical to establishment of viable infections and continued human transmission. We performed a genome-wide expression analysis of the S. mansoni miracidia and developing sporocyst using Long Serial Analysis of Gene Expression (LongSAGE). Five cDNA libraries were constructed from miracidia and in vitro cultured 6- and 20-day-old sporocysts maintained in sporocyst medium (SM) or in SM conditioned by previous cultivation with cells of the B. glabrata embryonic (Bge) cell line. We generated 21 440 SAGE tags and mapped 13 381 to the S. mansoni gene predictions (v4.0e) either by estimating theoretical 3' UTR lengths or using existing 3' EST sequence data. Overall, 432 transcripts were found to be differentially expressed amongst all 5 libraries. In total, 172 tags were differentially expressed between miracidia and 6-day conditioned sporocysts and 152 were differentially expressed between miracidia and 6-day unconditioned sporocysts. In addition, 53 and 45 tags, respectively, were differentially expressed in 6-day and 20-day cultured sporocysts, due to the effects of exposure to Bge cell-conditioned medium.

X-ray fluorescence spectrometry applied to soil analysis

International Nuclear Information System (INIS)

Salvador, Vera Lucia Ribeiro; Sato, Ivone Mulako; Scapin Junior, Wilson Santo; Scapin, Marcos Antonio; Imakima, Kengo

1997-01-01

This paper studies the X-ray fluorescence spectrometry applied to the soil analysis. A comparative study of the WD-XRFS and ED-XRFS techniques was carried out by using the following soil samples: SL-1, SOIL-7 and marine sediment SD-M-2/TM, from IAEA, and clay, JG-1a from Geological Survey of Japan (GSJ)

Neutron activation analysis applied to energy and environment

International Nuclear Information System (INIS)

Lyon, W.S.

1975-01-01

Neutron activation analysis was applied to a number of problems concerned with energy production and the environment. Burning of fossil fuel, the search for new sources of uranium, possible presence of toxic elements in food and water, and the relationship of trace elements to cardiovascular disease are some of the problems in which neutron activation was used. (auth)

Research in progress in applied mathematics, numerical analysis, and computer science

Science.gov (United States)

1990-01-01

Research conducted at the Institute in Science and Engineering in applied mathematics, numerical analysis, and computer science is summarized. The Institute conducts unclassified basic research in applied mathematics in order to extend and improve problem solving capabilities in science and engineering, particularly in aeronautics and space.

Applied data analysis and modeling for energy engineers and scientists

CERN Document Server

Reddy, T Agami

2011-01-01

""Applied Data Analysis and Modeling for Energy Engineers and Scientists"" discusses mathematical models, data analysis, and decision analysis in modeling. The approach taken in this volume focuses on the modeling and analysis of thermal systems in an engineering environment, while also covering a number of other critical areas. Other material covered includes the tools that researchers and engineering professionals will need in order to explore different analysis methods, use critical assessment skills and reach sound engineering conclusions. The book also covers process and system design and

The time-course analysis of gene expression during wound healing in mouse skin.

Science.gov (United States)

Kagawa, Shinichiro; Matsuo, Aya; Yagi, Yoichi; Ikematsu, Kazuya; Tsuda, Ryouichi; Nakasono, Ichiro

2009-03-01

RNA analysis has been applied to forensic work to determine wound age. We investigated mRNA expression using quantitative RT-PCR of ten genes, including c-fos, fosB, mitogen-activated protein kinase phosphatase-1 (MKP-1), CD14, chemokine (C-C motif) ligand 9 (CCL9), placenta growth factor (PlGF), mast cell protease-5 (MCP-5), growth arrest specific 5 (Gas5), beta-2 microglobulin (B2M) and major urinary protein-1 (MUP-1), in terms of repair response in adult mice. The expression level of c-fos, fosB and MKP-1 transcripts increased drastically, peaked within 1h, and that of the CD14 and CCL9 transcripts peaked from 12 to 24h. An increase in PlGF and MCP-5 mRNA appeared on about day 5. Gas5, B2M and MUP-1 transcripts showed no significant change. Each gene had differentially expressional patterns with time-course. Our result implied that the observation of the 7 genes in wounded skin could serve to aid in the accurate diagnosis of wound age.

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Directory of Open Access Journals (Sweden)

Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Expression and cut parser for CMS event data

International Nuclear Information System (INIS)

Lista, Luca; Jones, Christopher D; Petrucciani, Giovanni

2010-01-01

We present a parser to evaluate expressions and Boolean selections that is applied on CMS event data for event filtering and analysis purposes. The parser is based on Boost Spirit grammar definition, and uses Reflex dictionaries for class introspection. The parser allows for a natural definition of expressions and cuts in users' configurations, and provides good runtime performance compared to other existing parsers.

Analysis of concrete beams using applied element method

Science.gov (United States)

Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen

2018-03-01

The Applied Element Method (AEM) is a displacement based method of structural analysis. Some of its features are similar to that of Finite Element Method (FEM). In AEM, the structure is analysed by dividing it into several elements similar to FEM. But, in AEM, elements are connected by springs instead of nodes as in the case of FEM. In this paper, background to AEM is discussed and necessary equations are derived. For illustrating the application of AEM, it has been used to analyse plain concrete beam of fixed support condition. The analysis is limited to the analysis of 2-dimensional structures. It was found that the number of springs has no much influence on the results. AEM could predict deflection and reactions with reasonable degree of accuracy.

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.

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.

Model Proposition for the Fiscal Policies Analysis Applied in Economic Field

Directory of Open Access Journals (Sweden)

Larisa Preda

2007-05-01

Full Text Available This paper presents a study about fiscal policy applied in economic development. Correlations between macroeconomics and fiscal indicators signify the first steep in our analysis. Next step is a new model proposal for the fiscal and budgetary choices. This model is applied on the date of the Romanian case.

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.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis

Directory of Open Access Journals (Sweden)

Oksana Zinchenko

2018-06-01

Full Text Available Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis.

Science.gov (United States)

Zinchenko, Oksana; Yaple, Zachary A; Arsalidou, Marie

2018-01-01

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Global Gene Expression Analysis of Yeast Cells during Sake Brewing▿ †

Science.gov (United States)

Wu, Hong; Zheng, Xiaohong; Araki, Yoshio; Sahara, Hiroshi; Takagi, Hiroshi; Shimoi, Hitoshi

2006-01-01

During the brewing of Japanese sake, Saccharomyces cerevisiae cells produce a high concentration of ethanol compared with other ethanol fermentation methods. We analyzed the gene expression profiles of yeast cells during sake brewing using DNA microarray analysis. This analysis revealed some characteristics of yeast gene expression during sake brewing and provided a scaffold for a molecular level understanding of the sake brewing process. PMID:16997994

Functional and Structural Analysis of a Highly-Expressed Yersinia pestis Small RNA following Infection of Cultured Macrophages.

Directory of Open Access Journals (Sweden)

Nan Li

Full Text Available Non-coding small RNAs (sRNAs are found in practically all bacterial genomes and play important roles in regulating gene expression to impact bacterial metabolism, growth, and virulence. We performed transcriptomics analysis to identify sRNAs that are differentially expressed in Yersinia pestis that invaded the human macrophage cell line THP-1, compared to pathogens that remained extracellular in the presence of host. Using ultra high-throughput sequencing, we identified 37 novel and 143 previously known sRNAs in Y. pestis. In particular, the sRNA Ysr170 was highly expressed in intracellular Yersinia and exhibited a log2 fold change ~3.6 higher levels compared to extracellular bacteria. We found that knock-down of Ysr170 expression attenuated infection efficiency in cell culture and growth rate in response to different stressors. In addition, we applied selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE analysis to determine the secondary structure of Ysr170 and observed structural changes resulting from interactions with the aminoglycoside antibiotic gentamycin and the RNA chaperone Hfq. Interestingly, gentamicin stabilized helix 4 of Ysr170, which structurally resembles the native gentamicin 16S ribosomal binding site. Finally, we modeled the tertiary structure of Ysr170 binding to gentamycin using RNA motif modeling. Integration of these experimental and structural methods can provide further insight into the design of small molecules that can inhibit function of sRNAs required for pathogen virulence.

Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

CERN Document Server

Shiavi, Richard

2007-01-01

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

Analysis of musical expression in audio signals

Science.gov (United States)

Dixon, Simon

2003-01-01

In western art music, composers communicate their work to performers via a standard notation which specificies the musical pitches and relative timings of notes. This notation may also include some higher level information such as variations in the dynamics, tempo and timing. Famous performers are characterised by their expressive interpretation, the ability to convey structural and emotive information within the given framework. The majority of work on audio content analysis focusses on retrieving score-level information; this paper reports on the extraction of parameters describing the performance, a task which requires a much higher degree of accuracy. Two systems are presented: BeatRoot, an off-line beat tracking system which finds the times of musical beats and tracks changes in tempo throughout a performance, and the Performance Worm, a system which provides a real-time visualisation of the two most important expressive dimensions, tempo and dynamics. Both of these systems are being used to process data for a large-scale study of musical expression in classical and romantic piano performance, which uses artificial intelligence (machine learning) techniques to discover fundamental patterns or principles governing expressive performance.

Synergy analysis reveals association between insulin signaling and desmoplakin expression in palmitate treated HepG2 cells.

Directory of Open Access Journals (Sweden)

Xuewei Wang

Full Text Available The regulation of complex cellular activities in palmitate treated HepG2 cells, and the ensuing cytotoxic phenotype, involves cooperative interactions between genes. While previous approaches have largely focused on identifying individual target genes, elucidating interacting genes has thus far remained elusive. We applied the concept of information synergy to reconstruct a "gene-cooperativity" network for palmititate-induced cytotoxicity in liver cells. Our approach integrated gene expression data with metabolic profiles to select a subset of genes for network reconstruction. Subsequent analysis of the network revealed insulin signaling as the most significantly enriched pathway, and desmoplakin (DSP as its top neighbor. We determined that palmitate significantly reduces DSP expression, and treatment with insulin restores the lost expression of DSP. Insulin resistance is a common pathological feature of fatty liver and related ailments, whereas loss of DSP has been noted in liver carcinoma. Reduced DSP expression can lead to loss of cell-cell adhesion via desmosomes, and disrupt the keratin intermediate filament network. Our findings suggest that DSP expression may be perturbed by palmitate and, along with insulin resistance, may play a role in palmitate induced cytotoxicity, and serve as potential targets for further studies on non-alcoholic fatty liver disease (NAFLD.

A Serial Analysis of Gene Expression (SAGE) database analysis of chemosensitivity

DEFF Research Database (Denmark)

Stein, Wilfred D; Litman, Thomas; Fojo, Tito

2004-01-01

are their corresponding solid tumors. We used the Serial Analysis of Gene Expression (SAGE) database to identify differences between solid tumors and cell lines, hoping to detect genes that could potentially explain differences in drug sensitivity. SAGE libraries were available for both solid tumors and cell lines from...

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

Directory of Open Access Journals (Sweden)

Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Applied Behavior Analysis Is a Science And, Therefore, Progressive

Science.gov (United States)

Leaf, Justin B.; Leaf, Ronald; McEachin, John; Taubman, Mitchell; Ala'i-Rosales, Shahla; Ross, Robert K.; Smith, Tristram; Weiss, Mary Jane

2016-01-01

Applied behavior analysis (ABA) is a science and, therefore, involves progressive approaches and outcomes. In this commentary we argue that the spirit and the method of science should be maintained in order to avoid reductionist procedures, stifled innovation, and rote, unresponsive protocols that become increasingly removed from meaningful…

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...

Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment

Directory of Open Access Journals (Sweden)

Nan Liu

2018-01-01

Full Text Available Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55% were clean reads. Five differentially expressed genes with an adjusted P value 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

Science.gov (United States)

Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

2009-02-01

Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

Paired Expression Analysis of Tumor Cell Surface Antigens

Directory of Open Access Journals (Sweden)

Rimas J. Orentas

2017-08-01

Full Text Available Adoptive immunotherapy with antibody-based therapy or with T cells transduced to express chimeric antigen receptors (CARs is useful to the extent that the cell surface membrane protein being targeted is not expressed on normal tissues. The most successful CAR-based (anti-CD19 or antibody-based therapy (anti-CD20 in hematologic malignancies has the side effect of eliminating the normal B cell compartment. Targeting solid tumors may not provide a similar expendable marker. Beyond antibody to Her2/NEU and EGFR, very few antibody-based and no CAR-based therapies have seen broad clinical application for solid tumors. To expand the way in which the surfaceome of solid tumors can be analyzed, we created an algorithm that defines the pairwise relative overexpression of surface antigens. This enables the development of specific immunotherapies that require the expression of two discrete antigens on the surface of the tumor target. This dyad analysis was facilitated by employing the Hotelling’s T-squared test (Hotelling–Lawley multivariate analysis of variance for two independent variables in comparison to a third constant entity (i.e., gene expression levels in normal tissues. We also present a unique consensus scoring mechanism for identifying transcripts that encode cell surface proteins. The unique application of our bioinformatics processing pipeline and statistical tools allowed us to compare the expression of two membrane protein targets as a pair, and to propose a new strategy based on implementing immunotherapies that require both antigens to be expressed on the tumor cell surface to trigger therapeutic effector mechanisms. Specifically, we found that, for MYCN amplified neuroblastoma, pairwise expression of ACVR2B or anaplastic lymphoma kinase (ALK with GFRA3, GFRA2, Cadherin 24, or with one another provided the strongest hits. For MYCN, non-amplified stage 4 neuroblastoma, neurotrophic tyrosine kinase 1, or ALK paired with GFRA2, GFRA3, SSK

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.

Mathematical adventures in performance analysis from storage systems, through airplane boarding, to express line queues

CERN Document Server

Bachmat, Eitan

2014-01-01

This monograph describes problems in the field of performance analysis, primarily the study of storage systems and the diverse mathematical techniques that are required for solving such problems. Topics covered include best practices for scheduling I/O requests to a disk drive, how this problem is related to airplane boarding, and how both problems can be modeled using space-time geometry. The author also explains how Riemann's proof of the analytic continuation and functional equation of the Riemann zeta function can be used to analyze express-line queues in a minimarket. Overall, the book reveals the surprising applicability of abstract mathematical ideas that are not usually associated with applied topics. Advanced undergraduate students or graduate students with an interest in the applications of mathematics will find this book a useful resource. It will also be of interest to professional mathematicians who want exposure to the surprising ways that theoretical mathematics may be applied to engineering pr...

Molecular responses and expression analysis of genes in a ...

African Journals Online (AJOL)

STORAGESEVER

2009-06-17

Jun 17, 2009 ... Molecular responses and expression analysis of genes in a xerophytic desert shrub Haloxylon ammodendron .... physiological determination and cDNA-AFLP analysis, three groups of seeds were sowed in pots with sand and .... HaDR27. U. 234. PDR-like ABC transporter. AT1G59870. HaDR28. U. 135.

Dimensional Analysis with space discrimination applied to Fickian difussion phenomena

International Nuclear Information System (INIS)

Diaz Sanchidrian, C.; Castans, M.

1989-01-01

Dimensional Analysis with space discrimination is applied to Fickian difussion phenomena in order to transform its partial differen-tial equations into ordinary ones, and also to obtain in a dimensionl-ess fom the Ficks second law. (Author)

Neisseria meningitidis rifampicin resistant strains: analysis of protein differentially expressed

Directory of Open Access Journals (Sweden)

Schininà Maria

2010-09-01

Full Text Available Abstract Background Several mutations have been described as responsible for rifampicin resistance in Neisseria meningitidis. However, the intriguing question on why these strains are so rare remains open. The aim of this study was to investigate the protein content and to identify differential expression in specific proteins in two rifampicin resistant and one susceptible meningococci using two-dimensional electrophoresis (2-DE combined with mass spectrometry. Results In our experimental conditions, able to resolve soluble proteins with an isoelectric point between 4 and 7, twenty-three proteins have been found differentially expressed in the two resistant strains compared to the susceptible. Some of them, involved in the main metabolic pathways, showed an increased expression, mainly in the catabolism of pyruvate and in the tricarboxylic acid cycle. A decreased expression of proteins belonging to gene regulation and to those involved in the folding of polypeptides has also been observed. 2-DE analysis showed the presence of four proteins displaying a shift in their isoelectric point in both resistant strains, confirmed by the presence of amino acid changes in the sequence analysis, absent in the susceptible. Conclusions The analysis of differentially expressed proteins suggests that an intricate series of events occurs in N. meningitidis rifampicin resistant strains and the results here reported may be considered a starting point in understanding their decreased invasion capacity. In fact, they support the hypothesis that the presence of more than one protein differentially expressed, having a role in the metabolism of the meningococcus, influences its ability to infect and to spread in the population. Different reports have described and discussed how a drug resistant pathogen shows a high biological cost for survival and that may also explain why, for some pathogens, the rate of resistant organisms is relatively low considering the

Computerised analysis of facial emotion expression in eating disorders

Science.gov (United States)

2017-01-01

Background Problems with social-emotional processing are known to be an important contributor to the development and maintenance of eating disorders (EDs). Diminished facial communication of emotion has been frequently reported in individuals with anorexia nervosa (AN). Less is known about facial expressivity in bulimia nervosa (BN) and in people who have recovered from AN (RecAN). This study aimed to pilot the use of computerised facial expression analysis software to investigate emotion expression across the ED spectrum and recovery in a large sample of participants. Method 297 participants with AN, BN, RecAN, and healthy controls were recruited. Participants watched film clips designed to elicit happy or sad emotions, and facial expressions were then analysed using FaceReader. Results The finding mirrored those from previous work showing that healthy control and RecAN participants expressed significantly more positive emotions during the positive clip compared to the AN group. There were no differences in emotion expression during the sad film clip. Discussion These findings support the use of computerised methods to analyse emotion expression in EDs. The findings also demonstrate that reduced positive emotion expression is likely to be associated with the acute stage of AN illness, with individuals with BN showing an intermediate profile. PMID:28575109

Computerised analysis of facial emotion expression in eating disorders.

Science.gov (United States)

Leppanen, Jenni; Dapelo, Marcela Marin; Davies, Helen; Lang, Katie; Treasure, Janet; Tchanturia, Kate

2017-01-01

Problems with social-emotional processing are known to be an important contributor to the development and maintenance of eating disorders (EDs). Diminished facial communication of emotion has been frequently reported in individuals with anorexia nervosa (AN). Less is known about facial expressivity in bulimia nervosa (BN) and in people who have recovered from AN (RecAN). This study aimed to pilot the use of computerised facial expression analysis software to investigate emotion expression across the ED spectrum and recovery in a large sample of participants. 297 participants with AN, BN, RecAN, and healthy controls were recruited. Participants watched film clips designed to elicit happy or sad emotions, and facial expressions were then analysed using FaceReader. The finding mirrored those from previous work showing that healthy control and RecAN participants expressed significantly more positive emotions during the positive clip compared to the AN group. There were no differences in emotion expression during the sad film clip. These findings support the use of computerised methods to analyse emotion expression in EDs. The findings also demonstrate that reduced positive emotion expression is likely to be associated with the acute stage of AN illness, with individuals with BN showing an intermediate profile.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

Directory of Open Access Journals (Sweden)

Hero Alfred

2010-11-01

Full Text Available Abstract Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP, the Indian Buffet Process (IBP, and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV, Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD, closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

Science.gov (United States)

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Transcriptome Analysis of Mycobacteria-Specific CD4+ T Cells Identified by Activation-Induced Expression of CD154.

Science.gov (United States)

Kunnath-Velayudhan, Shajo; Goldberg, Michael F; Saini, Neeraj K; Johndrow, Christopher T; Ng, Tony W; Johnson, Alison J; Xu, Jiayong; Chan, John; Jacobs, William R; Porcelli, Steven A

2017-10-01

Analysis of Ag-specific CD4 + T cells in mycobacterial infections at the transcriptome level is informative but technically challenging. Although several methods exist for identifying Ag-specific T cells, including intracellular cytokine staining, cell surface cytokine-capture assays, and staining with peptide:MHC class II multimers, all of these have significant technical constraints that limit their usefulness. Measurement of activation-induced expression of CD154 has been reported to detect live Ag-specific CD4 + T cells, but this approach remains underexplored and, to our knowledge, has not previously been applied in mycobacteria-infected animals. In this article, we show that CD154 expression identifies adoptively transferred or endogenous Ag-specific CD4 + T cells induced by Mycobacterium bovis bacillus Calmette-Guérin vaccination. We confirmed that Ag-specific cytokine production was positively correlated with CD154 expression by CD4 + T cells from bacillus Calmette-Guérin-vaccinated mice and show that high-quality microarrays can be performed from RNA isolated from CD154 + cells purified by cell sorting. Analysis of microarray data demonstrated that the transcriptome of CD4 + CD154 + cells was distinct from that of CD154 - cells and showed major enrichment of transcripts encoding multiple cytokines and pathways of cellular activation. One notable finding was the identification of a previously unrecognized subset of mycobacteria-specific CD4 + T cells that is characterized by the production of IL-3. Our results support the use of CD154 expression as a practical and reliable method to isolate live Ag-specific CD4 + T cells for transcriptomic analysis and potentially for a range of other studies in infected or previously immunized hosts. Copyright © 2017 by The American Association of Immunologists, Inc.

Beyond Time out and Table Time: Today's Applied Behavior Analysis for Students with Autism

Science.gov (United States)

Boutot, E. Amanda; Hume, Kara

2012-01-01

Recent mandates related to the implementation of evidence-based practices for individuals with autism spectrum disorder (ASD) require that autism professionals both understand and are able to implement practices based on the science of applied behavior analysis (ABA). The use of the term "applied behavior analysis" and its related concepts…

Conversation Analysis and Applied Linguistics.

Science.gov (United States)

Schegloff, Emanuel A.; Koshik, Irene; Jacoby, Sally; Olsher, David

2002-01-01

Offers biographical guidance on several major areas of conversation-analytic work--turn-taking, repair, and word selection--and indicates past or potential points of contact with applied linguistics. Also discusses areas of applied linguistic work. (Author/VWL)

A proteomic method for analysis of CYP450s protein expression changes in carbon tetrachloride induced male rat liver microsomes

International Nuclear Information System (INIS)

Jia Nuan; Liu Xin; Wen Jun; Qian Linyi; Qian Xiaohong; Wu Yutian; Fan Guorong

2007-01-01

Carbon tetrachloride (CCl 4 ) is a well-known model compound for producing chemical hepatic injury. Cytochrome P450 is an important monooxygenase in biology. We investigated the CYP450 protein expression in the in vivo hepatotoxicity of rats induced by CCl 4 . In this experiment, CCl 4 were administered to male rats, and their livers at 24 h post-dosing were applied to the proteomic analysis. Blood biochemistry and histopathology were examined to identify specific changes. At the same time, a novel acetylation stable isotopic labeling method coupled with LTQ-FTICR mass spectrometry was applied to disclose the changes of cytochrome P450 expression amounts. The quantitative proteomics method demonstrated its correlation coefficient was 0.9998 in a 100-fold dynamic range and the average ratio of the labeled peptides was 1.04, which was very close to the theoretical ratio of 1.00 and the standard deviation (S.D.) of 0.21. With this approach, 17 cytochrome P450 proteins were identified and quantified with high confidence. Among them, the expression amount of 2C11, 3A2, and 2 E1 were down-regulated, while that of 2C6, 2B2, and 2B1 were up-regulated

The first facial expression recognition and analysis challenge

NARCIS (Netherlands)

Valstar, Michel F.; Jiang, Bihan; Mehu, Marc; Pantic, Maja; Scherer, Klaus

Automatic Facial Expression Recognition and Analysis, in particular FACS Action Unit (AU) detection and discrete emotion detection, has been an active topic in computer science for over two decades. Standardisation and comparability has come some way; for instance, there exist a number of commonly

Inclusive Elementary Classroom Teacher Knowledge of and Attitudes toward Applied Behavior Analysis and Autism Spectrum Disorder and Their Use of Applied Behavior Analysis

Science.gov (United States)

McCormick, Jennifer A.

2011-01-01

The purpose of this study was to examine inclusive elementary teacher knowledge and attitude toward Autism Spectrum Disorder (ASD) and applied behavior analysis (ABA) and their use of ABA. Furthermore, this study examined if knowledge and attitude predicted use of ABA. A survey was developed and administered through a web-based program. Of the…

Automated SEM Modal Analysis Applied to the Diogenites

Science.gov (United States)

Bowman, L. E.; Spilde, M. N.; Papike, James J.

1996-01-01

Analysis of volume proportions of minerals, or modal analysis, is routinely accomplished by point counting on an optical microscope, but the process, particularly on brecciated samples such as the diogenite meteorites, is tedious and prone to error by misidentification of very small fragments, which may make up a significant volume of the sample. Precise volume percentage data can be gathered on a scanning electron microscope (SEM) utilizing digital imaging and an energy dispersive spectrometer (EDS). This form of automated phase analysis reduces error, and at the same time provides more information than could be gathered using simple point counting alone, such as particle morphology statistics and chemical analyses. We have previously studied major, minor, and trace-element chemistry of orthopyroxene from a suite of diogenites. This abstract describes the method applied to determine the modes on this same suite of meteorites and the results of that research. The modal abundances thus determined add additional information on the petrogenesis of the diogenites. In addition, low-abundance phases such as spinels were located for further analysis by this method.

Sports dance artistic expression culture analysis

OpenAIRE

Chen Zegang

2017-01-01

At present, the sports dance has entered every stage of the people’s life, has become the public’s favorite sport. Sports dance has been well developed. This article mainly uses the literature material law to carry on the detailed analysis to the sports dance constitution, elaborated in detail the sports dance artistic expression. The composition of sports dance elements; sports dance is a form of dance art show; sports dance through the dance art can be divided into three aspects, namely, fo...

[Cloning and expressing of cyclophilin B gene from Schistosoma japonnicum and the analysis of immunoprotective effect].

Science.gov (United States)

Peng, Jinbiao; Han, Hongxiao; Hong, Yang; Wang, Yan; Guo, Fanji; Shi, Yaojun; Fu, Zhiqiang; Liu, Jinming; Cheng, Guofeng; Lin, Jiaojiao

2010-03-01

The present study was intend to clone and express the cDNA encoding Cyclophilin B (CyPB) of Schistosoma japonicum, its preliminary biological function and further immunoprotective effect against schistosome infection in mice. RT-PCR technique was applied to amplify a full-length cDNA encoding protein Cyclophilin B (Sj CyPB) from schistosomula cDNA. The expression profiles of Sj CyPB were determined by Real-time PCR using the template cDNAs isolated from 7, 13, 18, 23, 32 and 42 days parasites. The cDNA containing the Open Reading Frame of CyPB was then subcloned into a pGEX-6P-1 vector and transformed into competent Escherichia coli BL21 for expressing. The recombinant protein was renaturated, purified and its antigenicity were detected by Western blotting, and the immunoprotective effect induced by recombinant Sj CyPB was evaluated in Balb/C mice. The cDNA containing the ORF of Sj CyPB was cloned with the length of 672 base pairs, encoding 223 amino acids. Real-time PCR analysis revealed that the gene had the highest expression in 18-day schistosomula, suggesting that Sj CyPB was schistosomula differentially expressed gene. The recombinant protein showed a good antigenicity detected by Western blotting. Animal experiment indicated that the vaccination of recombinant CyPB protein in mice led to 31.5% worm and 41.01% liver egg burden reduction, respectively, compared with those of the control. A full-length cDNA differentially expressed in schistosomula was obtained. The recombinant Sj CyPB protein could induce partial protection against schistosome infection.

Applied research and development of neutron activation analysis

International Nuclear Information System (INIS)

Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Baek, Sung Ryel; Kim, Young Gi; Jung, Hwan Sung; Park, Kwang Won; Kang, Sang Hun; Lim, Jong Myoung

2003-05-01

The aims of this project are to establish the quality control system of Neutron Activation Analysis(NAA) due to increase of industrial needs for standard analytical method and to prepare and identify the standard operation procedure of NAA through practical testing for different analytical items. R and D implementations of analytical quality system using neutron irradiation facility and gamma-ray measurement system and automation of NAA facility in HANARO research reactor are as following ; 1) Establishment of NAA quality control system for the maintenance of best measurement capability and the promotion of utilization of HANARO research reactor 2) Improvement of analytical sensitivity for industrial applied technologies and establishment of certified standard procedures 3) Standardization and development of Prompt Gamma-ray Activation Analysis (PGAA) technology

Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

Directory of Open Access Journals (Sweden)

M J Pont

Full Text Available Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage-restricted expression as potential targets for immunotherapy of hematological cancers.

Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.

Directory of Open Access Journals (Sweden)

Kai Wang

2009-12-01

Full Text Available Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific characterizing evolutionary plasticity. We developed a semi-parametric meta-analysis approach for combining gene-gene co-expression relationships across expression profile datasets from multiple species. The simulation results showed that the semi-parametric method is robust against noise. When applied to human, mouse, and rat liver co-expression networks, our method out-performed existing methods in identifying gene pairs with coherent biological functions. We identified a network conserved across species that highlighted cell-cell signaling, cell-adhesion and sterol biosynthesis as main biological processes represented in genome-wide association study candidate gene sets for blood lipid levels. We further developed a heterogeneity statistic to test for network differences among multiple datasets, and demonstrated that genes with species-specific interactions tend to be under positive selection throughout evolution. Finally, we identified a human-specific sub-network regulated by RXRG, which has been validated to play a different role in hyperlipidemia and Type 2 diabetes between human and mouse. Taken together, our approach represents a novel step forward in integrating gene co-expression networks from multiple large scale datasets to leverage not only common information but also differences that are dataset-specific.

An Analysis of Methods Section of Research Reports in Applied Linguistics

OpenAIRE

Patrícia Marcuzzo

2011-01-01

This work aims at identifying analytical categories and research procedures adopted in the analysis of research article in Applied Linguistics/EAP in order to propose a systematization of the research procedures in Genre Analysis. For that purpose, 12 research reports and interviews with four authors were analyzed. The analysis showed that the studies are concentrated on the investigation of the macrostructure or on the microstructure of research articles in different fields. Studies about th...

Analysis of Brick Masonry Wall using Applied Element Method

Science.gov (United States)

Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen

2018-03-01

The Applied Element Method (AEM) is a versatile tool for structural analysis. Analysis is done by discretising the structure as in the case of Finite Element Method (FEM). In AEM, elements are connected by a set of normal and shear springs instead of nodes. AEM is extensively used for the analysis of brittle materials. Brick masonry wall can be effectively analyzed in the frame of AEM. The composite nature of masonry wall can be easily modelled using springs. The brick springs and mortar springs are assumed to be connected in series. The brick masonry wall is analyzed and failure load is determined for different loading cases. The results were used to find the best aspect ratio of brick to strengthen brick masonry wall.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

Science.gov (United States)

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

In silico analysis and verification of S100 gene expression in gastric cancer

International Nuclear Information System (INIS)

Liu, Ji; Li, Xue; Dong, Guang-Long; Zhang, Hong-Wei; Chen, Dong-Li; Du, Jian-Jun; Zheng, Jian-Yong; Li, Ji-Peng; Wang, Wei-Zhong

2008-01-01

The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca 2+ binding motif. They were involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. However, the expression status of S100 family members in gastric cancer was not known yet. Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated. The expression of S100A3 was further evaluated by quantitative RT-PCR. At least 5 S100 genes were found to be upregulated in gastric cance by in silico analysis. Among them, four genes, including S100A2, S100A4, S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. The expression of S100A3 in eighty patients of gastric cancer was further examined. The results showed that the mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer, which was relatively highly expressed in poorly differentiated and advanced gastric cancer tissues (P < 0.05). To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancers by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancers and S100A3 might play important roles in differentiation and progression of gastric cancer

Applied Fourier analysis from signal processing to medical imaging

CERN Document Server

Olson, Tim

2017-01-01

The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

A comparative Analysis by SAGE of Gene Expression Profiles of Esophageal Adenocarcinoma and Esophageal Squamous Cell Carcinoma

Directory of Open Access Journals (Sweden)

Jantine W. P. M. van Baal

2008-01-01

Full Text Available Esophageal adenocarcinoma (EA and esophageal squamous cell carcinoma (ESCC are the two main types of esophageal cancer. Despite extensive research the exact molecular basis of these cancers is unclear. Therefore we evaluated the transcriptome of EA in comparison to non-dysplastic Barrett’s esophagus (BE, the metaplastic epithelium that predisposes for EA, and compared the transcriptome of ESCC to normal esophageal squamous epithelium. For obtaining the transcriptomes tissue biopsies were used and serial analysis of gene expression (SAGE was applied. Validation of results by RT-PCR and immunoblotting was performed using tissues of an additional 23 EA and ESCC patients. Over 58,000 tags were sequenced. Between EA and BE 1013, and between ESCC and normal squamous epithelium 1235 tags were significantly differentially expressed (p < 0.05. The most up-regulated genes in EA compared to BE were SRY-box 4 and Lipocalin2, whereas the most down-regulated genes in EA were Trefoil factors and Annexin A10. The most up-regulated genes in ESCC compared to normal squamous epithelium were BMP4, E-Cadherin and TFF3. The results could suggest that the BE expression profile is closer related to normal squamous esophagus then to EA. In addition, several uniquely expressed genes are identified.

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

Molecular Characterization and Expression Analysis of Equine ( Gene in Horse (

Directory of Open Access Journals (Sweden)

Ki-Duk Song

2014-05-01

Full Text Available The objective of this study was to determine the molecular characteristics of the horse vascular endothelial growth factor alpha gene (VEGFα by constructing a phylogenetic tree, and to investigate gene expression profiles in tissues and blood leukocytes after exercise for development of suitable biomarkers. Using published amino acid sequences of other vertebrate species (human, chimpanzee, mouse, rat, cow, pig, chicken and dog, we constructed a phylogenetic tree which showed that equine VEGFα belonged to the same clade of the pig VEGFα. Analysis for synonymous (Ks and non-synonymous substitution ratios (Ka revealed that the horse VEGFα underwent positive selection. RNA was extracted from blood samples before and after exercise and different tissue samples of three horses. Expression analyses using reverse transcription-polymerase chain reaction (RT-PCR and quantitative-polymerase chain reaction (qPCR showed ubiquitous expression of VEGFα mRNA in skeletal muscle, kidney, thyroid, lung, appendix, colon, spinal cord, and heart tissues. Analysis of differential expression of VEGFα gene in blood leukocytes after exercise indicated a unimodal pattern. These results will be useful in developing biomarkers that can predict the recovery capacity of racing horses.

Evolution and expression analysis of the soybean glutamate ...

Indian Academy of Sciences (India)

Evolution and expression analysis of the soybean glutamate decarboxylase gene family. TAE KYUNG HYUN, SEUNG HEE EOM, XIAO HAN and JU-SUNG KIM http://www.ias.ac.in/jbiosci. J. Biosci. 39(5), December 2014, 899–907, © Indian Academy of Sciences. Supplementary material. Supplementary figure 1.

Protein expression analysis of inflammation-related colon carcinogenesis

Directory of Open Access Journals (Sweden)

Yasui Yumiko

2009-01-01

Full Text Available Background: Chronic inflammation is a risk factor for colorectal cancer (CRC development. The aim of this study was to determine the differences in protein expression between CRC and the surrounding nontumorous colonic tissues in the mice that received azoxymethane (AOM and dextran sodium sulfate (DSS using a proteomic analysis. Materials and Methods: Male ICR mice were given a single intraperitoneal injection of AOM (10 mg/kg body weight, followed by 2% (w/v DSS in their drinking water for seven days, starting one week after the AOM injection. Colonic adenocarcinoma developed after 20 weeks and a proteomics analysis based on two-dimensional gel electrophoresis and ultraflex TOF/TOF mass spectrometry was conducted in the cancerous and nontumorous tissue specimens. Results: The proteomic analysis revealed 21 differentially expressed proteins in the cancerous tissues in comparison to the nontumorous tissues. There were five markedly increased proteins (beta-tropomyosin, tropomyosin 1 alpha isoform b, S100 calcium binding protein A9, and an unknown protein and 16 markedly decreased proteins (Car1 proteins, selenium-binding protein 1, HMG-CoA synthase, thioredoxin 1, 1 Cys peroxiredoxin protein 2, Fcgbp protein, Cytochrome c oxidase, subunit Va, ETHE1 protein, and 7 unknown proteins. Conclusions: There were 21 differentially expressed proteins in the cancerous tissues of the mice that received AOM and DSS. Their functions include metabolism, the antioxidant system, oxidative stress, mucin production, and inflammation. These findings may provide new insights into the mechanisms of inflammation-related colon carcinogenesis and the establishment of novel therapies and preventative strategies to treat carcinogenesis in the inflamed colon.

Cost-effectiveness analysis in melanoma detection: A transition model applied to dermoscopy.

Science.gov (United States)

Tromme, Isabelle; Legrand, Catherine; Devleesschauwer, Brecht; Leiter, Ulrike; Suciu, Stefan; Eggermont, Alexander; Sacré, Laurine; Baurain, Jean-François; Thomas, Luc; Beutels, Philippe; Speybroeck, Niko

2016-11-01

The main aim of this study is to demonstrate how our melanoma disease model (MDM) can be used for cost-effectiveness analyses (CEAs) in the melanoma detection field. In particular, we used the data of two cohorts of Belgian melanoma patients to investigate the cost-effectiveness of dermoscopy. A MDM, previously constructed to calculate the melanoma burden, was slightly modified to be suitable for CEAs. Two cohorts of patients entered into the model to calculate morbidity, mortality and costs. These cohorts were constituted by melanoma patients diagnosed by dermatologists adequately, or not adequately, trained in dermoscopy. Effectiveness and costs were calculated for each cohort and compared. Effectiveness was expressed in quality-adjusted life years (QALYs), a composite measure depending on melanoma-related morbidity and mortality. Costs included costs of treatment and follow-up as well as costs of detection in non-melanoma patients and costs of excision and pathology of benign lesions excised to rule out melanoma. The result of our analysis concluded that melanoma diagnosis by dermatologists adequately trained in dermoscopy resulted in both a gain of QALYs (less morbidity and/or mortality) and a reduction in costs. This study demonstrates how our MDM can be used in CEAs in the melanoma detection field. The model and the methodology suggested in this paper were applied to two cohorts of Belgian melanoma patients. Their analysis concluded that adequate dermoscopy training is cost-effective. The results should be confirmed by a large-scale randomised study. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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)

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

Science.gov (United States)

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.

Directory of Open Access Journals (Sweden)

Helen L Ramsden

2015-01-01

Full Text Available Neural circuits in the medial entorhinal cortex (MEC encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.

Prognostic and clinical significance of histone deacetylase 1 expression in breast cancer: A meta-analysis.

Science.gov (United States)

Qiao, Weiqiang; Liu, Heyang; Liu, Ruidong; Liu, Qipeng; Zhang, Ting; Guo, Wanying; Li, Peng; Deng, Miao

2018-05-05

There are conflicting reports about the role of histone deacetylase 1 (HDAC1) in breast cancer prognosis. Here, we conducted a meta-analysis to investigate the prognostic significance of HDAC1 in breast cancer. We searched different databases to identify studies evaluating the association between HDAC1 expression and its prognostic value in breast cancer. The pooled hazard ratios (HRs) and odds radios (ORs) with 95% confidence intervals (95% CIs) were calculated from these studies to assess specific correlation. Our meta-analysis of four databases identified 7 eligible studies with 1429 total patients. We found that HDAC1 over-expression did not correlate with disease-free survival (DFS) and overall survival (OS) in breast cancer. Subgroup analysis indicated an association between up-regulated HDAC1 expression and better OS (HR = 0.47, 95% CI: 0.23-0.97; P = 0.04) in Asian breast cancer patients. However, false-positive report probability (FPRP) analysis and trial sequential analysis (TSA) indicated that the results need further validation. Furthermore, HDAC1 over-expression was associated with positive estrogen receptor (ER) expression (OR, 3.30; 95% CI, 1.11-9.83; P = 0.03) and negative human epidermal growth factor receptor 2 (HER2) expression (OR, 1.79; 95% CI, 1.22-2.61; P = 0.003), but there were no significant differences between patients based on age, tumor size, lymph node metastasis, nuclear grade, or progesterone receptor (PR) expression. Overall, our meta-analysis demonstrated an association between increased HDAC1 expression and better OS in Asian breast cancer patients. In addition, HDAC1 over-expression correlated with positive ER and negative HER2 expression in breast cancer. However, researches in large patients' randomised controlled trials (RCTs) are needed to confirm the results. Copyright © 2018 Elsevier B.V. All rights reserved.

Positive Behavior Support and Applied Behavior Analysis: A Familial Alliance

Science.gov (United States)

Dunlap, Glen; Carr, Edward G.; Horner, Robert H.; Zarcone, Jennifer R.; Schwartz, Ilene

2008-01-01

Positive behavior support (PBS) emerged in the mid-1980s as an approach for understanding and addressing problem behaviors. PBS was derived primarily from applied behavior analysis (ABA). Over time, however, PBS research and practice has incorporated evaluative methods, assessment and intervention procedures, and conceptual perspectives associated…

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.

Stochastic biological response to radiation. Comprehensive analysis of gene expression

International Nuclear Information System (INIS)

Inoue, Tohru; Hirabayashi, Yoko

2012-01-01

Authors explain that the radiation effect on biological system is stochastic along the law of physics, differing from chemical effect, using instances of Cs-137 gamma-ray (GR) and benzene (BZ) exposures to mice and of resultant comprehensive analyses of gene expression. Single GR irradiation is done with Gamma Cell 40 (CSR) to C57BL/6 or C3H/He mouse at 0, 0.6 and 3 Gy. BE is given orally at 150 mg/kg/day for 5 days x 2 weeks. Bone marrow cells are sampled 1 month after the exposure. Comprehensive gene expression is analyzed by Gene Chip Mouse Genome 430 2.0 Array (Affymetrix) and data are processed by programs like case normalization, statistics, network generation, functional analysis etc. GR irradiation brings about changes of gene expression, which are classifiable in common genes variable commonly on the dose change and stochastic genes variable stochastically within each dose: e.g., with Welch-t-test, significant differences are between 0/3 Gy (dose-specific difference, 455 pbs (probe set), in stochastic 2113 pbs), 0/0.6 Gy (267 in 1284 pbs) and 0.6/3 Gy (532 pbs); and with one-way analysis of variation (ANOVA) and hierarchial/dendrographic analyses, 520 pbs are shown to involve the dose-dependent 226 and dose-specific 294 pbs. It is also shown that at 3 Gy, expression of common genes are rather suppressed, including those related to the proliferation/apoptosis of B/T cells, and of stochastic genes, related to cell division/signaling. Ven diagram of the common genes of above 520 pbs, stochastic 2113 pbs at 3 Gy and 1284 pbs at 0.6 Gy shows the overlapping genes 29, 2 and 4, respectively, indicating only 35 pbs are overlapping in total. Network analysis of changes by GR shows the rather high expression of genes around hub of cAMP response element binding protein (CREB) at 0.6 Gy, and rather variable expression around CREB hub/suppressed expression of kinesin hub at 3 Gy; in the network by BZ exposure, unchanged or low expression around p53 hub and suppression

General theory for integrated analysis of growth, gene, and protein expression in biofilms.

Science.gov (United States)

Zhang, Tianyu; Pabst, Breana; Klapper, Isaac; Stewart, Philip S

2013-01-01

A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.

Tissue Microarray Analysis Applied to Bone Diagenesis.

Science.gov (United States)

Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

2017-01-04

Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

Xylella fastidiosa gene expression analysis by DNA microarrays

Directory of Open Access Journals (Sweden)

Regiane F. Travensolo

2009-01-01

Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Apply Functional Modelling to Consequence Analysis in Supervision Systems

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Gola, Giulio

2013-01-01

This paper will first present the purpose and goals of applying functional modelling approach to consequence analysis by adopting Multilevel Flow Modelling (MFM). MFM Models describe a complex system in multiple abstraction levels in both means-end dimension and whole-part dimension. It contains...... consequence analysis to practical or online applications in supervision systems. It will also suggest a multiagent solution as the integration architecture for developing tools to facilitate the utilization results of functional consequence analysis. Finally a prototype of the multiagent reasoning system...... causal relations between functions and goals. A rule base system can be developed to trace the causal relations and perform consequence propagations. This paper will illustrate how to use MFM for consequence reasoning by using rule base technology and describe the challenges for integrating functional...

Fast identification of folded human protein domains expressed in E. coli suitable for structural analysis

Directory of Open Access Journals (Sweden)

Schlegel Brigitte

2004-03-01

Full Text Available Abstract Background High-throughput protein structure analysis of individual protein domains requires analysis of large numbers of expression clones to identify suitable constructs for structure determination. For this purpose, methods need to be implemented for fast and reliable screening of the expressed proteins as early as possible in the overall process from cloning to structure determination. Results 88 different E. coli expression constructs for 17 human protein domains were analysed using high-throughput cloning, purification and folding analysis to obtain candidates suitable for structural analysis. After 96 deep-well microplate expression and automated protein purification, protein domains were directly analysed using 1D 1H-NMR spectroscopy. In addition, analytical hydrophobic interaction chromatography (HIC was used to detect natively folded protein. With these two analytical methods, six constructs (representing two domains were quickly identified as being well folded and suitable for structural analysis. Conclusion The described approach facilitates high-throughput structural analysis. Clones expressing natively folded proteins suitable for NMR structure determination were quickly identified upon small scale expression screening using 1D 1H-NMR and/or analytical HIC. This procedure is especially effective as a fast and inexpensive screen for the 'low hanging fruits' in structural genomics.

Unintended changes in protein expression revealed by proteomic analysis of seeds from transgenic pea expressing a bean alpha-amylase inhibitor gene.

Science.gov (United States)

Chen, Hancai; Bodulovic, Greg; Hall, Prudence J; Moore, Andy; Higgins, Thomas J V; Djordjevic, Michael A; Rolfe, Barry G

2009-09-01

Seeds of genetically modified (GM) peas (Pisum sativum L.) expressing the gene for alpha-amylase inhibitor-1 (alphaAI1) from the common bean (Phaseolus vulgaris L. cv. Tendergreen) exhibit resistance to the pea weevil (Bruchus pisorum). A proteomic analysis was carried out to compare seeds from GM pea lines expressing the bean alphaAI1 protein and the corresponding alphaAI1-free segregating lines and non-GM parental line to identify unintended alterations to the proteome of GM peas due to the introduction of the gene for alphaAI1. Proteomic analysis showed that in addition to the presence of alphaAI1, 33 other proteins were differentially accumulated in the alphaAI1-expressing GM lines compared with their non-GM parental line and these were grouped into five expression classes. Among these 33 proteins, only three were found to be associated with the expression of alphaAI1 in the GM pea lines. The accumulation of the remaining 30 proteins appears to be associated with Agrobacterium-mediated transformation events. Sixteen proteins were identified after MALDI-TOF-TOF analysis. About 56% of the identified proteins with altered accumulation in the GM pea were storage proteins including legumin, vicilin or convicilin, phaseolin, cupin and valosin-containing protein. Two proteins were uniquely expressed in the alphaAI1-expressing GM lines and one new protein was present in both the alphaAI1-expressing GM lines and their alphaAI1-free segregating lines, suggesting that both transgenesis and transformation events led to demonstrable changes in the proteomes of the GM lines tested.

Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

Directory of Open Access Journals (Sweden)

Paul Jean Etienne Jeszensky

2005-02-01

Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

Gene Expression Analysis of Plum pox virus (Sharka) Susceptibility/Resistance in Apricot (Prunus armeniaca L.).

Science.gov (United States)

Rubio, Manuel; Ballester, Ana Rosa; Olivares, Pedro Manuel; Castro de Moura, Manuel; Dicenta, Federico; Martínez-Gómez, Pedro

2015-01-01

RNA-Seq has proven to be a very powerful tool in the analysis of the Plum pox virus (PPV, sharka disease)/Prunus interaction. This technique is an important complementary tool to other means of studying genomics. In this work an analysis of gene expression of resistance/susceptibility to PPV in apricot is performed. RNA-Seq has been applied to analyse the gene expression changes induced by PPV infection in leaves from two full-sib apricot genotypes, "Rojo Pasión" and "Z506-7", resistant and susceptible to PPV, respectively. Transcriptomic analyses revealed the existence of more than 2,000 genes related to the pathogen response and resistance to PPV in apricot. These results showed that the response to infection by the virus in the susceptible genotype is associated with an induction of genes involved in pathogen resistance such as the allene oxide synthase, S-adenosylmethionine synthetase 2 and the major MLP-like protein 423. Over-expression of the Dicer protein 2a may indicate the suppression of a gene silencing mechanism of the plant by PPV HCPro and P1 PPV proteins. On the other hand, there were 164 genes involved in resistance mechanisms that have been identified in apricot, 49 of which are located in the PPVres region (scaffold 1 positions from 8,050,804 to 8,244,925), which is responsible for PPV resistance in apricot. Among these genes in apricot there are several MATH domain-containing genes, although other genes inside (Pleiotropic drug resistance 9 gene) or outside (CAP, Cysteine-rich secretory proteins, Antigen 5 and Pathogenesis-related 1 protein; and LEA, Late embryogenesis abundant protein) PPVres region could also be involved in the resistance.

Evaluation of schistosome promoter expression for transgenesis and genetic analysis.

Directory of Open Access Journals (Sweden)

Shuang Liang

Full Text Available Schistosome worms of the genus Schistosoma are the causative agents of schistosomiasis, a devastating parasitic disease affecting more than 240 million people worldwide. Schistosomes have complex life cycles, and have been challenging to manipulate genetically due to the dearth of molecular tools. Although the use of gene overexpression, gene knockouts or knockdowns are straight-forward genetic tools applied in many model systems, gene misexpression and genetic manipulation of schistosome genes in vivo has been exceptionally challenging, and plasmid based transfection inducing gene expression is limited. We recently reported the use of polyethyleneimine (PEI as a simple and effective method for schistosome transfection and gene expression. Here, we use PEI-mediated schistosome plasmid transgenesis to define and compare gene expression profiles from endogenous and nonendogenous promoters in the schistosomula stage of schistosomes that are potentially useful to misexpress (underexpress or overexpress gene product levels. In addition, we overexpress schistosome genes in vivo using a strong promoter and show plasmid-based misregulation of genes in schistosomes, producing a clear and distinct phenotype--death. These data focus on the schistosomula stage, but they foreshadow strong potential for genetic characterization of schistosome molecular pathways, and potential for use in overexpression screens and drug resistance studies in schistosomes using plasmid-based gene expression.

Exploratory Factor Analysis as a Construct Validation Tool: (Mis)applications in Applied Linguistics Research

Science.gov (United States)

Karami, Hossein

2015-01-01

Factor analysis has been frequently exploited in applied research to provide evidence about the underlying factors in various measurement instruments. A close inspection of a large number of studies published in leading applied linguistic journals shows that there is a misconception among applied linguists as to the relative merits of exploratory…

Anatomical specificity of vascular endothelial growth factor expression in glioblastomas: a voxel-based mapping analysis

Energy Technology Data Exchange (ETDEWEB)

Fan, Xing [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Wang, Yinyan [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Capital Medical University, Department of Neuropathology, Beijing Neurosurgical Institute, Beijing (China); Wang, Kai; Ma, Jun; Li, Shaowu [Capital Medical University, Department of Neuroradiology, Beijing Tiantan Hospital, Beijing (China); Liu, Shuai [Chinese Academy of Medical Sciences and Peking Union Medical College, Departments of Neurosurgery, Peking Union Medical College Hospital, Beijing (China); Liu, Yong [Chinese Academy of Sciences, Brainnetome Center, Institute of Automation, Beijing (China); Jiang, Tao [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Beijing Academy of Critical Illness in Brain, Department of Clinical Oncology, Beijing (China)

2016-01-15

The expression of vascular endothelial growth factor (VEGF) is a common genetic alteration in malignant gliomas and contributes to the angiogenesis of tumors. This study aimed to investigate the anatomical specificity of VEGF expression levels in glioblastomas using voxel-based neuroimaging analysis. Clinical information, MR scans, and immunohistochemistry stains of 209 patients with glioblastomas were reviewed. All tumor lesions were segmented manually and subsequently registered to standard brain space. Voxel-based regression analysis was performed to correlate the brain regions of tumor involvement with the level of VEGF expression. Brain regions identified as significantly associated with high or low VEGF expression were preserved following permutation correction. High VEGF expression was detected in 123 (58.9 %) of the 209 patients. Voxel-based statistical analysis demonstrated that high VEGF expression was more likely in tumors located in the left frontal lobe and the right caudate and low VEGF expression was more likely in tumors that occurred in the posterior region of the right lateral ventricle. Voxel-based neuroimaging analysis revealed the anatomic specificity of VEGF expression in glioblastoma, which may further our understanding of genetic heterogeneity during tumor origination. This finding provides primary theoretical support for potential future application of customized antiangiogenic therapy. (orig.)

Anatomical specificity of vascular endothelial growth factor expression in glioblastomas: a voxel-based mapping analysis

International Nuclear Information System (INIS)

Fan, Xing; Wang, Yinyan; Wang, Kai; Ma, Jun; Li, Shaowu; Liu, Shuai; Liu, Yong; Jiang, Tao

2016-01-01

The expression of vascular endothelial growth factor (VEGF) is a common genetic alteration in malignant gliomas and contributes to the angiogenesis of tumors. This study aimed to investigate the anatomical specificity of VEGF expression levels in glioblastomas using voxel-based neuroimaging analysis. Clinical information, MR scans, and immunohistochemistry stains of 209 patients with glioblastomas were reviewed. All tumor lesions were segmented manually and subsequently registered to standard brain space. Voxel-based regression analysis was performed to correlate the brain regions of tumor involvement with the level of VEGF expression. Brain regions identified as significantly associated with high or low VEGF expression were preserved following permutation correction. High VEGF expression was detected in 123 (58.9 %) of the 209 patients. Voxel-based statistical analysis demonstrated that high VEGF expression was more likely in tumors located in the left frontal lobe and the right caudate and low VEGF expression was more likely in tumors that occurred in the posterior region of the right lateral ventricle. Voxel-based neuroimaging analysis revealed the anatomic specificity of VEGF expression in glioblastoma, which may further our understanding of genetic heterogeneity during tumor origination. This finding provides primary theoretical support for potential future application of customized antiangiogenic therapy. (orig.)

[Expression profiles and bioinformatic analysis of miRNA in human dental pulp cells during endothelial differentiation].

Science.gov (United States)

Gong, Qimei; Jiang, Hongwei; Wang, Jinming; Ling, Junqi

2014-05-01

To investigate the differential expression profile and bioinformatic analysis of microRNA (miRNA) in human dental pulp cells (DPC) during endothelial differentiation. DPC were cultured in endothelial induction medium (50 µg/L vascular endothelial growth factor, 10 µg/L basic fibroblast growth factor and 2% fetal calf serum) for 7 days. Meanwhile non-induced DPC were used as control.Quantitative real-time PCR (qRT-PCR) was applied to detect vascular endothelial marker genes [CD31, von Willebrand factor (vWF) and vascular endothelial-cadherin (VE-cadherin)] and in vitro tube formation on matrigel was used to analyze the angiogenic ability of differentiated cells. And then miRNA expression profiles of DPC were examined using miRNA microarray and then the differentially expressed miRNA were validated by qRT-PCR. Furthermore, bioinformatic analysis was employed to predict the target genes of miRNA and to analyze the possible biological functions and signaling pathways that were involved in DPC after induction. The relative mRNA level of CD31, vWF and VE-cadherin in the control group were (3.48 ± 0.22) ×10(-4), (3.13 ± 0.31) ×10(-4) and (39.60 ± 2.36) ×10(-4), and (19.57 ± 2.20) ×10(-4), (48.13 ± 0.54) ×10(-4) and (228.00 ± 8.89) ×10(-4) in the induced group. The expressions of CD31, vWF and VE-cadherin were increased significantly in endothelial induced DPC compared to the control group (P functions, such as the regulation of transcription, cell motion, blood vessel morphogenesis, angiogenesis and cytoskeletal protein, and signaling pathways including the mitogen-activated protein kinase (MAPK) and the Wnt signaling pathway. The differential miRNA expression identified in this study may be involved in governing DPC endothelial differentiation, thus contributing to the future research on regulatory mechanisms in dental pulp angiogenesis.

Clinical Significance of Resistin Expression in Osteoarthritis: A Meta-Analysis

Directory of Open Access Journals (Sweden)

Xiao-Chuan Li

2014-01-01

Full Text Available Background. The objective of this study was to conduct a systematic review of literature evaluating human resistin expression as a diagnostic factor in osteoarthritis development and to quantify the overall diagnostic effect. Method. Relevant studies were identified and evaluated for quality through multiple search strategies. Studies analyzing resistin expression in the development of OA were eligible for inclusion. Data from eligible studies were extracted and included into the meta-analysis using a random-effects model. Results. Four case-control studies consisting of a total of 375 OA patients and 214 controls as well as three sex-stratified analyses composed of 53 males and 104 females were incorporated into our meta-analysis. Our results revealed that resistin levels were significantly higher in male OA subjects and OA patients overall. Country-stratified analysis yielded significantly different estimates in resistin levels between male OA subjects and female OA subjects in the Canadian subgroup but not among the French and USA subgroups. Based on the resistin levels in OA cases and controls, resistin levels were heightened in OA patients in the Dutch population. Conclusion. These results support the hypothesis that high expression of resistin represents a significant and reproducible marker of poor progression in OA patients, especially in males.

Applied linear algebra and matrix analysis

CERN Document Server

Shores, Thomas S

2018-01-01

In its second edition, this textbook offers a fresh approach to matrix and linear algebra. Its blend of theory, computational exercises, and analytical writing projects is designed to highlight the interplay between these aspects of an application. This approach places special emphasis on linear algebra as an experimental science that provides tools for solving concrete problems. The second edition’s revised text discusses applications of linear algebra like graph theory and network modeling methods used in Google’s PageRank algorithm. Other new materials include modeling examples of diffusive processes, linear programming, image processing, digital signal processing, and Fourier analysis. These topics are woven into the core material of Gaussian elimination and other matrix operations; eigenvalues, eigenvectors, and discrete dynamical systems; and the geometrical aspects of vector spaces. Intended for a one-semester undergraduate course without a strict calculus prerequisite, Applied Linear Algebra and M...

Prognostic value of Notch-1 expression in hepatocellular carcinoma: a meta-analysis

Directory of Open Access Journals (Sweden)

Wu T

2015-10-01

Full Text Available Tao Wu,1 Min Jiao,1 Li Jing,1 Min-Cong Wang,1 Hai-Feng Sun,2 Qing Li,1 Yi-Yang Bai,1 Yong-Chang Wei,1 Ke-Jun Nan,1 Hui Guo1 1Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, 2Department of Oncology, Shaanxi Cancer Hospital, Xi’an, People’s Republic of China Abstract: Association of Notch-1 expression with prognosis of patients with hepatocellular carcinoma (HCC remains controversial. We conducted a meta-analysis to reevaluate the association of Notch-1 expression with clinicopathological characteristics and prognosis of HCC. PubMed, Embase, Web of Science, and China National Knowledge Infrastructure were searched to look for relevant studies. The association between Notch-1 expression and clinicopathological parameters and overall survival (OS was then reassessed using the meta-analysis for odds ratio (OR or hazard ratio (HR and 95% confidence interval (CI. A total of seven studies, including 810 HCC patients, were eligible for the meta-analysis. Our data showed that high Notch-1 expression was able to predict poor OS (HR 1.50, 95% CI 1.17–1.83, P=0.0001. The pooled OR showed that high Notch-1 expression was significantly associated with tumor metastasis (OR 0.37, 95% CI 0.16–0.86, P=0.02 and tumor size >5 cm (OR 0.48, 95% CI 0.26–0.88, P=0.02. In contrast, there was no association between high Notch-1 expression and tumor differentiation, late TNM stage, tumor number, and portal vein invasion of HCC. In conclusion, Notch-1 overexpression might predict poorer survival and more aggressive behavior in patients with HCC. Keywords: hepatocellular carcinoma, Notch-1, prognosis, clinicopathological features, meta-analysis

EXP-PAC: providing comparative analysis and storage of next generation gene expression data.

Science.gov (United States)

Church, Philip C; Goscinski, Andrzej; Lefèvre, Christophe

2012-07-01

Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html). Copyright © 2012 Elsevier Inc. All rights reserved.

Expression analysis of argonaute, Dicer-like, and RNA-dependent ...

Indian Academy of Sciences (India)

DEFANG GAN

the first report of expression analysis of all CsDCL, CsAGO and CsRDR family genes in cucumber under .... tissues and organs were detected using online data and semi- ...... Wheeler B. S. 2013 Small RNAs, big impact: small RNA pathways.

Express-analysis of Radiocaesium Traces in Natural Water

International Nuclear Information System (INIS)

Remez, V.P.; Belyakova, E.G.

1999-01-01

To determine traces of radiocaesium in water solution, the sorbent on the base of ferric potassium hexacyanoferrate on cellulose carrier ANFEZH was worked out. The sorbent is capable to extract effectively the isotopes of caesium from various natural solutions (fresh and sea water, milk, juices and so on). The usage of sorbent allows practically completely concentrate the isotopes of caesium from water samples with the volume of tens and hundreds litres. The sorbent in quantity of 50-500 grams allows to extract 98±1% of caesium from natural water samples with the volume up to 1000 litres during 1-5 hours. The usage of this sorbent allowed to conduct the express analysis of multiple bore holes within the area of 30 km of Chernobyl Skaya NPP , drinking water and milk in the regions of Belorussia, Ukraine and Russia, hit by Chernobyl disaster and around NPP in Russia and America. The use of this express analysis reduced the time and required labour as compared with to precipitation methods

Identification and expression analysis of genes associated with bovine blastocyst formation

Directory of Open Access Journals (Sweden)

Van Zeveren Alex

2007-06-01

Full Text Available Abstract Background Normal preimplantation embryo development encompasses a series of events including first cleavage division, activation of the embryonic genome, compaction and blastocyst formation. First lineage differentiation starts at the blastocyst stage with the formation of the trophectoderm and the inner cell mass. The main objective of this study was the detection, identification and expression analysis of genes associated with blastocyst formation in order to help us better understand this process. This information could lead to improvements of in vitro embryo production procedures. Results A subtractive cDNA library was constructed enriched for transcripts preferentially expressed at the blastocyst stage compared to the 2-cell and 8-cell stage. Sequence information was obtained for 65 randomly selected clones. The RNA expression levels of 12 candidate genes were determined throughout 3 stages of preimplantation embryo development (2-cell, 8-cell and blastocyst and compared with the RNA expression levels of in vivo "golden standard" embryos using real-time PCR. The RNA expression profiles of 9 (75% transcripts (KRT18, FN1, MYL6, ATP1B3, FTH1, HINT1, SLC25A5, ATP6V0B, RPL10 were in agreement with the subtractive cDNA cloning approach, whereas for the remaining 3 (25% (ACTN1, COPE, EEF1A1 the RNA expression level was equal or even higher at the earlier developmental stages compared to the blastocyst stage. Moreover, significant differences in RNA expression levels were observed between in vitro and in vivo produced embryos. By immunofluorescent labelling, the protein expression of KRT18, FN1 and MYL6 was determined throughout bovine preimplantation embryo development and showed the same pattern as the RNA expression analyses. Conclusion By subtractive cDNA cloning, candidate genes involved in blastocyst formation were identified. For several candidate genes, important differences in gene expression were observed between in vivo and in

An Objective Comparison of Applied Behavior Analysis and Organizational Behavior Management Research

Science.gov (United States)

Culig, Kathryn M.; Dickinson, Alyce M.; McGee, Heather M.; Austin, John

2005-01-01

This paper presents an objective review, analysis, and comparison of empirical studies targeting the behavior of adults published in Journal of Applied Behavior Analysis (JABA) and Journal of Organizational Behavior Management (JOBM) between 1997 and 2001. The purpose of the comparisons was to identify similarities and differences with respect to…

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.

2013-07-18

The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

USAGE: a web-based approach towards the analysis of SAGE data. Serial Analysis of Gene Expression

NARCIS (Netherlands)

van Kampen, A. H.; van Schaik, B. D.; Pauws, E.; Michiels, E. M.; Ruijter, J. M.; Caron, H. N.; Versteeg, R.; Heisterkamp, S. H.; Leunissen, J. A.; Baas, F.; van der Mee, M.

2000-01-01

MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should

Expression analysis of NOS family and HSP genes during thermal stress in goat ( Capra hircus)

Science.gov (United States)

Yadav, Vijay Pratap; Dangi, Satyaveer Singh; Chouhan, Vikrant Singh; Gupta, Mahesh; Dangi, Saroj K.; Singh, Gyanendra; Maurya, Vijay Prakash; Kumar, Puneet; Sarkar, Mihir

2016-03-01

Approximately 50 genes other than heat shock protein (HSP) expression changes during thermal stress. These genes like nitric oxide synthase (NOS) need proper attention and investigation to find out their possible role in the adaptation to thermal stress in animals. So, the present study was undertaken to demonstrate the expressions of inducible form type II NOS (iNOS), endothelial type III NOS (eNOS), constitutively expressed enzyme NOS (cNOS), HSP70, and HSP90 in peripheral blood mononuclear cells (PBMCs) during different seasons in Barbari goats. Real-time polymerase chain reaction, western blot, and immunocytochemistry were applied to investigate messenger RNA (mRNA) expression, protein expression, and immunolocalization of examined factors. The mRNA and protein expressions of iNOS, eNOS, cNOS, HSP70, and HSP90 were significantly higher ( P goats.

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.

Comparative transcriptome analysis reveals differentially expressed genes associated with sex expression in garden asparagus (Asparagus officinalis).

Science.gov (United States)

Li, Shu-Fen; Zhang, Guo-Jun; Zhang, Xue-Jin; Yuan, Jin-Hong; Deng, Chuan-Liang; Gao, Wu-Jun

2017-08-22

Garden asparagus (Asparagus officinalis) is a highly valuable vegetable crop of commercial and nutritional interest. It is also commonly used to investigate the mechanisms of sex determination and differentiation in plants. However, the sex expression mechanisms in asparagus remain poorly understood. De novo transcriptome sequencing via Illumina paired-end sequencing revealed more than 26 billion bases of high-quality sequence data from male and female asparagus flower buds. A total of 72,626 unigenes with an average length of 979 bp were assembled. In comparative transcriptome analysis, 4876 differentially expressed genes (DEGs) were identified in the possible sex-determining stage of female and male/supermale flower buds. Of these DEGs, 433, including 285 male/supermale-biased and 149 female-biased genes, were annotated as flower related. Of the male/supermale-biased flower-related genes, 102 were probably involved in anther development. In addition, 43 DEGs implicated in hormone response and biosynthesis putatively associated with sex expression and reproduction were discovered. Moreover, 128 transcription factor (TF)-related genes belonging to various families were found to be differentially expressed, and this finding implied the essential roles of TF in sex determination or differentiation in asparagus. Correlation analysis indicated that miRNA-DEG pairs were also implicated in asparagus sexual development. Our study identified a large number of DEGs involved in the sex expression and reproduction of asparagus, including known genes participating in plant reproduction, plant hormone signaling, TF encoding, and genes with unclear functions. We also found that miRNAs might be involved in the sex differentiation process. Our study could provide a valuable basis for further investigations on the regulatory networks of sex determination and differentiation in asparagus and facilitate further genetic and genomic studies on this dioecious species.

Systematic analysis of gene expression pattern in has-miR-197 over-expressed human uterine leiomyoma cells.

Science.gov (United States)

Ling, Jing; Wu, Xiaoli; Fu, Ziyi; Tan, Jie; Xu, Qing

2015-10-01

Our previous study showed that the expression of miR-197 in leiomyoma was down-regulated compared with myometrium. Further, miR-197 has been identified to affect uterine leiomyoma cell proliferation, apoptosis, and metastasis ability, though the responsible molecular mechanism has not been well elucidated. In this study, we sought to determine the expression patterns of miR-197 targeted genes and to explore their potential functions, participating Pathways and the networks that are involved in the biological behavior of human uterine leiomyoma. After transfection of human uterine leiomyoma cells with miR-197, we confirmed the expression level of miR-197 using quantitative real-time PCR (qRT-PCR), and we detected the gene expression profiles after miR-197 over-expression through DNA microarray analysis. Further, we performed GO and Pathway analysis. The dominantly dys-regulated genes, which were up- or down-regulated by more than 10-fold, compared with parental cells, were confirmed using qRT-PCR technology. Compared with the control group, miR-197 was up-regulated by 30-fold after miR-197 lentiviral transfection. The microarray data showed that 872 genes were dys-regulated by more than 2-fold in human uterine leiomyoma cells after miR-197 overexpression, including 537 up-regulated and 335 down-regulated genes. The GO analysis indicated that the dys-regulated genes were primarily involved in response to stimuli, multicellular organ processes, and the signaling of biological progression. Further, Pathway analysis data showed that these genes participated in regulating several signaling Pathways, including the JAK/STAT signaling Pathway, the Toll-like receptor signaling Pathway, and cytokine-cytokine receptor interaction. The qRT-PCR results confirmed that 17 of the 66 selected genes, which were up- or down-regulated more than 10-fold by miR-197, were consistent with the microarray results, including tumorigenesis-related genes, such as DRT7, SLC549, SFMBT2, FLJ37956

PRO-ELICERE: A Hazard Analysis Automation Process Applied to Space Systems

Directory of Open Access Journals (Sweden)

Tharcius Augusto Pivetta

2016-07-01

Full Text Available In the last decades, critical systems have increasingly been developed using computers and software even in space area, where the project approach is usually very conservative. In the projects of rockets, satellites and its facilities, like ground support systems, simulators, among other critical operations for the space mission, it must be applied a hazard analysis. The ELICERE process was created to perform a hazard analysis mainly over computer critical systems, in order to define or evaluate its safety and dependability requirements, strongly based on Hazards and Operability Study and Failure Mode and Effect Analysis techniques. It aims to improve the project design or understand the potential hazards of existing systems improving their functions related to functional or non-functional requirements. Then, the main goal of the ELICERE process is to ensure the safety and dependability goals of a space mission. The process, at the beginning, was created to operate manually in a gradual way. Nowadays, a software tool called PRO-ELICERE was developed, in such a way to facilitate the analysis process and store the results for reuse in another system analysis. To understand how ELICERE works and its tool, a small example of space study case was applied, based on a hypothetical rocket of the Cruzeiro do Sul family, developed by the Instituto de Aeronáutica e Espaço in Brazil.

Molecular cloning and expression analysis of a zeta-class ...

African Journals Online (AJOL)

Jane

2011-07-27

Jul 27, 2011 ... sugar-signalling pathway (Chi et al., 2010). All the earlier mentioned ... real-time qPCR analysis was the ABI PRISM7500 real-time PCR system. ... Construction of prokaryotic expression vector of Sc-GST gene. pET29a (+) ...

How Has Applied Behavior Analysis and Behavior Therapy Changed?: An Historical Analysis of Journals

Science.gov (United States)

O'Donohue, William; Fryling, Mitch

2007-01-01

Applied behavior analysis and behavior therapy are now nearly a half century old. It is interesting to ask if and how these disciplines have changed over time, particularly regarding some of their key internal controversies (e.g., role of cognitions). We examined the first five years and the 2000-2004 five year period of the "Journal of Applied…

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

International Nuclear Information System (INIS)

Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

2008-01-01

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

Directory of Open Access Journals (Sweden)

Ergul Gulusan

2008-12-01

Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

Facial Expressivity at 4 Months: A Context by Expression Analysis.

Science.gov (United States)

Bennett, David S; Bendersky, Margaret; Lewis, Michael

2002-01-01

The specificity predicted by differential emotions theory (DET) for early facial expressions in response to 5 different eliciting situations was studied in a sample of 4-month-old infants (n = 150). Infants were videotaped during tickle, sour taste, jack-in-the-box, arm restraint, and masked-stranger situations and their expressions were coded second by second. Infants showed a variety of facial expressions in each situation; however, more infants exhibited positive (joy and surprise) than negative expressions (anger, disgust, fear, and sadness) across all situations except sour taste. Consistent with DET-predicted specificity, joy expressions were the most common in response to tickling, and were less common in response to other situations. Surprise expressions were the most common in response to the jack-in-the-box, as predicted, but also were the most common in response to the arm restraint and masked-stranger situations, indicating a lack of specificity. No evidence of predicted specificity was found for anger, disgust, fear, and sadness expressions. Evidence of individual differences in expressivity within situations, as well as stability in the pattern across situations, underscores the need to examine both child and contextual factors in studying emotional development. The results provide little support for the DET postulate of situational specificity and suggest that a synthesis of differential emotions and dynamic systems theories of emotional expression should be considered.

Gene expression analysis of FABP4 in gastric cancer

Directory of Open Access Journals (Sweden)

Abdulkarim Yasin Karim

2016-06-01

Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252

Microarray Expression Profile and Functional Analysis of Circular RNAs in Osteosarcoma

Directory of Open Access Journals (Sweden)

Weihai Liu

2017-09-01

Full Text Available Background/Aims: Osteosarcoma (OS is the most common primary malignant bone tumor in children and adolescents. However, the molecular mechanisms regulating osteosarcoma tumorigenesis and progression are still poorly understood. Circular RNAs (circRNAs have been identified as microRNA sponges and are involved in many important biological processes. This study aims to investigate the global changes in the expression pattern of circRNAs in osteosarcoma and provide a comprehensive understanding of differentially expressed circRNAs. Methods: Microarray based circRNA expression was determined in osteosarcoma cell lines and compared with hFOB1.19, which was used as the normal control. We confirmed the microarray data by real time-qPCR in both osteosarcoma cell lines and tissues. The circRNA/microRNA/mRNA interaction network was predicted using bioinformatics. Gene Ontology analysis and 4 annotation tools for pathway analysis (KEGG, Biocarta, PANTHER and Reactome were used to predict the functions of differentially expressed circRNAs. Results: We revealed a number of differentially expressed circRNAs and 12 of them were confirmed, which suggests a potential role of circRNAs in OS. Among these differentially expressed circRNAs, hsa_circRNA_103801 was up-regulated in both osteosarcoma cell lines and tissues, while hsa_circRNA_104980 was down-regulated. The most likely potential target miRNAs for hsa_circRNA_103801 include hsa-miR-370-3p, hsa-miR-338-3p and hsa-miR-877-3p, while the most potential target miRNAs of hsa_circRNA_104980 consist of hsa-miR-1298-3p and hsa-miR-660-3p. Functional analysis found that hsa_circRNA_103801 was involved in pathways in cancer, such as the HIF-1, VEGF and angiogenesis pathway, the Rap1 signaling pathway and the PI3K-Akt signaling pathway, while hsa_circRNA_104980 was related to some pathways such as the tight junction pathway. Conclusions: This study has identified the comprehensive expression profile of circRNAs in

Preliminary Hazard Analysis applied to Uranium Hexafluoride - UF6 production plant

International Nuclear Information System (INIS)

Tomzhinsky, David; Bichmacher, Ricardo; Braganca Junior, Alvaro; Peixoto, Orpet Jose

1996-01-01

The purpose of this paper is to present the results of the Preliminary hazard Analysis applied to the UF 6 Production Process, which is part of the UF 6 Conversion Plant. The Conversion Plant has designed to produce a high purified UF 6 in accordance with the nuclear grade standards. This Preliminary Hazard Analysis is the first step in the Risk Management Studies, which are under current development. The analysis evaluated the impact originated from the production process in the plant operators, members of public, equipment, systems and installations as well as the environment. (author)

Fatigue Analysis of Tubesheet/Shell Juncture Applying the Mitigation Factor for Over-conservatism

International Nuclear Information System (INIS)

Kang, Deog Ji; Kim, Kyu Hyoung; Lee, Jae Gon

2009-01-01

If the environmental fatigue requirements are applied to the primary components of a nuclear power plant, to which the present ASME Code fatigue curves are applied, some locations with high level CUF (Cumulative Usage Factor) are anticipated not to meet the code criteria. The application of environmental fatigue damage is still particularly controversial for plants with 60-year design lives. Therefore, it is need to develop a detailed fatigue analysis procedure to identify the conservatisms in the procedure and to lower the cumulative usage factor. Several factors are being considered to mitigate the conservatism such as three-dimensional finite element modeling. In the present analysis, actual pressure transient data instead of conservative maximum and minimum pressure data was applied as one of mitigation factors. Unlike in the general method, individual transient events were considered instead of the grouped transient events. The tubesheet/shell juncture in the steam generator assembly is the one of the weak locations and was, therefore, selected as a target to evaluate the mitigation factor in the present analysis

Applied environmetrics. Simulation applied to the physical environment

Energy Technology Data Exchange (ETDEWEB)

Beer, T

1988-02-01

Environmetrics is the application of quantitative methods to all aspects of the social and natural environment. This includes forecasting, mathematical modelling, data analysis, and statistics. Applied Environmetrics as a discipline involves the analysis of environmental data through the use of packaged, or specially designed computer software. Two case studies of recent implementations of applied environmetrics within the Australian mining industry are dealt with. 3 figs., 5 refs.

Expression cartography of human tissues using self organizing maps

Directory of Open Access Journals (Sweden)

Löffler Markus

2011-07-01

Full Text Available Abstract Background Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs. SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand. Results The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues. SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues

Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response

Directory of Open Access Journals (Sweden)

Nasrine Bendjilali

2017-01-01

Full Text Available Many cells experience hypoxia, or low oxygen, and respond by dramatically altering gene expression. In the yeast Saccharomyces cerevisiae, genes that respond are required for many oxygen-dependent cellular processes, such as respiration, biosynthesis, and redox regulation. To more fully characterize the global response to hypoxia, we exposed yeast to hypoxic conditions, extracted RNA at different times, and performed RNA sequencing (RNA-seq analysis. Time-course statistical analysis revealed hundreds of genes that changed expression by up to 550-fold. The genes responded with varying kinetics suggesting that multiple regulatory pathways are involved. We identified most known oxygen-regulated genes and also uncovered new regulated genes. Reverse transcription-quantitative PCR (RT-qPCR analysis confirmed that the lysine methyltransferase EFM6 and the recombinase DMC1, both conserved in humans, are indeed oxygen-responsive. Looking more broadly, oxygen-regulated genes participate in expected processes like respiration and lipid metabolism, but also in unexpected processes like amino acid and vitamin metabolism. Using principle component analysis, we discovered that the hypoxic response largely occurs during the first 2 hr and then a new steady-state expression state is achieved. Moreover, we show that the oxygen-dependent genes are not part of the previously described environmental stress response (ESR consisting of genes that respond to diverse types of stress. While hypoxia appears to cause a transient stress, the hypoxic response is mostly characterized by a transition to a new state of gene expression. In summary, our results reveal that hypoxia causes widespread and complex changes in gene expression to prepare the cell to function with little or no oxygen.

Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response.

Science.gov (United States)

Bendjilali, Nasrine; MacLeon, Samuel; Kalra, Gurmannat; Willis, Stephen D; Hossian, A K M Nawshad; Avery, Erica; Wojtowicz, Olivia; Hickman, Mark J

2017-01-05

Many cells experience hypoxia, or low oxygen, and respond by dramatically altering gene expression. In the yeast Saccharomyces cerevisiae, genes that respond are required for many oxygen-dependent cellular processes, such as respiration, biosynthesis, and redox regulation. To more fully characterize the global response to hypoxia, we exposed yeast to hypoxic conditions, extracted RNA at different times, and performed RNA sequencing (RNA-seq) analysis. Time-course statistical analysis revealed hundreds of genes that changed expression by up to 550-fold. The genes responded with varying kinetics suggesting that multiple regulatory pathways are involved. We identified most known oxygen-regulated genes and also uncovered new regulated genes. Reverse transcription-quantitative PCR (RT-qPCR) analysis confirmed that the lysine methyltransferase EFM6 and the recombinase DMC1, both conserved in humans, are indeed oxygen-responsive. Looking more broadly, oxygen-regulated genes participate in expected processes like respiration and lipid metabolism, but also in unexpected processes like amino acid and vitamin metabolism. Using principle component analysis, we discovered that the hypoxic response largely occurs during the first 2 hr and then a new steady-state expression state is achieved. Moreover, we show that the oxygen-dependent genes are not part of the previously described environmental stress response (ESR) consisting of genes that respond to diverse types of stress. While hypoxia appears to cause a transient stress, the hypoxic response is mostly characterized by a transition to a new state of gene expression. In summary, our results reveal that hypoxia causes widespread and complex changes in gene expression to prepare the cell to function with little or no oxygen. Copyright © 2017 Bendjilali et al.

Expression analysis of G Protein-Coupled Receptors in mouse macrophages.

Science.gov (United States)

Lattin, Jane E; Schroder, Kate; Su, Andrew I; Walker, John R; Zhang, Jie; Wiltshire, Tim; Saijo, Kaoru; Glass, Christopher K; Hume, David A; Kellie, Stuart; Sweet, Matthew J

2008-04-29

Monocytes and macrophages express an extensive repertoire of G Protein-Coupled Receptors (GPCRs) that regulate inflammation and immunity. In this study we performed a systematic micro-array analysis of GPCR expression in primary mouse macrophages to identify family members that are either enriched in macrophages compared to a panel of other cell types, or are regulated by an inflammatory stimulus, the bacterial product lipopolysaccharide (LPS). Several members of the P2RY family had striking expression patterns in macrophages; P2ry6 mRNA was essentially expressed in a macrophage-specific fashion, whilst P2ry1 and P2ry5 mRNA levels were strongly down-regulated by LPS. Expression of several other GPCRs was either restricted to macrophages (e.g. Gpr84) or to both macrophages and neural tissues (e.g. P2ry12, Gpr85). The GPCR repertoire expressed by bone marrow-derived macrophages and thioglycollate-elicited peritoneal macrophages had some commonality, but there were also several GPCRs preferentially expressed by either cell population. The constitutive or regulated expression in macrophages of several GPCRs identified in this study has not previously been described. Future studies on such GPCRs and their agonists are likely to provide important insights into macrophage biology, as well as novel inflammatory pathways that could be future targets for drug discovery.

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.

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.

Gene Expression Analysis of Plum pox virus (Sharka Susceptibility/Resistance in Apricot (Prunus armeniaca L..

Directory of Open Access Journals (Sweden)

Manuel Rubio

Full Text Available RNA-Seq has proven to be a very powerful tool in the analysis of the Plum pox virus (PPV, sharka disease/Prunus interaction. This technique is an important complementary tool to other means of studying genomics. In this work an analysis of gene expression of resistance/susceptibility to PPV in apricot is performed. RNA-Seq has been applied to analyse the gene expression changes induced by PPV infection in leaves from two full-sib apricot genotypes, "Rojo Pasión" and "Z506-7", resistant and susceptible to PPV, respectively. Transcriptomic analyses revealed the existence of more than 2,000 genes related to the pathogen response and resistance to PPV in apricot. These results showed that the response to infection by the virus in the susceptible genotype is associated with an induction of genes involved in pathogen resistance such as the allene oxide synthase, S-adenosylmethionine synthetase 2 and the major MLP-like protein 423. Over-expression of the Dicer protein 2a may indicate the suppression of a gene silencing mechanism of the plant by PPV HCPro and P1 PPV proteins. On the other hand, there were 164 genes involved in resistance mechanisms that have been identified in apricot, 49 of which are located in the PPVres region (scaffold 1 positions from 8,050,804 to 8,244,925, which is responsible for PPV resistance in apricot. Among these genes in apricot there are several MATH domain-containing genes, although other genes inside (Pleiotropic drug resistance 9 gene or outside (CAP, Cysteine-rich secretory proteins, Antigen 5 and Pathogenesis-related 1 protein; and LEA, Late embryogenesis abundant protein PPVres region could also be involved in the resistance.

Single-cell multiple gene expression analysis based on single-molecule-detection microarray assay for multi-DNA determination

Energy Technology Data Exchange (ETDEWEB)

Li, Lu [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Xianwei [School of Life Sciences, Shandong University, Jinan 250100 (China); Zhang, Xiaoli [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Jinxing [School of Life Sciences, Shandong University, Jinan 250100 (China); Jin, Wenrui, E-mail: jwr@sdu.edu.cn [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China)

2015-01-07

Highlights: • A single-molecule-detection (SMD) microarray for 10 samples is fabricated. • The based-SMD microarray assay (SMA) can determine 8 DNAs for each sample. • The limit of detection of SMA is as low as 1.3 × 10{sup −16} mol L{sup −1}. • The SMA can be applied in single-cell multiple gene expression analysis. - Abstract: We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3 × 10{sup −16} mol L{sup −1}. The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three

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.

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.

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.

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

Science.gov (United States)

Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

2017-03-01

Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

Applying Pragmatics Principles for Interaction with Visual Analytics.

Science.gov (United States)

Hoque, Enamul; Setlur, Vidya; Tory, Melanie; Dykeman, Isaac

2018-01-01

Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH) genes in multiple human solid tumors: A systematic expression analysis

International Nuclear Information System (INIS)

Hamm, Alexander; Knuechel, Ruth; Dahl, Edgar; Veeck, Juergen; Bektas, Nuran; Wild, Peter J; Hartmann, Arndt; Heindrichs, Uwe; Kristiansen, Glen; Werbowetski-Ogilvie, Tamra; Del Maestro, Rolando

2008-01-01

The inter-alpha-trypsin inhibitors (ITI) are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by AMBP – and five homologous heavy chains (encoded by ITIH1, ITIH2, ITIH3, ITIH4, and ITIH5), contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis. We systematically investigated differential gene expression of the ITIH gene family, as well as AMBP and the interacting partner TNFAIP6 in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas) using cDNA dot blot analysis (Cancer Profiling Array, CPA), semiquantitative RT-PCR and immunohistochemistry. We found that ITIH genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, ITIH genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose ITIH2 expression in human breast cancer. Loss of ITIH2 expression in 70% of cases (n = 50, CPA) could be confirmed by real-time PCR in an additional set of breast cancers (n = 36). Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p < 0.001) between ITIH2 expression and estrogen receptor (ER) expression indicating that ER may be involved in the regulation of this ECM molecule. Altogether, this is the first systematic analysis on the differential expression of ITIH genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies

Comparative analysis of the PCA3 gene expression in sediments and exosomes isolated from urine

Directory of Open Access Journals (Sweden)

D. S. Mikhaylenko

2017-01-01

Full Text Available Introduction. Prostate cancer (PCa is one of the common oncological diseases in men. Expression of the PCA3 gene in urine is currently used as a molecular genetic marker of PCa.Objective: to comparative analysis of the PCA3 expression in urine sediments and exosomes for the determination of the biomaterial, which allows detecting the PCA3 expression in more efficient manner.Materials and methods. The 12 patients with different stages of PCa and 8 control samples were examined.Results. The diagnostic accuracy of the PCA3 gene expression analysis in this cohort exceeded 90 %. We had not obtained significant differences in the sensitivity and specificity of the PCA3 hyperexpression in the urine sediments compared with exosomes. This result indicates in favor to using urine sediment for the PCA3 analysis as a biomaterial with less time-consuming sample preparation, although the possible advantage of exosomes for the analysis of the expression marker panels requires further studies.

Applying Authentic Data Analysis in Learning Earth Atmosphere

Science.gov (United States)

Johan, H.; Suhandi, A.; Samsudin, A.; Wulan, A. R.

2017-09-01

The aim of this research was to develop earth science learning material especially earth atmosphere supported by science research with authentic data analysis to enhance reasoning through. Various earth and space science phenomenon require reasoning. This research used experimental research with one group pre test-post test design. 23 pre-service physics teacher participated in this research. Essay test was conducted to get data about reason ability. Essay test was analyzed quantitatively. Observation sheet was used to capture phenomena during learning process. The results showed that student’s reasoning ability improved from unidentified and no reasoning to evidence based reasoning and inductive/deductive rule-based reasoning. Authentic data was considered using Grid Analysis Display System (GrADS). Visualization from GrADS facilitated students to correlate the concepts and bring out real condition of nature in classroom activity. It also helped student to reason the phenomena related to earth and space science concept. It can be concluded that applying authentic data analysis in learning process can help to enhance students reasoning. This study is expected to help lecture to bring out result of geoscience research in learning process and facilitate student understand concepts.

Applying DEA sensitivity analysis to efficiency measurement of Vietnamese universities

Directory of Open Access Journals (Sweden)

Thi Thanh Huyen Nguyen

2015-11-01

Full Text Available The primary purpose of this study is to measure the technical efficiency of 30 doctorate-granting universities, the universities or the higher education institutes with PhD training programs, in Vietnam, applying the sensitivity analysis of data envelopment analysis (DEA. The study uses eight sets of input-output specifications using the replacement as well as aggregation/disaggregation of variables. The measurement results allow us to examine the sensitivity of the efficiency of these universities with the sets of variables. The findings also show the impact of variables on their efficiency and its “sustainability”.

The x-rays fluorescence applied to the analysis of alloys

International Nuclear Information System (INIS)

Gutierrez, D.A.

1997-01-01

This work is based on the utilization of the Fluorescence of X Rays. This technique of non destructive trial, has the purpose to establish a routine method, for the control of the conformation of industrial samples used. It makes an analysis with a combination of the algorithms of Rasberry-Heinrich and Claisse-Thinh. Besides, the numerical implementation of non usual techniques in this type of analysis. Such as the Linear Programming applied to the solution of super determined systems, of equations and the utilization of methods of relaxation to facilitate the convergence to the solutions. (author) [es

Analysis of Salmonella enterica serotype paratyphi A gene expression in the blood of bacteremic patients in Bangladesh.

Directory of Open Access Journals (Sweden)

Alaullah Sheikh

2010-12-01

Full Text Available Salmonella enterica serotype Paratyphi A is a human-restricted cause of paratyphoid fever, accounting for up to a fifth of all cases of enteric fever in Asia.In this work, we applied an RNA analysis method, Selective Capture of Transcribed Sequences (SCOTS, and cDNA hybridization-microarray technology to identify S. Paratyphi A transcripts expressed by bacteria in the blood of three patients in Bangladesh. In total, we detected 1,798 S. Paratyphi A mRNAs expressed in the blood of infected humans (43.9% of the ORFeome. Of these, we identified 868 in at least two patients, and 315 in all three patients. S. Paratyphi A transcripts identified in at least two patients encode proteins involved in energy metabolism, nutrient and iron acquisition, vitamin biosynthesis, stress responses, oxidative stress resistance, and pathogenesis. A number of detected transcripts are expressed from PhoP and SlyA-regulated genes associated with intra-macrophage survival, genes contained within Salmonella Pathogenicity Islands (SPIs 1-4, 6, 10, 13, and 16, as well as RpoS-regulated genes. The largest category of identified transcripts is that of encoding proteins with unknown function. When comparing levels of bacterial mRNA using in vivo samples collected from infected patients to samples from in vitro grown organisms, we found significant differences for 347, 391, and 456 S. Paratyphi A transcripts in each of three individual patients (approximately 9.7% of the ORFeome. Of these, expression of 194 transcripts (4.7% of ORFs was concordant in two or more patients, and 41 in all patients. Genes encoding these transcripts are contained within SPI-1, 3, 6 and 10, PhoP-regulated genes, involved in energy metabolism, nutrient acquisition, drug resistance, or uncharacterized genes. Using quantitative RT-PCR, we confirmed increased gene expression in vivo for a subset of these genes.To our knowledge, we describe the first microarray-based transcriptional analysis of a pathogen

A Case Study in the Misrepresentation of Applied Behavior Analysis in Autism: The Gernsbacher Lectures

Science.gov (United States)

Morris, Edward K

2009-01-01

I know that most men, including those at ease with problems of the greatest complexity, can seldom accept the simplest and most obvious truth if it be such as would oblige them to admit the falsity of conclusions which they have proudly taught to others, and which they have woven, thread by thread, into the fabrics of their life. (Tolstoy, 1894) This article presents a case study in the misrepresentation of applied behavior analysis for autism based on Morton Ann Gernsbacher's presentation of a lecture titled “The Science of Autism: Beyond the Myths and Misconceptions.” Her misrepresentations involve the characterization of applied behavior analysis, descriptions of practice guidelines, reviews of the treatment literature, presentations of the clinical trials research, and conclusions about those trials (e.g., children's improvements are due to development, not applied behavior analysis). The article also reviews applied behavior analysis' professional endorsements and research support, and addresses issues in professional conduct. It ends by noting the deleterious effects that misrepresenting any research on autism (e.g., biological, developmental, behavioral) have on our understanding and treating it in a transdisciplinary context. PMID:22478522

Expression analysis of dihydroflavonol 4-reductase genes in Petunia hybrida.

Science.gov (United States)

Chu, Y X; Chen, H R; Wu, A Z; Cai, R; Pan, J S

2015-05-12

Dihydroflavonol 4-reductase (DFR) genes from Rosa chinensis (Asn type) and Calibrachoa hybrida (Asp type), driven by a CaMV 35S promoter, were integrated into the petunia (Petunia hybrida) cultivar 9702. Exogenous DFR gene expression characteristics were similar to flower-color changes, and effects on anthocyanin concentration were observed in both types of DFR gene transformants. Expression analysis showed that exogenous DFR genes were expressed in all of the tissues, but the expression levels were significantly different. However, both of them exhibited a high expression level in petals that were starting to open. The introgression of DFR genes may significantly change DFR enzyme activity. Anthocyanin ultra-performance liquid chromatography results showed that anthocyanin concentrations changed according to DFR enzyme activity. Therefore, the change in flower color was probably the result of a DFR enzyme change. Pelargonidin 3-O-glucoside was found in two different transgenic petunias, indicating that both CaDFR and RoDFR could catalyze dihydrokaempferol. Our results also suggest that transgenic petunias with DFR gene of Asp type could biosynthesize pelargonidin 3-O-glucoside.

Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

Science.gov (United States)

Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

2012-03-01

High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

Differential expression analysis for RNAseq using Poisson mixed models.

Science.gov (United States)

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comprehensive analysis of gene expression patterns of hedgehog-related genes

Directory of Open Access Journals (Sweden)

Baillie David

2006-10-01

Full Text Available Abstract Background The Caenorhabditis elegans genome encodes ten proteins that share sequence similarity with the Hedgehog signaling molecule through their C-terminal autoprocessing Hint/Hog domain. These proteins contain novel N-terminal domains, and C. elegans encodes dozens of additional proteins containing only these N-terminal domains. These gene families are called warthog, groundhog, ground-like and quahog, collectively called hedgehog (hh-related genes. Previously, the expression pattern of seventeen genes was examined, which showed that they are primarily expressed in the ectoderm. Results With the completion of the C. elegans genome sequence in November 2002, we reexamined and identified 61 hh-related ORFs. Further, we identified 49 hh-related ORFs in C. briggsae. ORF analysis revealed that 30% of the genes still had errors in their predictions and we improved these predictions here. We performed a comprehensive expression analysis using GFP fusions of the putative intergenic regulatory sequence with one or two transgenic lines for most genes. The hh-related genes are expressed in one or a few of the following tissues: hypodermis, seam cells, excretory duct and pore cells, vulval epithelial cells, rectal epithelial cells, pharyngeal muscle or marginal cells, arcade cells, support cells of sensory organs, and neuronal cells. Using time-lapse recordings, we discovered that some hh-related genes are expressed in a cyclical fashion in phase with molting during larval development. We also generated several translational GFP fusions, but they did not show any subcellular localization. In addition, we also studied the expression patterns of two genes with similarity to Drosophila frizzled, T23D8.1 and F27E11.3A, and the ortholog of the Drosophila gene dally-like, gpn-1, which is a heparan sulfate proteoglycan. The two frizzled homologs are expressed in a few neurons in the head, and gpn-1 is expressed in the pharynx. Finally, we compare the

Cloning, characterization and expression analysis of porcine microRNAs

Directory of Open Access Journals (Sweden)

Desilva Udaya

2009-02-01

Full Text Available Abstract Background MicroRNAs (miRNAs are small ~22-nt regulatory RNAs that can silence target genes, by blocking their protein production or degrading the mRNAs. Pig is an important animal in the agriculture industry because of its utility in the meat production. Besides, pig has tremendous biomedical importance as a model organism because of its closer proximity to humans than the mouse model. Several hundreds of miRNAs have been identified from mammals, humans, mice and rats, but little is known about the miRNA component in the pig genome. Here, we adopted an experimental approach to identify conserved and unique miRNAs and characterize their expression patterns in diverse tissues of pig. Results By sequencing a small RNA library generated using pooled RNA from the pig heart, liver and thymus; we identified a total of 120 conserved miRNA homologs in pig. Expression analysis of conserved miRNAs in 14 different tissue types revealed heart-specific expression of miR-499 and miR-208 and liver-specific expression of miR-122. Additionally, miR-1 and miR-133 in the heart, miR-181a and miR-142-3p in the thymus, miR-194 in the liver, and miR-143 in the stomach showed the highest levels of expression. miR-22, miR-26b, miR-29c and miR-30c showed ubiquitous expression in diverse tissues. The expression patterns of pig-specific miRNAs also varied among the tissues examined. Conclusion Identification of 120 miRNAs and determination of the spatial expression patterns of a sub-set of these in the pig is a valuable resource for molecular biologists, breeders, and biomedical investigators interested in post-transcriptional gene regulation in pig and in related mammals, including humans.

Long SAGE analysis of genes differentially expressed in the midgut ...

African Journals Online (AJOL)

Long SAGE analysis of genes differentially expressed in the midgut and silk gland between the sexes of the silkwormBombyx mori. Liping Gan, Ying Wang, Jian Xi, Yanshan Niu, Hongyou Qin, Yanghu Sima, Shiqing Xu ...

A novel bi-level meta-analysis approach: applied to biological pathway analysis.

Science.gov (United States)

Nguyen, Tin; Tagett, Rebecca; Donato, Michele; Mitrea, Cristina; Draghici, Sorin

2016-02-01

The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. The R scripts are available on demand from the authors. sorin@wayne.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

Analysis of gene expression profile microarray data in complex regional pain syndrome.

Science.gov (United States)

Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

Expression analysis of the Theileria parva subtelomere-encoded variable secreted protein gene family.

Directory of Open Access Journals (Sweden)

Jacqueline Schmuckli-Maurer

Full Text Available The intracellular protozoan parasite Theileria parva transforms bovine lymphocytes inducing uncontrolled proliferation. Proteins released from the parasite are assumed to contribute to phenotypic changes of the host cell and parasite persistence. With 85 members, genes encoding subtelomeric variable secreted proteins (SVSPs form the largest gene family in T. parva. The majority of SVSPs contain predicted signal peptides, suggesting secretion into the host cell cytoplasm.We analysed SVSP expression in T. parva-transformed cell lines established in vitro by infection of T or B lymphocytes with cloned T. parva parasites. Microarray and quantitative real-time PCR analysis revealed mRNA expression for a wide range of SVSP genes. The pattern of mRNA expression was largely defined by the parasite genotype and not by host background or cell type, and found to be relatively stable in vitro over a period of two months. Interestingly, immunofluorescence analysis carried out on cell lines established from a cloned parasite showed that expression of a single SVSP encoded by TP03_0882 is limited to only a small percentage of parasites. Epitope-tagged TP03_0882 expressed in mammalian cells was found to translocate into the nucleus, a process that could be attributed to two different nuclear localisation signals.Our analysis reveals a complex pattern of Theileria SVSP mRNA expression, which depends on the parasite genotype. Whereas in cell lines established from a cloned parasite transcripts can be found corresponding to a wide range of SVSP genes, only a minority of parasites appear to express a particular SVSP protein. The fact that a number of SVSPs contain functional nuclear localisation signals suggests that proteins released from the parasite could contribute to phenotypic changes of the host cell. This initial characterisation will facilitate future studies on the regulation of SVSP gene expression and the potential biological role of these enigmatic

Serial analysis of gene expression in the silkworm, Bombyx mori.

Science.gov (United States)

Huang, Jianhua; Miao, Xuexia; Jin, Weirong; Couble, Pierre; Mita, Kasuei; Zhang, Yong; Liu, Wenbin; Zhuang, Leijun; Shen, Yan; Keime, Celine; Gandrillon, Olivier; Brouilly, Patrick; Briolay, Jerome; Zhao, Guoping; Huang, Yongping

2005-08-01

The silkworm Bombyx mori is one of the most economically important insects and serves as a model for Lepidoptera insects. We used serial analysis of gene expression (SAGE) to derive profiles of expressed genes during the developmental life cycle of the silkworm and to create a reference for understanding silkworm metamorphosis. We generated four SAGE libraries, one from each of the four developmental stages of the silkworm. In total we obtained 257,964 SAGE tags, of which 39,485 were unique tags. Sorted by copy number, 14.1% of the unique tags were detected at a median to high level (five or more copies), 24.2% at lower levels (two to four copies), and 61.7% as single copies. Using a basic local alignment search tool on the EST database, 35% of the tags matched known silkworm expressed sequence tags. SAGE demonstrated that a number of the genes were up- or down-regulated during the four developmental phases of the egg, larva, pupa, and adult. Furthermore, we found that the generation of longer cDNA fragments from SAGE tags constituted the most efficient method of gene identification, which facilitated the analysis of a large number of unknown genes.

Common cause evaluations in applied risk analysis of nuclear power plants

International Nuclear Information System (INIS)

Taniguchi, T.; Ligon, D.; Stamatelatos, M.

1983-04-01

Qualitative and quantitative approaches were developed for the evaluation of common cause failures (CCFs) in nuclear power plants and were applied to the analysis of the auxiliary feedwater systems of several pressurized water reactors (PWRs). Key CCF variables were identified through a survey of experts in the field and a review of failure experience in operating PWRs. These variables were classified into categories of high, medium, and low defense against a CCF. Based on the results, a checklist was developed for analyzing CCFs of systems. Several known techniques for quantifying CCFs were also reviewed. The information provided valuable insights in the development of a new model for estimating CCF probabilities, which is an extension of and improvement over the Beta Factor method. As applied to the analysis of the PWR auxiliary feedwater systems, the method yielded much more realistic values than the original Beta Factor method for a one-out-of-three system

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

Science.gov (United States)

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Elucidating gene function and function evolution through comparison of co-expression networks in plants

Directory of Open Access Journals (Sweden)

Marek eMutwil

2014-08-01

Full Text Available The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23. In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We show that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that, in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.

German taxi drivers' experiences and expressions of driving anger: Are the driving anger scale and the driving anger expression inventory valid measures?

Science.gov (United States)

Brandenburg, Stefan; Oehl, Michael; Seigies, Kristin

2017-11-17

The objective of this article was 2-fold: firstly, we wanted to examine whether the original Driving Anger Scale (DAS) and the original Driving Anger Expression Inventory (DAX) apply to German professional taxi drivers because these scales have previously been given to professional and particularly to nonprofessional drivers in different countries. Secondly, we wanted to examine possible differences in driving anger experience and expression between professional German taxi drivers and nonprofessional German drivers. We applied German versions of the DAS, the DAX, and the State-Trait Anger Expression Inventory (STAXI) to a sample of 138 professional German taxi drivers. We then compared their ratings to the ratings of a sample of 1,136 nonprofessional German drivers (Oehl and Brandenburg n.d. ). Regarding our first objective, confirmatory factor analysis shows that the model fit of the DAS is better for nonprofessional drivers than for professional drivers. The DAX applies neither to professional nor to nonprofessional German drivers properly. Consequently, we suggest modified shorter versions of both scales for professional drivers. The STAXI applies to both professional and nonprofessional drivers. With respect to our second objective, we show that professional drivers experience significantly less driving anger than nonprofessional drivers, but they express more driving anger. We conclude that the STAXI can be applied to professional German taxi drivers. In contrast, for the DAS and the DAX we found particular shorter versions for professional taxi drivers. Especially for the DAX, most statements were too strong for German drivers to agree to. They do not show behaviors related to driving anger expression as they are described in the DAX. These problems with the original American DAX items are in line with several other studies in different countries. Future investigations should examine whether (professional) drivers from further countries express their anger

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

Science.gov (United States)

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

Clinical Omics Analysis of Colorectal Cancer Incorporating Copy Number Aberrations and Gene Expression Data

Directory of Open Access Journals (Sweden)

Tsuyoshi Yoshida

2010-07-01

Full Text Available Background: Colorectal cancer (CRC is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an “omics” study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Materials and methods: Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. Result: We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene

Can Automated Facial Expression Analysis Show Differences Between Autism and Typical Functioning?

Science.gov (United States)

Borsos, Zsófia; Gyori, Miklos

2017-01-01

Exploratory analyses of emotional expressions using a commercially available facial expression recognition software are reported, from the context of a serious game for screening purposes. Our results are based on a comparative analysis of two matched groups of kindergarten-age children (high-functioning children with autism spectrum condition: n=13; typically developing children: n=13). Results indicate that this technology has the potential to identify autism-specific emotion expression features, and may play a role in affective diagnostic and assistive technologies.

Analysis of global gene expression in Brachypodium distachyon reveals extensive network plasticity in response to abiotic stress.

Directory of Open Access Journals (Sweden)

Henry D Priest

Full Text Available Brachypodium distachyon is a close relative of many important cereal crops. Abiotic stress tolerance has a significant impact on productivity of agriculturally important food and feedstock crops. Analysis of the transcriptome of Brachypodium after chilling, high-salinity, drought, and heat stresses revealed diverse differential expression of many transcripts. Weighted Gene Co-Expression Network Analysis revealed 22 distinct gene modules with specific profiles of expression under each stress. Promoter analysis implicated short DNA sequences directly upstream of module members in the regulation of 21 of 22 modules. Functional analysis of module members revealed enrichment in functional terms for 10 of 22 network modules. Analysis of condition-specific correlations between differentially expressed gene pairs revealed extensive plasticity in the expression relationships of gene pairs. Photosynthesis, cell cycle, and cell wall expression modules were down-regulated by all abiotic stresses. Modules which were up-regulated by each abiotic stress fell into diverse and unique gene ontology GO categories. This study provides genomics resources and improves our understanding of abiotic stress responses of Brachypodium.

Conversation after Right Hemisphere Brain Damage: Motivations for Applying Conversation Analysis

Science.gov (United States)

Barnes, Scott; Armstrong, Elizabeth

2010-01-01

Despite the well documented pragmatic deficits that can arise subsequent to Right Hemisphere Brain Damage (RHBD), few researchers have directly studied everyday conversations involving people with RHBD. In recent years, researchers have begun applying Conversation Analysis (CA) to the everyday talk of people with aphasia. This research programme…

Gene set analysis of the EADGENE chicken data-set

DEFF Research Database (Denmark)

Skarman, Axel; Jiang, Li; Hornshøj, Henrik

2009-01-01

 Abstract Background: Gene set analysis is considered to be a way of improving our biological interpretation of the observed expression patterns. This paper describes different methods applied to analyse expression data from a chicken DNA microarray dataset. Results: Applying different gene set...... analyses to the chicken expression data led to different ranking of the Gene Ontology terms tested. A method for prediction of possible annotations was applied. Conclusion: Biological interpretation based on gene set analyses dependent on the statistical method used. Methods for predicting the possible...

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes

International Nuclear Information System (INIS)

Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome

Cloning and expression analysis of a new anther-specific gene ...

Indian Academy of Sciences (India)

sequencing gene differential expression analysis (Chen et al. ... DNase digestion (Takara, Shiga, Japan), so that any remain- ..... ing the early moments of pollen germination (Guyon et al. 2000). The steady-state transcript level of PGPS/D3 ...

Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection

International Nuclear Information System (INIS)

Gregg, Jennifer L; Brown, Kathleen E; Mintz, Eric M; Piontkivska, Helen; Fraizer, Gail C

2010-01-01

The prostate gland represents a multifaceted system in which prostate epithelia and stroma have distinct physiological roles. To understand the interaction between stroma and glandular epithelia, it is essential to delineate the gene expression profiles of these two tissue types in prostate cancer. Most studies have compared tumor and normal samples by performing global expression analysis using a mixture of cell populations. This report presents the first study of prostate tumor tissue that examines patterns of differential expression between specific cell types using laser capture microdissection (LCM). LCM was used to isolate distinct cell-type populations and identify their gene expression differences using oligonucleotide microarrays. Ten differentially expressed genes were then analyzed in paired tumor and non-neoplastic prostate tissues by quantitative real-time PCR. Expression patterns of the transcription factors, WT1 and EGR1, were further compared in established prostate cell lines. WT1 protein expression was also examined in prostate tissue microarrays using immunohistochemistry. The two-step method of laser capture and microarray analysis identified nearly 500 genes whose expression levels were significantly different in prostate epithelial versus stromal tissues. Several genes expressed in epithelial cells (WT1, GATA2, and FGFR-3) were more highly expressed in neoplastic than in non-neoplastic tissues; conversely several genes expressed in stromal cells (CCL5, CXCL13, IGF-1, FGF-2, and IGFBP3) were more highly expressed in non-neoplastic than in neoplastic tissues. Notably, EGR1 was also differentially expressed between epithelial and stromal tissues. Expression of WT1 and EGR1 in cell lines was consistent with these patterns of differential expression. Importantly, WT1 protein expression was demonstrated in tumor tissues and was absent in normal and benign tissues. The prostate represents a complex mix of cell types and there is a need to analyze

Can Link Analysis Be Applied to Identify Behavioral Patterns in Train Recorder Data?

Science.gov (United States)

Strathie, Ailsa; Walker, Guy H

2016-03-01

A proof-of-concept analysis was conducted to establish whether link analysis could be applied to data from on-train recorders to detect patterns of behavior that could act as leading indicators of potential safety issues. On-train data recorders capture data about driving behavior on thousands of routine journeys every day and offer a source of untapped data that could be used to offer insights into human behavior. Data from 17 journeys undertaken by six drivers on the same route over a 16-hr period were analyzed using link analysis, and four key metrics were examined: number of links, network density, diameter, and sociometric status. The results established that link analysis can be usefully applied to data captured from on-vehicle recorders. The four metrics revealed key differences in normal driver behavior. These differences have promising construct validity as leading indicators. Link analysis is one method that could be usefully applied to exploit data routinely gathered by on-vehicle data recorders. It facilitates a proactive approach to safety based on leading indicators, offers a clearer understanding of what constitutes normal driving behavior, and identifies trends at the interface of people and systems, which is currently a key area of strategic risk. These research findings have direct applications in the field of transport data monitoring. They offer a means of automatically detecting patterns in driver behavior that could act as leading indicators of problems during operation and that could be used in the proactive monitoring of driver competence, risk management, and even infrastructure design. © 2015, Human Factors and Ergonomics Society.

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

Directory of Open Access Journals (Sweden)

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.

Integrative analysis of many weighted co-expression networks using tensor computation.

Directory of Open Access Journals (Sweden)

Wenyuan Li

2011-06-01

Full Text Available The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

Epithermal neutron activation analysis in applied microbiology

International Nuclear Information System (INIS)

Marina Frontasyeva

2012-01-01

Some results from applying epithermal neutron activation analysis at FLNP JINR, Dubna, Russia, in medical biotechnology, environmental biotechnology and industrial biotechnology are reviewed. In the biomedical experiments biomass from the blue-green alga Spirulina platensis (S. platensis) has been used as a matrix for the development of pharmaceutical substances containing such essential trace elements as selenium, chromium and iodine. The feasibility of target-oriented introduction of these elements into S. platensis biocomplexes retaining its protein composition and natural beneficial properties was shown. The absorption of mercury on growth dynamics of S. platensis and other bacterial strains was observed. Detoxification of Cr and Hg by Arthrobacter globiformis 151B was demonstrated. Microbial synthesis of technologically important silver nanoparticles by the novel actinomycete strain Streptomyces glaucus 71 MD and blue-green alga S. platensis were characterized by a combined use of transmission electron microscopy, scanning electron microscopy and energy-dispersive analysis of X-rays. It was established that the tested actinomycete S. glaucus 71 MD produces silver nanoparticles extracellularly when acted upon by the silver nitrate solution, which offers a great advantage over an intracellular process of synthesis from the point of view of applications. The synthesis of silver nanoparticles by S. platensis proceeded differently under the short-term and long-term silver action. (author)

Cloning and expression analysis of chalcone synthase gene from ...

Indian Academy of Sciences (India)

Expression analysis of CfCHS in different tissues and elicitor treatments showed that methyl jasmonate ... Journal of Genetics, DOI 10.1007/s12041-016-0680-8, Vol. 95, No. ... leaf of C. forskohlii. Quantitative real time RT-PCR was used ..... SGG acknowledges the financial support for this work from CSIR. 12th FYP project ...

Global Gene-Expression Analysis to Identify Differentially Expressed Genes Critical for the Heat Stress Response in Brassica rapa.

Directory of Open Access Journals (Sweden)

Xiangshu Dong

Full Text Available Genome-wide dissection of the heat stress response (HSR is necessary to overcome problems in crop production caused by global warming. To identify HSR genes, we profiled gene expression in two Chinese cabbage inbred lines with different thermotolerances, Chiifu and Kenshin. Many genes exhibited >2-fold changes in expression upon exposure to 0.5- 4 h at 45°C (high temperature, HT: 5.2% (2,142 genes in Chiifu and 3.7% (1,535 genes in Kenshin. The most enriched GO (Gene Ontology items included 'response to heat', 'response to reactive oxygen species (ROS', 'response to temperature stimulus', 'response to abiotic stimulus', and 'MAPKKK cascade'. In both lines, the genes most highly induced by HT encoded small heat shock proteins (Hsps and heat shock factor (Hsf-like proteins such as HsfB2A (Bra029292, whereas high-molecular weight Hsps were constitutively expressed. Other upstream HSR components were also up-regulated: ROS-scavenging genes like glutathione peroxidase 2 (BrGPX2, Bra022853, protein kinases, and phosphatases. Among heat stress (HS marker genes in Arabidopsis, only exportin 1A (XPO1A (Bra008580, Bra006382 can be applied to B. rapa for basal thermotolerance (BT and short-term acquired thermotolerance (SAT gene. CYP707A3 (Bra025083, Bra021965, which is involved in the dehydration response in Arabidopsis, was associated with membrane leakage in both lines following HS. Although many transcription factors (TF genes, including DREB2A (Bra005852, were involved in HS tolerance in both lines, Bra024224 (MYB41 and Bra021735 (a bZIP/AIR1 [Anthocyanin-Impaired-Response-1] were specific to Kenshin. Several candidate TFs involved in thermotolerance were confirmed as HSR genes by real-time PCR, and these assignments were further supported by promoter analysis. Although some of our findings are similar to those obtained using other plant species, clear differences in Brassica rapa reveal a distinct HSR in this species. Our data could also provide a

Real-time gene expression analysis in carp (Cyprinus carpio) skin: inflammatory responses to injury mimicking infection with ectoparasites

NARCIS (Netherlands)

Gonzalez, S.F.; Huising, M.O.; Stakauska, R.; Forlenza, M.; Verburg-van Kemenade, B.M.L.; Buchmann, K.; Nielsen, M.E.; Wiegertjes, G.F.

2007-01-01

We studied a predictive model of gene expression induced by mechanical injury of fish skin, to resolve the confounding effects on the immune system induced by injury and skin parasite-specific molecules. We applied real time quantitative PCR (RQ-PCR) to measure the expression of the pro-inflammatory

Prognostic significance of p53 expression in patients with esophageal cancer: a meta-analysis

International Nuclear Information System (INIS)

Wang, Lianghai; Yu, Xiaodan; Li, Jing; Zhang, Zhiyu; Hou, Jun; Li, Feng

2016-01-01

The prognostic value of p53 protein expression in esophageal cancer has been evaluated, but the results remain inconclusive and no consensus has yet been achieved. This meta-analysis was conducted to quantitatively assess the prognostic significance of p53 expression in esophageal cancer. Publications that assessed the clinical or prognostic significance of p53 expression in esophageal cancer and were published before July 1, 2015 were identified by searching the PubMed and EMBASE databases. A meta-analysis was performed to clarify the association between p53 expression and the clinical outcomes. A total of 36 publications met the criteria and included 4577 cases. Analysis of these data showed that p53 expression in esophageal cancer was significantly associated with poorer 5-year survival (RR = 1.30, 95 % CI: 1.11–1.51, P = 0.0008). Subgroup analyses according to histological type, continent of the patients, and cut-off value revealed the similar results. The results also indicated that p53 expression was highly associated with advanced TNM stages (I/II vs. III/IV, OR = 0.74, 95 % CI: 0.55–0.99, P = 0.04), lymph node metastasis (OR = 0.77, 95 % CI: 0.66–0.90, P = 0.001), and distant metastasis (OR = 0.46, 95 % CI: 0.26–0.80, P = 0.006). However, p53 expression in the included studies was not significantly associated with tumor size (≤ 5 cm vs. > 5 cm, OR = 1.13, 95 % CI: 0.92–1.40, P = 0.24), tumor location (upper + middle vs. lower, OR = 0.91, 95 % CI: 0.70–1.17, P = 0.45), grade of differentiation (well + moderate vs. poor, OR = 1.10, 95 % CI: 0.90–1.34, P = 0.35), and the depth of invasion (T1/T2 vs. T3/T4, OR = 0.86, 95 % CI: 0.71–1.03, P = 0.09). This meta-analysis showed that p53 expression may be a useful biomarker for predicting poorer prognosis in patients with esophageal cancer

Analysis of Mel-18 expression in prostate cancer tissues and correlation with clinicopathologic features.

Science.gov (United States)

Wang, Wei; Lin, Tianxin; Huang, Jian; Hu, Weilie; Xu, Kewei; Liu, Jun

2011-01-01

Mel-18 is a member of the polycomb group (PcG) of proteins, which are chromatin regulatory factors that play an important role in development and oncogenesis. This study was designed to investigate the clinical and prognostic significance of Mel-18 in the patients with prostate cancer. Immunostaining with Mel-18 specific antibodies was performed on paraffin sections from 202 patients. Correlations between Mel-18 and the Gleason grading system, clinical stage, serum prostate-specific antigen (PSA) levels, and age were evaluated. PSA recurrence in 76 patients who underwent radical prostatectomy and survival in 59 patients with metastases at diagnosis were analyzed to evaluate the influence of Mel-18 expression in cancer progression using Kaplan-Meier analysis and multivariate Cox regression analysis. Staining was seen in all prostatic tissues. Mel-18 expression was significantly reduced in the prostate cancer patients with PSA levels over 100 ng/ml (P=0.009), advanced clinical stage (>T4, N1, or M1 disease, P=0.029), higher Gleason grade or with a higher Gleason score (P=0.018) than in those with other clinicopathologic features. Negative expression of Mel-18 was associated with significantly higher rates of PSA recurrence after radical prostatectomy than with positive expression of Mel-18 (P = 0.029), and was an independent predictor of PSA recurrence (P=0.034, HR=2.143) in multivariate analysis. Similarly, metastatic prostate cancer patients with negative expression of Mel-18 showed significantly worse survival compared with the positive expression of Mel-18 (P=0.025). In multivariate analysis, negative expression of Mel-18 was an independent predictor of cancer-specific survival (P=0.024, HR=2.365). Our study provides important evidence for the recognition of Mel-18 as a tumor suppressor. The expression of Mel-18 showed potential as a prognostic marker for human prostate cancer. Copyright © 2011 Elsevier Inc. All rights reserved.

School-Wide PBIS: Extending the Impact of Applied Behavior Analysis. Why is This Important to Behavior Analysts?

Science.gov (United States)

Putnam, Robert F; Kincaid, Donald

2015-05-01

Horner and Sugai (2015) recently wrote a manuscript providing an overview of school-wide positive behavioral interventions and supports (PBIS) and why it is an example of applied behavior analysis at the scale of social importance. This paper will describe why school-wide PBIS is important to behavior analysts, how it helps promote applied behavior analysis in schools and other organizations, and how behavior analysts can use this framework to assist them in the promotion and implementation of applied behavior analysis at both at the school and organizational level, as well as, the classroom and individual level.

Classical linear-control analysis applied to business-cycle dynamics and stability

Science.gov (United States)

Wingrove, R. C.

1983-01-01

Linear control analysis is applied as an aid in understanding the fluctuations of business cycles in the past, and to examine monetary policies that might improve stabilization. The analysis shows how different policies change the frequency and damping of the economic system dynamics, and how they modify the amplitude of the fluctuations that are caused by random disturbances. Examples are used to show how policy feedbacks and policy lags can be incorporated, and how different monetary strategies for stabilization can be analytically compared. Representative numerical results are used to illustrate the main points.

On the use of the term 'frequency' in applied behavior analysis.

Science.gov (United States)

Carr, James E; Nosik, Melissa R; Luke, Molli M

2018-04-01

There exists a terminological problem in applied behavior analysis: the term frequency has been used as a synonym for both rate (the number of responses per time) and count (the number of responses). To guide decisions about the use and meaning of frequency, we surveyed the usage of frequency in contemporary behavior-analytic journals and textbooks and found that the predominant usage of frequency was as count, not rate. Thus, we encourage behavior analysts to use frequency as a synonym for count. © 2018 Society for the Experimental Analysis of Behavior.

Aberrant Gene Expression in Acute Myeloid Leukaemia

DEFF Research Database (Denmark)

Bagger, Frederik Otzen

model to investigate the role of telomerase in AML, we were able to translate the observed effect into human AML patients and identify specific genes involved, which also predict survival patterns in AML patients. During these studies we have applied methods for investigating differentially expressed......-based gene-lookup webservices, called HemaExplorer and BloodSpot. These web-services support the aim of making data and analysis of haematopoietic cells from mouse and human accessible for researchers without bioinformatics expertise. Finally, in order to aid the analysis of the very limited number...

Applied functional analysis

CERN Document Server

Oden, J Tinsley

2010-01-01

The textbook is designed to drive a crash course for beginning graduate students majoring in something besides mathematics, introducing mathematical foundations that lead to classical results in functional analysis. More specifically, Oden and Demkowicz want to prepare students to learn the variational theory of partial differential equations, distributions, and Sobolev spaces and numerical analysis with an emphasis on finite element methods. The 1996 first edition has been used in a rather intensive two-semester course. -Book News, June 2010

Lovaas Model of Applied Behavior Analysis. What Works Clearinghouse Intervention Report

Science.gov (United States)

What Works Clearinghouse, 2010

2010-01-01

The "Lovaas Model of Applied Behavior Analysis" is a type of behavioral therapy that initially focuses on discrete trials: brief periods of one-on-one instruction, during which a teacher cues a behavior, prompts the appropriate response, and provides reinforcement to the child. Children in the program receive an average of 35 to 40 hours…

Resolving relative time expressions in Dutch text with Constraint Handling Rules

DEFF Research Database (Denmark)

van de Camp, Matje; Christiansen, Henning

2012-01-01

It is demonstrated how Constraint Handling Rules can be applied for resolution of indirect and relative time expressions in text as part of a shallow analysis, following a specialized tagging phase. A method is currently under development, optimized for a particular corpus of historical biographies...

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba

2016-07-20

The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

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.

The utility of optical detection system (qPCR) and bioinformatics methods in reference gene expression analysis

Science.gov (United States)

Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew

2016-09-01

Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.

Applied functional analysis

CERN Document Server

Griffel, DH

2002-01-01

A stimulating introductory text, this volume examines many important applications of functional analysis to mechanics, fluid mechanics, diffusive growth, and approximation. Detailed enough to impart a thorough understanding, the text is also sufficiently straightforward for those unfamiliar with abstract analysis. Its four-part treatment begins with distribution theory and discussions of Green's functions. Essentially independent of the preceding material, the second and third parts deal with Banach spaces, Hilbert space, spectral theory, and variational techniques. The final part outlines the

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

Science.gov (United States)

Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

2016-01-01

The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis

Directory of Open Access Journals (Sweden)

Chun Chen

2016-03-01

Full Text Available Abstract The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host–pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S, 28S rRNA(28S and elongation factor 1 alpha-like protein (EF1, were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae, and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189, 28S (1.414 and EF1 (3. The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis.

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH genes in multiple human solid tumors: A systematic expression analysis

Directory of Open Access Journals (Sweden)

Werbowetski-Ogilvie Tamra

2008-01-01

Full Text Available Abstract Background The inter-alpha-trypsin inhibitors (ITI are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by AMBP – and five homologous heavy chains (encoded by ITIH1, ITIH2, ITIH3, ITIH4, and ITIH5, contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis. Methods We systematically investigated differential gene expression of the ITIH gene family, as well as AMBP and the interacting partner TNFAIP6 in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas using cDNA dot blot analysis (Cancer Profiling Array, CPA, semiquantitative RT-PCR and immunohistochemistry. Results We found that ITIH genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, ITIH genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose ITIH2 expression in human breast cancer. Loss of ITIH2 expression in 70% of cases (n = 50, CPA could be confirmed by real-time PCR in an additional set of breast cancers (n = 36. Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p Conclusion Altogether, this is the first systematic analysis on the differential expression of ITIH genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies.

Isolation and expression analysis of a tobacco AINTEGUMENTA ortholog (NtANTL).

Science.gov (United States)

Rieu, Ivo; Bots, Marc; Mariani, Celestina; Weterings, Koen A P

2005-05-01

The Arabidopsis AINTEGUMENTA (ANT) protein is essential for proper ovule development, but functions in cell proliferation and organ growth throughout the plant. Here we report the isolation of a full-length cDNA clone from tobacco (Nicotiana tabacum L.) that encodes a protein with high similarity to ANT and is preferentially expressed in the pistil. In situ hybridization analysis on the tobacco ovary shows that the expression pattern of the corresponding gene is different from that of ANT in Arabidopsis.

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.

Multimodal Approach for Automatic Emotion Recognition Applied to the Tension Levels Study in TV Newscasts

Directory of Open Access Journals (Sweden)

Moisés Henrique Ramos Pereira

2015-12-01

Full Text Available This article addresses a multimodal approach to automatic emotion recognition in participants of TV newscasts (presenters, reporters, commentators and others able to assist the tension levels study in narratives of events in this television genre. The methodology applies state-of-the-art computational methods to process and analyze facial expressions, as well as speech signals. The proposed approach contributes to semiodiscoursive study of TV newscasts and their enunciative praxis, assisting, for example, the identification of the communication strategy of these programs. To evaluate the effectiveness of the proposed approach was applied it in a video related to a report displayed on a Brazilian TV newscast great popularity in the state of Minas Gerais. The experimental results are promising on the recognition of emotions on the facial expressions of tele journalists and are in accordance with the distribution of audiovisual indicators extracted over a TV newscast, demonstrating the potential of the approach to support the TV journalistic discourse analysis.This article addresses a multimodal approach to automatic emotion recognition in participants of TV newscasts (presenters, reporters, commentators and others able to assist the tension levels study in narratives of events in this television genre. The methodology applies state-of-the-art computational methods to process and analyze facial expressions, as well as speech signals. The proposed approach contributes to semiodiscoursive study of TV newscasts and their enunciative praxis, assisting, for example, the identification of the communication strategy of these programs. To evaluate the effectiveness of the proposed approach was applied it in a video related to a report displayed on a Brazilian TV newscast great popularity in the state of Minas Gerais. The experimental results are promising on the recognition of emotions on the facial expressions of tele journalists and are in accordance

Towards factor analysis exploration applied to positron emission tomography functional imaging for breast cancer characterization

International Nuclear Information System (INIS)

Rekik, W.; Ketata, I.; Sellami, L.; Ben slima, M.; Ben Hamida, A.; Chtourou, K.; Ruan, S.

2011-01-01

This paper aims to explore the factor analysis when applied to a dynamic sequence of medical images obtained using nuclear imaging modality, Positron Emission Tomography (PET). This latter modality allows obtaining information on physiological phenomena, through the examination of radiotracer evolution during time. Factor analysis of dynamic medical images sequence (FADMIS) estimates the underlying fundamental spatial distributions by factor images and the associated so-called fundamental functions (describing the signal variations) by factors. This method is based on an orthogonal analysis followed by an oblique analysis. The results of the FADMIS are physiological curves showing the evolution during time of radiotracer within homogeneous tissues distributions. This functional analysis of dynamic nuclear medical images is considered to be very efficient for cancer diagnostics. In fact, it could be applied for cancer characterization, vascularization as well as possible evaluation of response to therapy.

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.

Applied Electromagnetics

Energy Technology Data Exchange (ETDEWEB)

Yamashita, H; Marinova, I; Cingoski, V [eds.

2002-07-01

These proceedings contain papers relating to the 3rd Japanese-Bulgarian-Macedonian Joint Seminar on Applied Electromagnetics. Included are the following groups: Numerical Methods I; Electrical and Mechanical System Analysis and Simulations; Inverse Problems and Optimizations; Software Methodology; Numerical Methods II; Applied Electromagnetics.

Applied Electromagnetics

International Nuclear Information System (INIS)

Yamashita, H.; Marinova, I.; Cingoski, V.

2002-01-01

These proceedings contain papers relating to the 3rd Japanese-Bulgarian-Macedonian Joint Seminar on Applied Electromagnetics. Included are the following groups: Numerical Methods I; Electrical and Mechanical System Analysis and Simulations; Inverse Problems and Optimizations; Software Methodology; Numerical Methods II; Applied Electromagnetics

Dissociation between recognition and detection advantage for facial expressions: a meta-analysis.

Science.gov (United States)

Nummenmaa, Lauri; Calvo, Manuel G

2015-04-01

Happy facial expressions are recognized faster and more accurately than other expressions in categorization tasks, whereas detection in visual search tasks is widely believed to be faster for angry than happy faces. We used meta-analytic techniques for resolving this categorization versus detection advantage discrepancy for positive versus negative facial expressions. Effect sizes were computed on the basis of the r statistic for a total of 34 recognition studies with 3,561 participants and 37 visual search studies with 2,455 participants, yielding a total of 41 effect sizes for recognition accuracy, 25 for recognition speed, and 125 for visual search speed. Random effects meta-analysis was conducted to estimate effect sizes at population level. For recognition tasks, an advantage in recognition accuracy and speed for happy expressions was found for all stimulus types. In contrast, for visual search tasks, moderator analysis revealed that a happy face detection advantage was restricted to photographic faces, whereas a clear angry face advantage was found for schematic and "smiley" faces. Robust detection advantage for nonhappy faces was observed even when stimulus emotionality was distorted by inversion or rearrangement of the facial features, suggesting that visual features primarily drive the search. We conclude that the recognition advantage for happy faces is a genuine phenomenon related to processing of facial expression category and affective valence. In contrast, detection advantages toward either happy (photographic stimuli) or nonhappy (schematic) faces is contingent on visual stimulus features rather than facial expression, and may not involve categorical or affective processing. (c) 2015 APA, all rights reserved).

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression

International Nuclear Information System (INIS)

Abba, Martin C; Aldaz, C Marcelo; Drake, Jeffrey A; Hawkins, Kathleen A; Hu, Yuhui; Sun, Hongxia; Notcovich, Cintia; Gaddis, Sally; Sahin, Aysegul; Baggerly, Keith

2004-01-01

Genomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution. In the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed. We accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01). A major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions

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.

Immunohistochemical quantification of expression of a tight junction protein, claudin-7, in human lung cancer samples using digital image analysis method.

Science.gov (United States)

Lu, Zhe; Liu, Yi; Xu, Junfeng; Yin, Hongping; Yuan, Haiying; Gu, Jinjing; Chen, Yan-Hua; Shi, Liyun; Chen, Dan; Xie, Bin

2018-03-01

Tight junction proteins are correlated with cancer development. As the pivotal proteins in epithelial cells, altered expression and distribution of different claudins have been reported in a wide variety of human malignancies. We have previously reported that claudin-7 was strongly expressed in benign bronchial epithelial cells at the cell-cell junction while expression of claudin-7 was either altered with discontinued weak expression or completely absent in lung cancers. Based on these results, we continued working on the expression pattern of claudin-7 and its relationship with lung cancer development. We herein proposed a new Digital Image Classification, Fragmentation index, Morphological analysis (DICFM) method for differentiating the normal lung tissues and lung cancer tissues based on the claudin-7 immunohistochemical staining. Seventy-seven lung cancer samples were obtained from the Second Affiliated Hospital of Zhejiang University and claudin-7 immunohistochemical staining was performed. Based on C++ and Open Source Computer Vision Library (OpenCV, version 2.4.4), the DICFM processing module was developed. Intensity and fragmentation of claudin-7 expression, as well as the morphological parameters of nuclei were calculated. Evaluation of results was performed using Receiver Operator Characteristic (ROC) analysis. Agreement between these computational results and the results obtained by two pathologists was demonstrated. The intensity of claudin-7 expression was significantly decreased while the fragmentation was significantly increased in the lung cancer tissues compared to the normal lung tissues and the intensity was strongly positively associated with the differentiation of lung cancer cells. Moreover, the perimeters of the nuclei of lung cancer cells were significantly greater than that of the normal lung cells, while the parameters of area and circularity revealed no statistical significance. Taken together, our DICFM approach may be applied as an

Applied Behavior Analysis: Its Impact on the Treatment of Mentally Retarded Emotionally Disturbed People.

Science.gov (United States)

Matson, Johnny L.; Coe, David A.

1992-01-01

This article reviews applications of the applied behavior analysis ideas of B. F. Skinner and others to persons with both mental retardation and emotional disturbance. The review examines implications of behavior analysis for operant conditioning and radical behaviorism, schedules of reinforcement, and emotion and mental illness. (DB)

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

Directory of Open Access Journals (Sweden)

Zhu Yuelin

2008-01-01

Full Text Available Abstract Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from http://www.ezarray.com/.

Advantages and Drawbacks of Applying Periodic Time-Variant Modal Analysis to Spur Gear Dynamics

DEFF Research Database (Denmark)

Pedersen, Rune; Santos, Ilmar; Hede, Ivan Arthur

2010-01-01

to ensure sufficient accuracy of the results. The method of time-variant modal analysis is applied, and the changes in the fundamental and the parametric resonance frequencies as a function of the rotational speed of the gears, are found. By obtaining the stationary and parametric parts of the time...... of applying the methodology to wind turbine gearboxes are addressed and elucidated....

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

Science.gov (United States)

Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

2017-02-02

Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

Real-time gene expression analysis in carp (Cyprinus carpio L.) skin: Inflammatory responses to injury mimicking infection with ectoparasites

NARCIS (Netherlands)

Gonzalez, S.F.; Huising, M.O.; Stakauskas, R.; Forlenza, M.; Verburg-van Kemenade, B.M.L.; Buchmann, K.; Nielsen, M.E.; Wiegertjes, G.F.

2007-01-01

We studied a predictive model of gene expression induced by mechanical injury of fish skin, to resolve the confounding effects on the immune system induced by injury and skin parasite-specific molecules. We applied real time quantitative PCR (RQ-PCR) to measure the expression of the pro-inflammatory

Sociosexuality Education for Persons with Autism Spectrum Disorders Using Principles of Applied Behavior Analysis

Science.gov (United States)

Wolfe, Pamela S.; Condo, Bethany; Hardaway, Emily

2009-01-01

Applied behavior analysis (ABA) has emerged as one of the most effective empirically based strategies for instructing individuals with autism spectrum disorders (ASD). Four ABA-based strategies that have been found effective are video modeling, visual strategies, social script fading, and task analysis. Individuals with ASD often struggle with…

Image-based Analysis of Emotional Facial Expressions in Full Face Transplants.

Science.gov (United States)

Bedeloglu, Merve; Topcu, Çagdas; Akgul, Arzu; Döger, Ela Naz; Sever, Refik; Ozkan, Ozlenen; Ozkan, Omer; Uysal, Hilmi; Polat, Ovunc; Çolak, Omer Halil

2018-01-20

In this study, it is aimed to determine the degree of the development in emotional expression of full face transplant patients from photographs. Hence, a rehabilitation process can be planned according to the determination of degrees as a later work. As envisaged, in full face transplant cases, the determination of expressions can be confused or cannot be achieved as the healthy control group. In order to perform image-based analysis, a control group consist of 9 healthy males and 2 full-face transplant patients participated in the study. Appearance-based Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) methods are adopted for recognizing neutral and 6 emotional expressions which consist of angry, scared, happy, hate, confused and sad. Feature extraction was carried out by using both methods and combination of these methods serially. In the performed expressions, the extracted features of the most distinct zones in the facial area where the eye and mouth region, have been used to classify the emotions. Also, the combination of these region features has been used to improve classifier performance. Control subjects and transplant patients' ability to perform emotional expressions have been determined with K-nearest neighbor (KNN) classifier with region-specific and method-specific decision stages. The results have been compared with healthy group. It has been observed that transplant patients don't reflect some emotional expressions. Also, there were confusions among expressions.

Gene expression analysis of embryonic stem cells expressing VE-cadherin (CD144 during endothelial differentiation

Directory of Open Access Journals (Sweden)

Libermann Towia

2008-05-01

Full Text Available Abstract Background Endothelial differentiation occurs during normal vascular development in the developing embryo. This process is recapitulated in the adult when endothelial progenitor cells are generated in the bone marrow and can contribute to vascular repair or angiogenesis at sites of vascular injury or ischemia. The molecular mechanisms of endothelial differentiation remain incompletely understood. Novel approaches are needed to identify the factors that regulate endothelial differentiation. Methods Mouse embryonic stem (ES cells were used to further define the molecular mechanisms of endothelial differentiation. By flow cytometry a population of VEGF-R2 positive cells was identified as early as 2.5 days after differentiation of ES cells, and a subset of VEGF-R2+ cells, that were CD41 positive at 3.5 days. A separate population of VEGF-R2+ stem cells expressing the endothelial-specific marker CD144 (VE-cadherin was also identified at this same time point. Channels lined by VE-cadherin positive cells developed within the embryoid bodies (EBs formed by differentiating ES cells. VE-cadherin and CD41 expressing cells differentiate in close proximity to each other within the EBs, supporting the concept of a common origin for cells of hematopoietic and endothelial lineages. Results Microarray analysis of >45,000 transcripts was performed on RNA obtained from cells expressing VEGF-R2+, CD41+, and CD144+ and VEGF-R2-, CD41-, and CD144-. All microarray experiments were performed in duplicate using RNA obtained from independent experiments, for each subset of cells. Expression profiling confirmed the role of several genes involved in hematopoiesis, and identified several putative genes involved in endothelial differentiation. Conclusion The isolation of CD144+ cells during ES cell differentiation from embryoid bodies provides an excellent model system and method for identifying genes that are expressed during endothelial differentiation and that

Digital gene expression analysis of Microsporum canis exposed to berberine chloride.

Directory of Open Access Journals (Sweden)

Chen-Wen Xiao

Full Text Available Berberine, a natural isoquinoline alkaloid of many medicinal herbs, has an active function against a variety of microbial infections including Microsporum canis (M. canis. However, the underlying mechanisms are poorly understood. To study the effect of berberine chloride on M. canis infection, a Digital Gene Expression (DGE tag profiling was constructed and a transcriptome analysis of the M. canis cellular responses upon berberine treatment was performed. Illumina/Hisseq sequencing technique was used to generate the data of gene expression profile, and the following enrichment analysis of Gene Ontology (GO and Pathway function were conducted based on the data of transcriptome. The results of DGE showed that there were 8476945, 14256722, 7708575, 5669955, 6565513 and 9303468 tags respectively, which was obtained from M. canis incubated with berberine or control DMSO. 8,783 genes were totally mapped, and 1,890 genes have shown significant changes between the two groups. 1,030 genes were up-regulated and 860 genes were down-regulated (P<0.05 in berberine treated group compared to the control group. Besides, twenty-three GO terms were identified by Gene Ontology functional enrichment analysis, such as calcium-transporting ATPase activity, 2-oxoglutarate metabolic process, valine catabolic process, peroxisome and unfolded protein binding. Pathway significant enrichment analysis indicated 6 signaling pathways that are significant, including steroid biosynthesis, steroid hormone biosynthesis, Parkinson's disease, 2,4-Dichlorobenzoate degradation, and tropane, piperidine and Isoquinoline alkaloid biosynthesis. Among these, eleven selected genes were further verified by qRT-PCR. Our findings provide a comprehensive view on the gene expression profile of M. canis upon berberine treatment, and shed light on its complicated effects on M. canis.

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

Nuclear physical express analysis of solid fuel sulphur content

International Nuclear Information System (INIS)

Pak, Yu.; Ponomaryova, M

2005-01-01

Full text: Sulphur content is an important qualitative coal parameter. The problem of coal sulphur content determining remains one of the most important both in Kazakhstan and in other coal-mining countries. The traditional method of sampling, the final stage of which is chemical analysis of coal for sulphur, is characterized by high labour intensity and low productivity. That's why it is ineffective for mass express analytical quality control and technological schemes of coal processing control. In this connection it is very urgent to develop a method of coal sulphur content on the base of a series nuclear-geophysical equipment with an isotope source of primary radiation, allowing to increase analysis representativity and maximally take into account coal real composition inconstancy. To solve the problem set it is necessary to study the main laws of X-ray-radiometric method applied to the coal quality analysis for working out instrumental methods of speed determining of coal sulphur content with satisfactory accuracy for technological tasks, to determine laws of changing the flows of characteristic X-ray and scattered radiation from coal sulphur content of various real composition and to optimize methodical and hardware parameters, providing minimal error of sulphur content control. On the base of studying laws of real composition coal components and their interconnections with sulphur content there has been substantiated the expediency of using hardware functions of calcium and iron to control coal sulphur contents; there has been suggested a model to estimate the methodical error of coal sulphur content determining on the base of the data about sensitivity to sulphur and effecting factors using ultimate methods of coal components substitution methods allowing to optimize sulphur control parameters; there has been worked out an algorithm of X-ray-radiometric control of sulphur content based on the sequential radiating the analyzed coal with gamma-radiation of

Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.

Science.gov (United States)

Rudert, Thomas; Lohmann, Gabriele

2008-12-01

To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.

Toward a Technology of Derived Stimulus Relations: An Analysis of Articles Published in the "Journal of Applied Behavior Analysis," 1992-2009

Science.gov (United States)

Rehfeldt, Ruth Anne

2011-01-01

Every article on stimulus equivalence or derived stimulus relations published in the "Journal of Applied Behavior Analysis" was evaluated in terms of characteristics that are relevant to the development of applied technologies: the type of participants, settings, procedure automated vs. tabletop), stimuli, and stimulus sensory modality; types of…

Clonal analysis of the T-cell response to in vivo expressed Mycobacterium tuberculosis protein Rv2034, using a CD154 expression based T-cell cloning method.

Directory of Open Access Journals (Sweden)

Susanna Commandeur

Full Text Available Tuberculosis (TB, caused by Mycobacterium tuberculosis (Mtb, remains a leading cause of death worldwide. A better understanding of the role of CD4+ and CD8+ T cells, which are both important to TB protection, is essential to unravel the mechanisms of protection and to identify the key antigens seen by these T cells. We have recently identified a set of in vivo expressed Mtb genes (IVE-TB which is expressed during in vivo pulmonary infection in mice, and shown that their encoded antigens are potently recognized by polyclonal T cells from tuberculin skin test-positive, in vitro ESAT-6/CFP10-responsive individuals. Here we have cloned T cells specific for one of these newly identified in vivo expressed Mtb (IVE-TB antigens, Rv2034. T cells were enriched based on the expression of CD154 (CD40L, which represents a new method for selecting antigen-specific (low frequency T cells independent of their specific function. An Rv2034-specific CD4+ T-cell clone expressed the Th1 markers T-bet, IFN-γ, TNF-α, IL-2 and the cytotoxicity related markers granzyme B and CD107a as measured by flow cytometry. The clone specifically recognized Rv2034 protein, Rv2034 peptide p81-100 and Mtb lysate. Remarkably, while the recognition of the dominant p81-100 epitope was HLA-DR restricted, the T-cell clone also recognized a neighboring epitope (p88-107 in an HLA-DR- as well as HLA-DQ1-restricted fashion. Importantly, the T-cell clone was able to inhibit Mtb outgrowth from infected monocytes significantly. The characterization of the polyfunctional and Mtb inhibitory T-cell response to IVE-TB Rv2034 at the clonal level provides detailed further insights into the potential of IVE-TB antigens as new vaccine candidate antigens in TB. Our new approach allowed the identification of T-cell subsets that likely play a significant role in controlling Mtb infection, and can be applied to the analysis of T-cell responses in patient populations.

Sensitivity and uncertainty analysis applied to a repository in rock salt

International Nuclear Information System (INIS)

Polle, A.N.

1996-12-01

This document describes the sensitivity and uncertainty analysis with UNCSAM, as applied to a repository in rock salt for the EVEREST project. UNCSAM is a dedicated software package for sensitivity and uncertainty analysis, which was already used within the preceding PROSA project. The use of UNCSAM provides a flexible interface to EMOS ECN by substituting the sampled values in the various input files to be used by EMOS ECN ; the model calculations for this repository were performed with the EMOS ECN code. Preceding the sensitivity and uncertainty analysis, a number of preparations has been carried out to facilitate EMOS ECN with the probabilistic input data. For post-processing the EMOS ECN results, the characteristic output signals were processed. For the sensitivity and uncertainty analysis with UNCSAM the stochastic input, i.e. sampled values, and the output for the various EMOS ECN runs have been analyzed. (orig.)

The evolution of applied harmonic analysis models of the real world

CERN Document Server

Prestini, Elena

2016-01-01

A sweeping exploration of the development and far-reaching applications of harmonic analysis such as signal processing, digital music, optics, radio astronomy, crystallography, medical imaging, spectroscopy, and more. Featuring a wealth of illustrations, examples, and material not found in other harmonic analysis books, this unique monograph skillfully blends together historical narrative with scientific exposition to create a comprehensive yet accessible work. While only an understanding of calculus is required to appreciate it, there are more technical sections that will charm even specialists in harmonic analysis. From undergraduates to professional scientists, engineers, and mathematicians, there is something for everyone here. The second edition of The Evolution of Applied Harmonic Analysis contains a new chapter on atmospheric physics and climate change, making it more relevant for today’s audience. Praise for the first edition: "…can be thoroughly recommended to any reader who is curious about the ...

A meta-analysis of gene expression signatures of blood pressure and hypertension.

Directory of Open Access Journals (Sweden)

Tianxiao Huan

2015-03-01

Full Text Available Genome-wide association studies (GWAS have uncovered numerous genetic variants (SNPs that are associated with blood pressure (BP. Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05. Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2. Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.

eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.

Science.gov (United States)

Clarke, Daniel J B; Kuleshov, Maxim V; Schilder, Brian M; Torre, Denis; Duffy, Mary E; Keenan, Alexandra B; Lachmann, Alexander; Feldmann, Axel S; Gundersen, Gregory W; Silverstein, Moshe C; Wang, Zichen; Ma'ayan, Avi

2018-05-25

While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases (X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.

Expression analysis of miRNA and target mRNAs in esophageal cancer

Energy Technology Data Exchange (ETDEWEB)

Meng, X.R. [Oncology Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou (China); Lu, P. [Gastrointestinal Surgery Department, People' s Hospital of Zhengzhou, Zhengzhou (China); Mei, J.Z.; Liu, G.J. [Medical Oncology Department, People' s Hospital of Zhengzhou, Zhengzhou (China); Fan, Q.X. [Oncology Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou (China)

2014-08-01

We aimed to investigate miRNAs and related mRNAs through a network-based approach in order to learn the crucial role that they play in the biological processes of esophageal cancer. Esophageal squamous-cell carcinoma (ESCC) and adenocarcinoma (EAC)-related miRNA and gene expression data were downloaded from the Gene Expression Omnibus database, and differentially expressed miRNAs and genes were selected. Target genes of differentially expressed miRNAs were predicted and their regulatory networks were constructed. Differentially expressed miRNA analysis selected four miRNAs associated with EAC and ESCC, among which hsa-miR-21 and hsa-miR-202 were shared by both diseases. hsa-miR-202 was reported for the first time to be associated with esophageal cancer in the present study. Differentially expressed miRNA target genes were mainly involved in cancer-related and signal-transduction pathways. Functional categories of these target genes were related to transcriptional regulation. The results may indicate potential target miRNAs and genes for future investigations of esophageal cancer.

How to find soluble proteins: a comprehensive analysis of alpha/beta hydrolases for recombinant expression in E. coli

Directory of Open Access Journals (Sweden)

Barth Sandra

2005-04-01

Full Text Available Abstract Background In screening of libraries derived by expression cloning, expression of active proteins in E. coli can be limited by formation of inclusion bodies. In these cases it would be desirable to enrich gene libraries for coding sequences with soluble gene products in E. coli and thus to improve the efficiency of screening. Previously Wilkinson and Harrison showed that solubility can be predicted from amino acid composition (Biotechnology 1991, 9(5:443–448. We have applied this analysis to members of the alpha/beta hydrolase fold family to predict their solubility in E. coli. alpha/beta hydrolases are a highly diverse family with more than 1800 proteins which have been grouped into homologous families and superfamilies. Results The predicted solubility in E. coli depends on hydrolase size, phylogenetic origin of the host organism, the homologous family and the superfamily, to which the hydrolase belongs. In general small hydrolases are predicted to be more soluble than large hydrolases, and eukaryotic hydrolases are predicted to be less soluble in E. coli than prokaryotic ones. However, combining phylogenetic origin and size leads to more complex conclusions. Hydrolases from prokaryotic, fungal and metazoan origin are predicted to be most soluble if they are of small, medium and large size, respectively. We observed large variations of predicted solubility between hydrolases from different homologous families and from different taxa. Conclusion A comprehensive analysis of all alpha/beta hydrolase sequences allows more efficient screenings for new soluble alpha/beta hydrolases by the use of libraries which contain more soluble gene products. Screening of hydrolases from families whose members are hard to express as soluble proteins in E. coli should first be done in coding sequences of organisms from phylogenetic groups with the highest average of predicted solubility for proteins of this family. The tools developed here can be used

The expression of cytoglobin as a prognostic factor in gliomas: a retrospective analysis of 88 patients

International Nuclear Information System (INIS)

Xu, Hong-Wu; Huang, Hai-Hua; Wei, Xiao-Long; Man, Kwan; Zhang, Guo-Jun; Huang, Yue-Jun; Xie, Ze-Yu; Lin, Lan; Guo, Yan-Chun; Zhuang, Ze-Rui; Lin, Xin-Peng; Zhou, Wen; Li, Mu

2013-01-01

Evidence suggests that cytoglobin (Cygb) may function as a tumor suppressor gene. We immunohistochemically evaluated the expression of Cygb, phosphatidylinositol-3 kinase (PI-3K), phosphorylated (p)-Akt, Interleukin-6 (IL-6), tumor necrosis factor-α (TNFα) and vascular endothelial growth factor (VEGF) in 88 patients with 41 high-grade gliomas and 47 low-grade gliomas. Intratumoral microvessel density (IMD) was also determined and associated with clinicopathological factors. Low expression of Cygb was significantly associated with the higher histological grading and tumor recurrence. A significant negative correlation emerged between Cygb expression and PI3K, p-Akt, IL-6, TNFα or VEGF expression. Cygb expression was negatively correlated with IMD. There was a positive correlation between PI3K, p-Akt, IL-6, TNFα and VEGF expression with IMD.High histologic grade, tumor recurrence, decreased Cygb expression, increased PI3K expression, increased p-Akt expression and increased VEGF expression correlated with patients’ overall survival in univariate analysis. However, only histological grading and Cygb expression exhibited a relationship with survival of patients as independent prognostic factors of glioma by multivariate analysis. Cygb loss may contribute to tumor recurrence and a worse prognosis in gliomas. Cygb may serve as an independent predictive factor for prognosis of glioma patients

Analysis of facial expressions in parkinson's disease through video-based automatic methods.

Science.gov (United States)

Bandini, Andrea; Orlandi, Silvia; Escalante, Hugo Jair; Giovannelli, Fabio; Cincotta, Massimo; Reyes-Garcia, Carlos A; Vanni, Paola; Zaccara, Gaetano; Manfredi, Claudia

2017-04-01

The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia. In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based METHODS: 17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions. Results show that control subjects reported on average higher distances than PD patients along the tasks. This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients. Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform. Copyright © 2017 Elsevier B.V. All rights reserved.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.

Science.gov (United States)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.

In situ aromatase expression in primary tumor is associated with estrogen receptor expression but is not predictive of response to endocrine therapy in advanced breast cancer

International Nuclear Information System (INIS)

Lykkesfeldt, Anne E; Henriksen, Katrine L; Rasmussen, Birgitte B; Sasano, Hironobu; Evans, Dean B; Møller, Susanne; Ejlertsen, Bent; Mouridsen, Henning T

2009-01-01

New, third-generation aromatase inhibitors (AIs) have proven comparable or superior to the anti-estrogen tamoxifen for treatment of estrogen receptor (ER) and/or progesterone receptor (PR) positive breast cancer. AIs suppress total body and intratumoral estrogen levels. It is unclear whether in situ carcinoma cell aromatization is the primary source of estrogen production for tumor growth and whether the aromatase expression is predictive of response to endocrine therapy. Due to methodological difficulties in the determination of the aromatase protein, COX-2, an enzyme involved in the synthesis of aromatase, has been suggested as a surrogate marker for aromatase expression. Primary tumor material was retrospectively collected from 88 patients who participated in a randomized clinical trial comparing the AI letrozole to the anti-estrogen tamoxifen for first-line treatment of advanced breast cancer. Semi-quantitative immunohistochemical (IHC) analysis was performed for ER, PR, COX-2 and aromatase using Tissue Microarrays (TMAs). Aromatase was also analyzed using whole sections (WS). Kappa analysis was applied to compare association of protein expression levels. Univariate Wilcoxon analysis and the Cox-analysis were performed to evaluate time to progression (TTP) in relation to marker expression. Aromatase expression was associated with ER, but not with PR or COX-2 expression in carcinoma cells. Measurements of aromatase in WS were not comparable to results from TMAs. Expression of COX-2 and aromatase did not predict response to endocrine therapy. Aromatase in combination with high PR expression may select letrozole treated patients with a longer TTP. TMAs are not suitable for IHC analysis of in situ aromatase expression and we did not find COX-2 expression in carcinoma cells to be a surrogate marker for aromatase. In situ aromatase expression in tumor cells is associated with ER expression and may thus point towards good prognosis. Aromatase expression in cancer

Applying HAZOP analysis in assessing remote handling compatibility of ITER port plugs

International Nuclear Information System (INIS)

Duisings, L.P.M.; Til, S. van; Magielsen, A.J.; Ronden, D.M.S.; Elzendoorn, B.S.Q.; Heemskerk, C.J.M.

2013-01-01

Highlights: ► We applied HAZOP analysis to assess the criticality of remote handling maintenance activities on port plugs in the ITER Hot Cell facility. ► We identified several weak points in the general upper port plug maintenance concept. ► We made clear recommendations on redesign in port plug design, operational sequence and Hot Cell equipment. ► The use of a HAZOP approach for the ECH UL port can also be applied to ITER port plugs in general. -- Abstract: This paper describes the application of a Hazard and Operability Analysis (HAZOP) methodology in assessing the criticality of remote handling maintenance activities on port plugs in the ITER Hot Cell facility. As part of the ECHUL consortium, the remote handling team at the DIFFER Institute is developing maintenance tools and procedures for critical components of the ECH Upper launcher (UL). Based on NRG's experience with nuclear risk analysis and Hot Cell procedures, early versions of these tool concepts and maintenance procedures were subjected to a HAZOP analysis. The analysis identified several weak points in the general upper port plug maintenance concept and led to clear recommendations on redesigns in port plug design, the operational sequence and ITER Hot Cell equipment. The paper describes the HAZOP methodology and illustrates its application with specific procedures: the Steering Mirror Assembly (SMA) replacement and the exchange of the Mid Shield Optics (MSO) in the ECH UPL. A selection of recommended changes to the launcher design associated with the accessibility, maintainability and manageability of replaceable components are presented

Molecular cloning and expression analysis of the sucrose transporter gene family from Theobroma cacao L.

Science.gov (United States)

Li, Fupeng; Wu, Baoduo; Qin, Xiaowei; Yan, Lin; Hao, Chaoyun; Tan, Lehe; Lai, Jianxiong

2014-08-10

In this study, we performed cloning and expression analysis of six putative sucrose transporter genes, designated TcSUT1, TcSUT2, TcSUT3, TcSUT4, TcSUT5 and TcSUT6, from the cacao genotype 'TAS-R8'. The combination of cDNA and genomic DNA sequences revealed that the cacao SUT genes contained exon numbers ranging from 1 to 14. The average molecular mass of all six deduced proteins was approximately 56 kDa (range 52 to 66 kDa). All six proteins were predicted to exhibit typical features of sucrose transporters with 12 trans-membrane spanning domains. Phylogenetic analysis revealed that TcSUT2 and TcSUT4 belonged to Group 2 SUT and Group 4 SUT, respectively, and the other TcSUT proteins were belonging to Group 1 SUT. Real-time PCR was conducted to investigate the expression pattern of each member of the SUT family in cacao. Our experiment showed that TcSUT1 was expressed dominantly in pods and that, TcSUT3 and TcSUT4 were highly expressed in both pods and in bark with phloem. Within pods, TcSUT1 and TcSUT4 were expressed more in the seed coat and seed from the pod enlargement stage to the ripening stage. TcSUT5 expression sharply increased to its highest expression level in the seed coat during the ripening stage. Expression pattern analysis indicated that TcSUT genes may be associated with photoassimilate transport into developing seeds and may, therefore, have an impact on seed production. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel joint analysis framework improves identification of differentially expressed genes in cross disease transcriptomic analysis

Directory of Open Access Journals (Sweden)

Wenyi Qin

2018-02-01

Full Text Available Abstract Motivation Detecting differentially expressed (DE genes between disease and normal control group is one of the most common analyses in genome-wide transcriptomic data. Since most studies don’t have a lot of samples, researchers have used meta-analysis to group different datasets for the same disease. Even then, in many cases the statistical power is still not enough. Taking into account the fact that many diseases share the same disease genes, it is desirable to design a statistical framework that can identify diseases’ common and specific DE genes simultaneously to improve the identification power. Results We developed a novel empirical Bayes based mixture model to identify DE genes in specific study by leveraging the shared information across multiple different disease expression data sets. The effectiveness of joint analysis was demonstrated through comprehensive simulation studies and two real data applications. The simulation results showed that our method consistently outperformed single data set analysis and two other meta-analysis methods in identification power. In real data analysis, overall our method demonstrated better identification power in detecting DE genes and prioritized more disease related genes and disease related pathways than single data set analysis. Over 150% more disease related genes are identified by our method in application to Huntington’s disease. We expect that our method would provide researchers a new way of utilizing available data sets from different diseases when sample size of the focused disease is limited.

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark; Knowles, David W.; Weber, Gunther H.; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

2011-03-30

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

How do we talk about doctors and drugs? Sentiment analysis in forums expressing opinions for medical domain.

Science.gov (United States)

Jiménez-Zafra, Salud María; Martín-Valdivia, M Teresa; Molina-González, M Dolores; Ureña-López, L Alfonso

2018-04-20

The main goal of this study is to examine how people express their opinion in medical forums. We analyze the language used in order to determine the best way to tackle sentiment analysis in this domain. We have applied supervised learning and lexicon-based sentiment analysis approaches over two different corpora extracted from social web. Specifically, we have focused on two aspects: drugs and doctors. We have selected two forums and we have collected corpora for each one: (i) DOS, a Spanish corpus of drug reviews and (ii) COPOS, a Spanish corpus of patients' opinions about physicians. The classification results show that drug reviews are more difficult to classify than those about physicians. In order to understand the difference in the results, we have studied the linguistic features of both corpora. Although opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult. Copyright © 2018 Elsevier B.V. All rights reserved.

Sports dance artistic expression culture analysis

Directory of Open Access Journals (Sweden)

Chen Zegang

2017-01-01

Full Text Available At present, the sports dance has entered every stage of the people’s life, has become the public’s favorite sport. Sports dance has been well developed. This article mainly uses the literature material law to carry on the detailed analysis to the sports dance constitution, elaborated in detail the sports dance artistic expression. The composition of sports dance elements; sports dance is a form of dance art show; sports dance through the dance art can be divided into three aspects, namely, form, music, shape of the expressive force. In this paper, the study will be more in-depth excavation of the cultural connotation of sports dance, and promote the development of sports dance can be more comprehensive. In 20s of last century, Chinese Sports Dance Association officially joined the International Sports Dance Association, which also makes our country’s sports dance and international exchange more frequent. However, due to China’s sports dance sports dance learning time is not long, while learning is influenced by Chinese traditional culture, the sports dance movements are too conservative, there is a very large gap and international enthusiasm, bold and unrestrained, the pursuit of individual sports dance in the dance style, music and performance hand. Sports dance originated from abroad, it is produced in the daily life of people in foreign countries. China’s domestic sports dance players in learning dance at the same time, the production and the connotation of dance is not very understanding, therefore, it is difficult to better reflect the emotional expression of sports dance. Although the sports dance is a kind of similar to the competitive projects, but it is also a kind of dance culture, and to constitute a force from the dance art show a detailed study, detailed mining playing officer of sports dance performance further, reducing China’s sports dance and international sports dance gap.

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...

Microarray analysis of gene expression profiles in ripening pineapple fruits.

Science.gov (United States)

Koia, Jonni H; Moyle, Richard L; Botella, Jose R

2012-12-18

Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit

Applying Fuzzy and Probabilistic Uncertainty Concepts to the Material Flow Analysis of Palladium in Austria

DEFF Research Database (Denmark)

Laner, David; Rechberger, Helmut; Astrup, Thomas Fruergaard

2015-01-01

Material flow analysis (MFA) is a widely applied tool to investigate resource and recycling systems of metals and minerals. Owing to data limitations and restricted system understanding, MFA results are inherently uncertain. To demonstrate the systematic implementation of uncertainty analysis in ...

Gene expression signature analysis identifies vorinostat as a candidate therapy for gastric cancer.

Directory of Open Access Journals (Sweden)

Sofie Claerhout

Full Text Available Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future.Using microarray technology, we generated a gene expression profile of human gastric cancer-specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern.We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment.

A Study in the Founding of Applied Behavior Analysis Through Its Publications

Science.gov (United States)

Morris, Edward K.; Altus, Deborah E.; Smith, Nathaniel G.

2013-01-01

This article reports a study of the founding of applied behavior analysis through its publications. Our methods included hand searches of sources (e.g., journals, reference lists), search terms (i.e., early, applied, behavioral, research, literature), inclusion criteria (e.g., the field's applied dimension), and (d) challenges to their face and content validity. Our results were 36 articles published between 1959 and 1967 that we organized into 4 groups: 12 in 3 programs of research and 24 others. Our discussion addresses (a) limitations in our method (e.g., the completeness of our search), (b) challenges to the validity of our methods and results (e.g., convergent validity), and (c) priority claims about the field's founding. We conclude that the claims are irresolvable because identification of the founding publications depends significantly on methods and because the field's founding was an evolutionary process. We close with suggestions for future research. PMID:25729133

A study in the founding of applied behavior analysis through its publications.

Science.gov (United States)

Morris, Edward K; Altus, Deborah E; Smith, Nathaniel G

2013-01-01

This article reports a study of the founding of applied behavior analysis through its publications. Our methods included hand searches of sources (e.g., journals, reference lists), search terms (i.e., early, applied, behavioral, research, literature), inclusion criteria (e.g., the field's applied dimension), and (d) challenges to their face and content validity. Our results were 36 articles published between 1959 and 1967 that we organized into 4 groups: 12 in 3 programs of research and 24 others. Our discussion addresses (a) limitations in our method (e.g., the completeness of our search), (b) challenges to the validity of our methods and results (e.g., convergent validity), and (c) priority claims about the field's founding. We conclude that the claims are irresolvable because identification of the founding publications depends significantly on methods and because the field's founding was an evolutionary process. We close with suggestions for future research.

Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast

Directory of Open Access Journals (Sweden)

Hawthorn Lesleyann

2010-08-01

Full Text Available Abstract Background A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine parallel analyses that assess changes in the copy number alterations (CNAs. This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions which demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes'. Methods We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs. Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Fourteen IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from loss of heterozygosity (LOH analysis to identify genes showing altered expression in LOH regions. Results Common chromosome gains and amplifications were identified at 1q21.3, 6p21.3, 7p11.2-p12.1, 8q21.11 and 8q24.3. A novel amplicon was identified at 5p15.33. Frequent losses were found at 1p36.22, 8q23.3, 11p13, 11q23, and 22q13. Over 130 genes were identified with concurrent increases or decreases in expression that mapped to these regions of copy number alterations. LOH analysis revealed three tumors with whole chromosome or p arm allelic loss of chromosome 17. Genes were identified that mapped to copy neutral LOH regions. LOH with accompanying copy loss was detected on Xp24 and Xp25 and genes mapping to these regions with decreased expression were identified. Gene expression data highlighted the PPARα/RXRα Activation Pathway as down-regulated in the tumor samples. Conclusion We have demonstrated the utility of the application of

Evolution of Applied Behavior Analysis in the Treatment of Individuals With Autism

Science.gov (United States)

Wolery, Mark; Barton, Erin E.; Hine, Jeffrey F.

2005-01-01

Two issues of each volume of the Journal of Applied Behavior Analysis were reviewed to identify research reports focusing on individuals with autism. The identified articles were analyzed to describe the ages of individuals with autism, the settings in which the research occurred, the nature of the behaviors targeted for intervention, and the…

Dimensional Information-Theoretic Measurement of Facial Emotion Expressions in Schizophrenia

Directory of Open Access Journals (Sweden)

Jihun Hamm

2014-01-01

Full Text Available Altered facial expressions of emotions are characteristic impairments in schizophrenia. Ratings of affect have traditionally been limited to clinical rating scales and facial muscle movement analysis, which require extensive training and have limitations based on methodology and ecological validity. To improve reliable assessment of dynamic facial expression changes, we have developed automated measurements of facial emotion expressions based on information-theoretic measures of expressivity of ambiguity and distinctiveness of facial expressions. These measures were examined in matched groups of persons with schizophrenia (n=28 and healthy controls (n=26 who underwent video acquisition to assess expressivity of basic emotions (happiness, sadness, anger, fear, and disgust in evoked conditions. Persons with schizophrenia scored higher on ambiguity, the measure of conditional entropy within the expression of a single emotion, and they scored lower on distinctiveness, the measure of mutual information across expressions of different emotions. The automated measures compared favorably with observer-based ratings. This method can be applied for delineating dynamic emotional expressivity in healthy and clinical populations.

An Improved Biclustering Algorithm and Its Application to Gene Expression Spectrum Analysis

OpenAIRE

Qu, Hua; Wang, Liu-Pu; Liang, Yan-Chun; Wu, Chun-Guo

2016-01-01

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the d...

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

Energy Technology Data Exchange (ETDEWEB)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

International Nuclear Information System (INIS)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-01-01

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC

Molecular characterization, sequence analysis and tissue expression of a porcine gene – MOSPD2

Directory of Open Access Journals (Sweden)

Yang Jie

2017-01-01

Full Text Available The full-length cDNA sequence of a porcine gene, MOSPD2, was amplified using the rapid amplification of cDNA ends method based on a pig expressed sequence tag sequence which was highly homologous to the coding sequence of the human MOSPD2 gene. Sequence prediction analysis revealed that the open reading frame of this gene encodes a protein of 491 amino acids that has high homology with the motile sperm domain-containing protein 2 (MOSPD2 of five species: horse (89%, human (90%, chimpanzee (89%, rhesus monkey (89% and mouse (85%; thus, it could be defined as a porcine MOSPD2 gene. This novel porcine gene was assigned GeneID: 100153601. This gene is structured in 15 exons and 14 introns as revealed by computer-assisted analysis. The phylogenetic analysis revealed that the porcine MOSPD2 gene has a closer genetic relationship with the MOSPD2 gene of horse. Tissue expression analysis indicated that the porcine MOSPD2 gene is generally and differentially expressed in the spleen, muscle, skin, kidney, lung, liver, fat and heart. Our experiment is the first to establish the primary foundation for further research on the porcine MOSPD2 gene.

Meta-analysis of expression and function of neprilysin in Alzheimer's disease.

Science.gov (United States)

Zhang, Huifeng; Liu, Dan; Wang, Yixing; Huang, Huanhuan; Zhao, Yujia; Zhou, Hui

2017-09-14

Neprilysin (NEP) is one of the most important Aβ-degrading enzymes, and its expression and activity in Alzheimer's brain have been widely reported, but the results remain debatable. Thus, the meta-analysis was performed to elucidate the role of NEP in Alzheimer's disease (AD). The relevant case-control or cohort studies were retrieved according to our inclusion/exclusion criteria. Six studies with 123 controls and 141 AD cases, seven studies with 102 controls and 90 AD cases, and four studies with 93 controls and 132 AD cases were included in meta-analysis of NEP's protein, mRNA, and enzyme activity respectively. We conducted Meta regression to detect the sources of heterogeneity and further performed cumulative meta-analysis or subgroup analysis. Our meta-analysis revealed a significantly lower level of NEP mRNA (SMD=-0.44, 95%CI: -0.87, -0.00, p=0.049) in AD cases than in non-AD cases, and such pattern was not altered over time in the cumulative meta-analysis. However, the decrease of NEP protein (SMD=-0.18, 95%CI: -0.62, 0.25) and enzyme activity (SMD=-0.35, 95%CI: -1.03, 0.32) in AD cases did not pass the significance check, while the cumulative meta-analysis by average age showed the pooled effect became insignificant as adding the studies with younger subjects, which indicates that the protein expression and enzyme activity of NEP in the cortex are affected by age. Therefore, the present meta-analysis suggests the need of further investigation of roles of NEP in AD pathogenesis and treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Directory of Open Access Journals (Sweden)

Yang X

2018-03-01

Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the

Applied statistical training to strengthen analysis and health research capacity in Rwanda.

Science.gov (United States)

Thomson, Dana R; Semakula, Muhammed; Hirschhorn, Lisa R; Murray, Megan; Ndahindwa, Vedaste; Manzi, Anatole; Mukabutera, Assumpta; Karema, Corine; Condo, Jeanine; Hedt-Gauthier, Bethany

2016-09-29

To guide efficient investment of limited health resources in sub-Saharan Africa, local researchers need to be involved in, and guide, health system and policy research. While extensive survey and census data are available to health researchers and program officers in resource-limited countries, local involvement and leadership in research is limited due to inadequate experience, lack of dedicated research time and weak interagency connections, among other challenges. Many research-strengthening initiatives host prolonged fellowships out-of-country, yet their approaches have not been evaluated for effectiveness in involvement and development of local leadership in research. We developed, implemented and evaluated a multi-month, deliverable-driven, survey analysis training based in Rwanda to strengthen skills of five local research leaders, 15 statisticians, and a PhD candidate. Research leaders applied with a specific research question relevant to country challenges and committed to leading an analysis to publication. Statisticians with prerequisite statistical training and experience with a statistical software applied to participate in class-based trainings and complete an assigned analysis. Both statisticians and research leaders were provided ongoing in-country mentoring for analysis and manuscript writing. Participants reported a high level of skill, knowledge and collaborator development from class-based trainings and out-of-class mentorship that were sustained 1 year later. Five of six manuscripts were authored by multi-institution teams and submitted to international peer-reviewed scientific journals, and three-quarters of the participants mentored others in survey data analysis or conducted an additional survey analysis in the year following the training. Our model was effective in utilizing existing survey data and strengthening skills among full-time working professionals without disrupting ongoing work commitments and using few resources. Critical to our

Research in progress in applied mathematics, numerical analysis, fluid mechanics, and computer science

Science.gov (United States)

1994-01-01

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1993 through March 31, 1994. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.

Expression analysis and biochemical characterization of beans plants biofortificated with zinc

Directory of Open Access Journals (Sweden)

Sandra Pérez Álvarez

2017-09-01

Full Text Available The present work was carried out in greenhouse conditions at the Centro de Investigación en Alimentación y Desarrollo AC in Delicias, Chihuahua, México. Four different concentrations (0, 25, 50 and 100 μM L−1 of Zn chelate and sulfate were used to study the antioxidant system of Phaseolus vulgaris L. Three genes related with antioxidant activity [superoxide dismutase (SOD, glutathione peroxidase (GSH-Px and catalase (CAT] were selected for expression study. Results showed that when Zn chelate at 50 and 100 μM L−1 were applied SOD was repressed and GSH-Px expression was low at 0, 25 and 100 μM L−1 while with sulfate form SOD expression was low and GSH-Px expression was strong in all treatment. CAT was highly expressed in all form and treatments. For a biochemical study the same enzymes were spectrophotometrically measured. SOD activity shows differences in both forms of Zn, chelate form was different at 25, 50 and 100 μM L−1 with less activity at 100 μM L−1 and sulfate treatment shows differences in all concentrations used. GSH-Px activity shows significant differences with sulfate form at 25, 50 μM L−1 where at 50 μM the activity was higher and low at 100 μM L−1, CAT does not exhibit significant differences but with chelate treatment at 50–100 μM L−1 the activity was higher compared to sulfate. Finally, to raise the Zn concentration in bean under biofortification program is a promising strategy in cropping systems in order to increase the ingestion of zinc and antioxidant capacity in the general population and provided the benefits that this element offered in human health.

Perturbation-expression analysis identifies RUNX1 as a regulator of human mammary stem cell differentiation.

Directory of Open Access Journals (Sweden)

Ethan S Sokol

2015-04-01

Full Text Available The search for genes that regulate stem cell self-renewal and differentiation has been hindered by a paucity of markers that uniquely label stem cells and early progenitors. To circumvent this difficulty we have developed a method that identifies cell-state regulators without requiring any markers of differentiation, termed Perturbation-Expression Analysis of Cell States (PEACS. We have applied this marker-free approach to screen for transcription factors that regulate mammary stem cell differentiation in a 3D model of tissue morphogenesis and identified RUNX1 as a stem cell regulator. Inhibition of RUNX1 expanded bipotent stem cells and blocked their differentiation into ductal and lobular tissue rudiments. Reactivation of RUNX1 allowed exit from the bipotent state and subsequent differentiation and mammary morphogenesis. Collectively, our findings show that RUNX1 is required for mammary stem cells to exit a bipotent state, and provide a new method for discovering cell-state regulators when markers are not available.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.

2010-09-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry

2010-01-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Validating Internal Control Genes for the Accurate Normalization of qPCR Expression Analysis of the Novel Model Plant Setaria viridis.

Directory of Open Access Journals (Sweden)

Julia Lambret-Frotté

Full Text Available Employing reference genes to normalize the data generated with quantitative PCR (qPCR can increase the accuracy and reliability of this method. Previous results have shown that no single housekeeping gene can be universally applied to all experiments. Thus, the identification of a suitable reference gene represents a critical step of any qPCR analysis. Setaria viridis has recently been proposed as a model system for the study of Panicoid grasses, a crop family of major agronomic importance. Therefore, this paper aims to identify suitable S. viridis reference genes that can enhance the analysis of gene expression in this novel model plant. The first aim of this study was the identification of a suitable RNA extraction method that could retrieve a high quality and yield of RNA. After this, two distinct algorithms were used to assess the gene expression of fifteen different candidate genes in eighteen different samples, which were divided into two major datasets, the developmental and the leaf gradient. The best-ranked pair of reference genes from the developmental dataset included genes that encoded a phosphoglucomutase and a folylpolyglutamate synthase; genes that encoded a cullin and the same phosphoglucomutase as above were the most stable genes in the leaf gradient dataset. Additionally, the expression pattern of two target genes, a SvAP3/PI MADS-box transcription factor and the carbon-fixation enzyme PEPC, were assessed to illustrate the reliability of the chosen reference genes. This study has shown that novel reference genes may perform better than traditional housekeeping genes, a phenomenon which has been previously reported. These results illustrate the importance of carefully validating reference gene candidates for each experimental set before employing them as universal standards. Additionally, the robustness of the expression of the target genes may increase the utility of S. viridis as a model for Panicoid grasses.

Applied research and development of neutron activation analysis

Energy Technology Data Exchange (ETDEWEB)

Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Bak, Sung Ryel; Park, Yong Chul; Kim, Young Ki; Chung, Hwan Sung; Park, Kwang Won; Kang, Sang Hun

2000-05-01

This report is written for results of research and development as follows : improvement of neutron irradiation facilities, counting system and development of automation system and capsules for NAA in HANARO ; improvement of analytical procedures and establishment of analytical quality control and assurance system; applied research and development of environment, industry and human health and its standardization. For identification and standardization of analytical method, environmental biological samples and polymer are analyzed and uncertainity of measurement are estimated. Also data intercomparison and proficency test were performed. Using airborne particulate matter chosen as a environmental indicators, trace elemental concentrations of sample collected at urban and rural site are determined and then the calculation of statistics and the factor analysis are carried out for investigation of emission source. International cooperation research project was carried out for utilization of nuclear techniques.

Applied research and development of neutron activation analysis

International Nuclear Information System (INIS)

Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Bak, Sung Ryel; Park, Yong Chul; Kim, Young Ki; Chung, Hwan Sung; Park, Kwang Won; Kang, Sang Hun

2000-05-01

This report is written for results of research and development as follows : improvement of neutron irradiation facilities, counting system and development of automation system and capsules for NAA in HANARO ; improvement of analytical procedures and establishment of analytical quality control and assurance system; applied research and development of environment, industry and human health and its standardization. For identification and standardization of analytical method, environmental biological samples and polymer are analyzed and uncertainity of measurement are estimated. Also data intercomparison and proficency test were performed. Using airborne particulate matter chosen as a environmental indicators, trace elemental concentrations of sample collected at urban and rural site are determined and then the calculation of statistics and the factor analysis are carried out for investigation of emission source. International cooperation research project was carried out for utilization of nuclear techniques

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

Directory of Open Access Journals (Sweden)

Teng Shaolei

2013-01-01

Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

Altered retinal microRNA expression profiles in early diabetic retinopathy: an in silico analysis.

Science.gov (United States)

Xiong, Fen; Du, Xinhua; Hu, Jianyan; Li, Tingting; Du, Shanshan; Wu, Qiang

2014-07-01

MicroRNAs (miRNAs) - as negative regulators of target genes - are associated with various human diseases, but their precise role(s) in diabetic retinopathy (DR) remains to be elucidated. The aim of this study was to elucidate the involvement of miRNAs in early DR using in silico analysis to explore their gene expression patterns. We used the streptozotocin (STZ)-induced diabetic rat to investigate the roles of miRNAs in early DR. Retinal miRNA expression profiles from diabetic versus healthy control rats were examined by miRNA array analysis. Based on several bioinformatic systems, specifically, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we identified signatures of the potential pathological processes, gene functions, and signaling pathways that are influenced by dysregulated miRNAs. We used quantitative real-time polymerase chain reaction (qRT-PCR) to validate six (i.e. those with significant changes in expression levels) of the 17 miRNAs that were detected in the miRNA array. We also describe the significant role of the miRNA-gene network, which is based on the interactions between miRNAs and target genes. GO analysis of the 17 miRNAs detected in the miRNA array analysis revealed the most prevalent miRNAs to be those related to biological processes, olfactory bulb development and axonogenesis. These miRNAs also exert significant influence on additional pathways, including the mitogen-activated protein and calcium signaling pathways. Six of the seventeen miRNAs were chosen for qRT-PCR validation. With the exception of a slight difference in miRNA-350, our results are in close agreement with the differential expressions detected by array analysis. This study, which describes miRNA expression during the early developmental phases of DR, revealed extensive miRNA interactions. Based on both their target genes and signaling pathways, we suggest that miRNAs perform critical regulatory functions during the early stages of DR

Downregulation of transferrin receptor surface expression by intracellular antibody

International Nuclear Information System (INIS)

Peng Jilin; Wu Sha; Zhao Xiaoping; Wang Min; Li Wenhan; Shen Xin; Liu Jing; Lei Ping; Zhu Huifen; Shen Guanxin

2007-01-01

To deplete cellular iron uptake, and consequently inhibit the proliferation of tumor cells, we attempt to block surface expression of transferrin receptor (TfR) by intracellular antibody technology. We constructed two expression plasmids (scFv-HAK and scFv-HA) coding for intracellular single-chain antibody against TfR with or without endoplasmic reticulum (ER) retention signal, respectively. Then they were transfected tumor cells MCF-7 by liposome. Applying RT-PCR, Western blotting, immunofluorescence microscopy and immunoelectron microscope experiments, we insure that scFv-HAK intrabody was successfully expressed and retained in ER contrasted to the secreted expression of scFv-HA. Flow cytometric analysis confirmed that the TfR surface expression was markedly decreased approximately 83.4 ± 2.5% in scFv-HAK transfected cells, while there was not significantly decrease in scFv-HA transfected cells. Further cell growth and apoptosis characteristics were evaluated by cell cycle analysis, nuclei staining and MTT assay. Results indicated that expression of scFv-HAK can dramatically induce cell cycle G1 phase arrest and apoptosis of tumor cells, and consequently significantly suppress proliferation of tumor cells compared with other control groups. For First time this study demonstrates the potential usage of anti-TfR scFv-intrabody as a growth inhibitor of TfR overexpressing tumors

Applied Behavior Analysis in Autism Spectrum Disorders: Recent Developments, Strengths, and Pitfalls

Science.gov (United States)

Matson, Johnny L.; Turygin, Nicole C.; Beighley, Jennifer; Rieske, Robert; Tureck, Kimberly; Matson, Michael L.

2012-01-01

Autism has become one of the most heavily researched topics in the field of mental health and education. While genetics has been the most studied of all topics, applied behavior analysis (ABA) has also received a great deal of attention, and has arguably yielded the most promising results of any research area to date. The current paper provides a…

Effect of method of deduplication on estimation of differential gene expression using RNA-seq

Directory of Open Access Journals (Sweden)

Anna V. Klepikova

2017-03-01

Full Text Available Background RNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads. Results To infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in SAMtools, and deduplication based on one or two molecular indices (MI. We also analyzed the influence of sequencing layout (single read or paired end and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes. Conclusion The use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

Disease gene characterization through large-scale co-expression analysis.

Directory of Open Access Journals (Sweden)

Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

Science.gov (United States)

Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong

2011-01-01

Background Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. Methodology/Principal Findings Using microarray technology, we generated a gene expression profile of human gastric cancer–specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A) whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. Conclusions/Significance We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment. PMID:21931799

Applied Behavior Analysis, Autism, and Occupational Therapy: A Search for Understanding.

Science.gov (United States)

Welch, Christie D; Polatajko, H J

2016-01-01

Occupational therapists strive to be mindful, competent practitioners and continuously look for ways to improve practice. Applied behavior analysis (ABA) has strong evidence of effectiveness in helping people with autism achieve goals, yet it does not seem to be implemented in occupational therapy practice. To better understand whether ABA could be an evidence-based option to expand occupational therapy practice, the authors conducted an iterative, multiphase investigation of relevant literature. Findings suggest that occupational therapists apply developmental and sensory approaches to autism treatment. The occupational therapy literature does not reflect any use of ABA despite its strong evidence base. Occupational therapists may currently avoid using ABA principles because of a perception that ABA is not client centered. ABA principles and occupational therapy are compatible, and the two could work synergistically. Copyright © 2016 by the American Occupational Therapy Association, Inc.

The practical problems of applying cost-effectiveness analysis to joint finance programmes

OpenAIRE

Karen Gerard; Ken Wright

1990-01-01

Joint finance is money allocated by the Department of Health to NHS authorities to promote policies of inter-agency collaboration which prevent people being admitted to hospital or facilitate earlier discharge from hospital or save on NHS resources generally. Worries have been expressed that joint finance has not been used as effectively or efficiency as it might have been. This paper is concerned with the practical application of cost-effectiveness analysis to policies or schemes which typic...

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Data Analysis and Visualization (IDAV) and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,' ' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

System Sensitivity Analysis Applied to the Conceptual Design of a Dual-Fuel Rocket SSTO

Science.gov (United States)

Olds, John R.

1994-01-01

This paper reports the results of initial efforts to apply the System Sensitivity Analysis (SSA) optimization method to the conceptual design of a single-stage-to-orbit (SSTO) launch vehicle. SSA is an efficient, calculus-based MDO technique for generating sensitivity derivatives in a highly multidisciplinary design environment. The method has been successfully applied to conceptual aircraft design and has been proven to have advantages over traditional direct optimization methods. The method is applied to the optimization of an advanced, piloted SSTO design similar to vehicles currently being analyzed by NASA as possible replacements for the Space Shuttle. Powered by a derivative of the Russian RD-701 rocket engine, the vehicle employs a combination of hydrocarbon, hydrogen, and oxygen propellants. Three primary disciplines are included in the design - propulsion, performance, and weights & sizing. A complete, converged vehicle analysis depends on the use of three standalone conceptual analysis computer codes. Efforts to minimize vehicle dry (empty) weight are reported in this paper. The problem consists of six system-level design variables and one system-level constraint. Using SSA in a 'manual' fashion to generate gradient information, six system-level iterations were performed from each of two different starting points. The results showed a good pattern of convergence for both starting points. A discussion of the advantages and disadvantages of the method, possible areas of improvement, and future work is included.

Hessian regularization based non-negative matrix factorization for gene expression data clustering.

Science.gov (United States)

Liu, Xiao; Shi, Jun; Wang, Congzhi

2015-01-01

Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

Comparative analysis of human conjunctival and corneal epithelial gene expression with oligonucleotide microarrays.

Science.gov (United States)

Turner, Helen C; Budak, Murat T; Akinci, M A Murat; Wolosin, J Mario

2007-05-01

To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. cDNA samples derived from human conjunctival and corneal epithelia were hybridized in three independent experiments to a commercial oligonucleotide array representing more than 22,000 transcripts. The resultant signal intensities and microarray software transcript present/absent calls were used in conjunction with the local pooled error (LPE) statistical method to identify transcripts that are preferentially or exclusively expressed in one of the two tissues at significant levels (expression >1% of the beta-actin level). EASE (Expression Analysis Systematic Explorer software) was used to identify biological systems comparatively overrepresented in either epithelium. Immuno-, and cytohistochemistry was performed to validate or expand on selected results of interest. The analysis identified 332 preferential and 93 exclusive significant corneal epithelial transcripts. The corresponding numbers of conjunctival epithelium transcripts were 592 and 211, respectively. The overrepresented biological processes in the cornea were related to cell adhesion and oxiredox equilibria and cytoprotection activities. In the conjunctiva, the biological processes that were most prominent were related to innate immunity and melanogenesis. Immunohistochemistry for antigen-presenting cells and melanocytes was consistent with these gene signatures. The transcript comparison identified a substantial number of genes that have either not been identified previously or are not known to be highly expressed in these two epithelia, including testican-1, ECM1, formin, CRTAC1, and NQO1 in the cornea and, in the conjunctiva, sPLA(2)-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Comparative gene expression profiling leads to the identification of many biological processes and previously unknown genes that

Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

Science.gov (United States)

Shen, Po-Chih; Hour, Ai-Ling; Liu, Li-Yu Daisy

2017-12-01

Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data. By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search. Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

Digital gene expression analysis in mice lung with coinfection of influenza and streptococcus pneumoniae.

Science.gov (United States)

Luo, Jun; Zhou, Linlin; Wang, Hongren; Qin, Zhen; Xiang, Li; Zhu, Jie; Huang, Xiaojun; Yang, Yuan; Li, Wanyi; Wang, Baoning; Li, Mingyuan

2017-12-22

Influenza A virus (IAV) and Streptococcus pneumoniae (SP) are two major upper respiratory tract pathogens that can also cause infection in polarized bronchial epithelial cells to exacerbate disease in coinfected individuals which may result in significant morbidity. However, the underlying molecular mechanism is poorly understood. Here, we employed BALB/c ByJ mice inflected with SP, IAV, IAV followed by SP (IAV+SP) and PBS (Control) as models to survey the global gene expression using digital gene expression (DGE) profiling. We attempt to gain insights into the underlying genetic basis of this synergy at the expression level. Gene expression profiles were obtain using the Illimina/Hisseq sequencing technique, and further analyzed by enrichment analysis of Gene Ontology (GO) and Pathway function. The hematoxylin-eosin (HE) staining revealed different tissue changes in groups during which IAV+SP group showed the most severe cell apoptosis. Compared with Control, a total of 2731, 3221 and 3946 differentially expressed genes (DEGs) were detected in SP, IAV and IAV+SP respectively. Besides, sixty-two GO terms were identified by Gene Ontology functional enrichment analysis, such as cell killing, biological regulation, response to stimulus, signaling, biological adhesion, enzyme regulator activity, receptor regulator activity and translation regulator activity. Pathway significant enrichment analysis indicated the dysregulation of multiple pathways, including apoptosis pathway. Among these, five selected genes were further verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). This study shows that infection with SP, IAV or IAV+SP induces apoptosis with different degrees which might provide insights into the molecular mechanisms to facilitate further research.

LncRNA expression and implication in osteosarcoma: a systematic review and meta-analysis

Directory of Open Access Journals (Sweden)

Wang Y

2017-11-01

Full Text Available Ying Wang,1,2,* Yuelong Huang,2,* Peng Xiang,3 Wei Tian2 1Department of Molecular Orthopaedics, Beijing Institute of Traumatology and Orthopaedics, 2Department of Spinal Surgery, Beijing Jishuitan Hospital, The Fourth Clinical Medical College of Peking University, 3Department of Urology, Peking University First Hospital, Beijing, People’s Republic of China *These authors contributed equally to this work Purpose: Osteosarcoma is the most prevalent primary bone tumor in children, adolescents, and older adults, typically presenting with poor survival outcomes. In recent years, ample evidence has shown that many long noncoding RNAs (lncRNAs have been aberrantly expressed in osteosarcoma, demonstrating their potential to serve as prognostic markers. In this study, we performed a meta-analysis on four lncRNAs (TUG1, UCA1, BCAR4, and HULC to systematically evaluate their prognostic value in osteosarcoma.Materials and methods: The eligible articles were systematically searched in PubMed, Web of Science, Embase, and Elsevier ScienceDirect (up to September 22, 2017, and one meta-analysis concerning the association between lncRNA expression and the overall survival (OS of osteosarcoma patients was performed. Survival outcomes were analyzed by OS. Subgroup analyses were performed.Results: A total of 1,361 patients with osteosarcoma and 12 lncRNAs from 16 articles were included in the study. Of the listed lncRNAs, the high expression of 10 lncRNAs indicated worse survival outcomes, while only two lncRNAs were shown to positively affect patients’ OS.Conclusion: This meta-analysis indicated that the abnormally expressed lncRNAs might significantly affect the survival of osteosarcoma patients. Combined use of these lncRNAs may serve as potential novel biomarkers for the indication of clinical outcomes of osteosarcoma patients as well as the selection of adjuvant chemotherapy strategies for clinical treatment of this disease. Keywords: lncRNAs, osteosarcoma

Explorative data analysis of MCL reveals gene expression networks implicated in survival and prognosis supported by explorative CGH analysis