WorldWideScience

Sample records for gene selection method

  1. A simulation to analyze feature selection methods utilizing gene ontology for gene expression classification.

    Science.gov (United States)

    Gillies, Christopher E; Siadat, Mohammad-Reza; Patel, Nilesh V; Wilson, George D

    2013-12-01

    Gene expression profile classification is a pivotal research domain assisting in the transformation from traditional to personalized medicine. A major challenge associated with gene expression data classification is the small number of samples relative to the large number of genes. To address this problem, researchers have devised various feature selection algorithms to reduce the number of genes. Recent studies have been experimenting with the use of semantic similarity between genes in Gene Ontology (GO) as a method to improve feature selection. While there are few studies that discuss how to use GO for feature selection, there is no simulation study that addresses when to use GO-based feature selection. To investigate this, we developed a novel simulation, which generates binary class datasets, where the differentially expressed genes between two classes have some underlying relationship in GO. This allows us to investigate the effects of various factors such as the relative connectedness of the underlying genes in GO, the mean magnitude of separation between differentially expressed genes denoted by δ, and the number of training samples. Our simulation results suggest that the connectedness in GO of the differentially expressed genes for a biological condition is the primary factor for determining the efficacy of GO-based feature selection. In particular, as the connectedness of differentially expressed genes increases, the classification accuracy improvement increases. To quantify this notion of connectedness, we defined a measure called Biological Condition Annotation Level BCAL(G), where G is a graph of differentially expressed genes. Our main conclusions with respect to GO-based feature selection are the following: (1) it increases classification accuracy when BCAL(G) ≥ 0.696; (2) it decreases classification accuracy when BCAL(G) ≤ 0.389; (3) it provides marginal accuracy improvement when 0.389genes in a biological condition increases beyond 50 and

  2. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  3. Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

    Directory of Open Access Journals (Sweden)

    Abdel Samee Nagwan M

    2012-08-01

    Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

  4. 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.

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

    KAUST Repository

    Abusamra, Heba

    2013-05-01

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

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

    KAUST Repository

    Abusamra, Heba

    2013-11-01

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

  7. Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

    Science.gov (United States)

    Dashtban, M; Balafar, Mohammadali

    2017-03-01

    Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification.

  9. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  10. Locating disease genes using Bayesian variable selection with the Haseman-Elston method

    Directory of Open Access Journals (Sweden)

    He Qimei

    2003-12-01

    Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.

  11. Selective Gene Expression Analysis of Muscular and Vascular Components in Hearts Using Laser Microdissection Method

    Directory of Open Access Journals (Sweden)

    Ayami Ikeda

    2012-01-01

    Full Text Available Background. The heart consists of various kinds of cell components. However, it has not been feasible to separately analyze the gene expression of individual components. The laser microdissection (LMD method, a new technology to collect target cells from the microscopic regions, has been used for malignancies. We sought to establish a method to selectively collect the muscular and vascular regions from the heart sections and to compare the marker gene expressions with this method. Methods and Results. Frozen left ventricle sections were obtained from Wistar-Kyoto rats (WKY and stroke-prone spontaneously hypertensive rats (SHR-SP at 24 weeks of age. Using the LMD method, the muscular and vascular regions were selectively collected under microscopic guidance. Real-time RT-PCR analysis showed that brain-type natriuretic peptide (BNP, a marker of cardiac myocytes, was expressed in the muscular samples, but not in the vascular samples, whereas α-smooth muscle actin, a marker of smooth muscle cells, was detected only in the vascular samples. Moreover, SHR-SP had significantly greater BNP upregulation than WKY (<0.05 in the muscular samples. Conclusions. The LMD method enabled us to separately collect the muscular and vascular samples from myocardial sections and to selectively evaluate mRNA expressions of the individual tissue component.

  12. A combinational feature selection and ensemble neural network method for classification of gene expression data

    Directory of Open Access Journals (Sweden)

    Jiang Tianzi

    2004-09-01

    Full Text Available Abstract Background Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for a particular disease. To date, this problem has received most attention in the context of cancer research, especially in tumor classification. Various feature selection methods and classifier design strategies also have been generally used and compared. However, most published articles on tumor classification have applied a certain technique to a certain dataset, and recently several researchers compared these techniques based on several public datasets. But, it has been verified that differently selected features reflect different aspects of the dataset and some selected features can obtain better solutions on some certain problems. At the same time, faced with a large amount of microarray data with little knowledge, it is difficult to find the intrinsic characteristics using traditional methods. In this paper, we attempt to introduce a combinational feature selection method in conjunction with ensemble neural networks to generally improve the accuracy and robustness of sample classification. Results We validate our new method on several recent publicly available datasets both with predictive accuracy of testing samples and through cross validation. Compared with the best performance of other current methods, remarkably improved results can be obtained using our new strategy on a wide range of different datasets. Conclusions Thus, we conclude that our methods can obtain more information in microarray data to get more accurate classification and also can help to extract the latent marker genes of the diseases for better diagnosis and treatment.

  13. A Novel Gene Selection Method Based on Sparse Representation and Max-Relevance and Min-Redundancy.

    Science.gov (United States)

    Chen, Min; He, Xiaoming; Duan, ShaoBin; Deng, YingWei

    2017-01-01

    Gene selection method as an important data preprocessing work has been followed. The criteria Maximum relevance and minimum redundancy (MRMR) has been commonly used for gene selection, which has a satisfactory performance in evaluating the correlation between two genes. However, for viewing genes in isolation, it ignores the influence of other genes. In this study, we propose a new method based on sparse representation and MRMR algorithm (SRCMRM), using the sparse representation coefficient to represent the relevance of genes and correlation between genes and categories. The SRCMRMR algorithm contains two steps. Firstly, the genes irrelevant to the classification target are removed by using sparse representation coefficient. Secondly, sparse representation coefficient is used to calculate the correlation between genes and the most representative gene with the highest evaluation. To validate the performance of the SRCMRM, our method is compared with various algorithms. The proposed method achieves better classification accuracy for all datasets. The effectiveness and stability of our method have been proven through various experiments, which means that our method has practical significance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  14. Rank sum method for related gene selection and its application to tumor diagnosis

    Institute of Scientific and Technical Information of China (English)

    DENG Lin; MA Jinwen; PEI Jian

    2004-01-01

    Tumor diagnosis by analyzing gene expression profiles becomes an interesting topic in bioinformatics and the main problem is to identify the genes related to a tumor.This paper proposes a rank sum method to identify the related genes based on the rank sum test theory in statistics.The tumor diagnosis system is constructed by the support vector machine (SVM) trained on the set of the related gene expression profiles. The experiments demonstrate that the constructed tumor diagnosis system with the rank sum method and SVM can reach an accuracy level of 96.2% on the colon data and 100 % on the leukemia data.

  15. Development of a protocol for selection of genes fit for the in vivo knockdown method and its application to insulin receptor substrate genes in mice.

    Science.gov (United States)

    Saito, Mikako; Kakutani, Yukari; Kaburagi, Misako; Funabashi, Hisakage; Matsuoka, Hideaki

    2013-01-01

    Prediabetes model mice in which more than one gene associated with diabetes is knocked down simultaneously are potentially useful for pharmaceutical and medical studies of diabetes. However, the effective conditions for sufficient knockdown in vivo are dependent on the intrinsic properties of the target genes. It is necessary to investigate which genes are applicable or not to the in vivo knockdown method. In this study, insulin receptor substrate 1 and 2 (Irs-1, Irs-2) were selected as target genes. Effective siRNAs against the respective genes were designed, and their efficacy was confirmed by cell-based experiments. Based on the results of siRNAs, shRNA expression vectors against Irs-1 and Irs-2 were constructed, respectively. Their efficacy was also confirmed by cell-based experiments. A hydrodynamic method was applied to the delivery of the vectors to mice. This method was found to be effective for predominant delivery to the liver by demonstrative delivery of an EGFP expression vector and successive histochemical analysis. Fifty micrograms of the shRNA expression vector was injected into the tail vein. After 24 h, the liver, pancreas, and muscle were isolated, and the expression levels of Irs-1 and Irs-2 were analyzed by quantitative RT-PCR. In the liver, Irs-2 was effectively knocked down to 60% of the control level, but Irs-1 was not influenced even under the same conditions. The protocol developed here is feasible for the selection of genes fit for in vivo knockdown method.

  16. Development of a two-stage gene selection method that incorporates a novel hybrid approach using the cuckoo optimization algorithm and harmony search for cancer classification.

    Science.gov (United States)

    Elyasigomari, V; Lee, D A; Screen, H R C; Shaheed, M H

    2017-03-01

    For each cancer type, only a few genes are informative. Due to the so-called 'curse of dimensionality' problem, the gene selection task remains a challenge. To overcome this problem, we propose a two-stage gene selection method called MRMR-COA-HS. In the first stage, the minimum redundancy and maximum relevance (MRMR) feature selection is used to select a subset of relevant genes. The selected genes are then fed into a wrapper setup that combines a new algorithm, COA-HS, using the support vector machine as a classifier. The method was applied to four microarray datasets, and the performance was assessed by the leave one out cross-validation method. Comparative performance assessment of the proposed method with other evolutionary algorithms suggested that the proposed algorithm significantly outperforms other methods in selecting a fewer number of genes while maintaining the highest classification accuracy. The functions of the selected genes were further investigated, and it was confirmed that the selected genes are biologically relevant to each cancer type.

  17. Selections of data preprocessing methods and similarity metrics for gene cluster analysis

    Institute of Scientific and Technical Information of China (English)

    YANG Chunmei; WAN Baikun; GAO Xiaofeng

    2006-01-01

    Clustering is one of the major exploratory techniques for gene expression data analysis. Only with suitable similarity metrics and when datasets are properly preprocessed, can results of high quality be obtained in cluster analysis. In this study, gene expression datasets with external evaluation criteria were preprocessed as normalization by line, normalization by column or logarithm transformation by base-2, and were subsequently clustered by hierarchical clustering, k-means clustering and self-organizing maps (SOMs) with Pearson correlation coefficient or Euclidean distance as similarity metric. Finally, the quality of clusters was evaluated by adjusted Rand index. The results illustrate that k-means clustering and SOMs have distinct advantages over hierarchical clustering in gene clustering, and SOMs are a bit better than k-means when randomly initialized. It also shows that hierarchical clustering prefers Pearson correlation coefficient as similarity metric and dataset normalized by line. Meanwhile, k-means clustering and SOMs can produce better clusters with Euclidean distance and logarithm transformed datasets. These results will afford valuable reference to the implementation of gene expression cluster analysis.

  18. Confirming candidate genes for longevity in Drosophila melanogaster using two different genetic backgrounds and selection methods

    DEFF Research Database (Denmark)

    Wit, Janneke; Frydenberg, Jane; Sarup, Pernille Merete

    2013-01-01

    Elucidating genes that affect life span or that can be used as biomarkers for ageing has received attention in diverse studies in recent years. Using model organisms and various approaches several genes have been linked to the longevity phenotype. For Drosophila melanogaster those studies have...... usually focussed on one sex and on flies originating from one genetic background, and results from different studies often do not overlap. Using D. melanogaster selected for increased longevity we aimed to find robust longevity related genes by examining gene expression in both sexes of flies originating...... from different genetic backgrounds. Further, we compared expression changes across three ages, when flies were young, middle aged or old, to examine how candidate gene expression changes with the onset of ageing. We selected 10 genes based on their expression differences in prior microarray studies...

  19. Random forest for gene selection and microarray data classification.

    Science.gov (United States)

    Moorthy, Kohbalan; Mohamad, Mohd Saberi

    2011-01-01

    A random forest method has been selected to perform both gene selection and classification of the microarray data. In this embedded method, the selection of smallest possible sets of genes with lowest error rates is the key factor in achieving highest classification accuracy. Hence, improved gene selection method using random forest has been proposed to obtain the smallest subset of genes as well as biggest subset of genes prior to classification. The option for biggest subset selection is done to assist researchers who intend to use the informative genes for further research. Enhanced random forest gene selection has performed better in terms of selecting the smallest subset as well as biggest subset of informative genes with lowest out of bag error rates through gene selection. Furthermore, the classification performed on the selected subset of genes using random forest has lead to lower prediction error rates compared to existing method and other similar available methods.

  20. Multiclass gene selection using Pareto-fronts.

    Science.gov (United States)

    Rajapakse, Jagath C; Mundra, Piyushkumar A

    2013-01-01

    Filter methods are often used for selection of genes in multiclass sample classification by using microarray data. Such techniques usually tend to bias toward a few classes that are easily distinguishable from other classes due to imbalances of strong features and sample sizes of different classes. It could therefore lead to selection of redundant genes while missing the relevant genes, leading to poor classification of tissue samples. In this manuscript, we propose to decompose multiclass ranking statistics into class-specific statistics and then use Pareto-front analysis for selection of genes. This alleviates the bias induced by class intrinsic characteristics of dominating classes. The use of Pareto-front analysis is demonstrated on two filter criteria commonly used for gene selection: F-score and KW-score. A significant improvement in classification performance and reduction in redundancy among top-ranked genes were achieved in experiments with both synthetic and real-benchmark data sets.

  1. A Filter Feature Selection Method Based on MFA Score and Redundancy Excluding and It's Application to Tumor Gene Expression Data Analysis.

    Science.gov (United States)

    Li, Jiangeng; Su, Lei; Pang, Zenan

    2015-12-01

    Feature selection techniques have been widely applied to tumor gene expression data analysis in recent years. A filter feature selection method named marginal Fisher analysis score (MFA score) which is based on graph embedding has been proposed, and it has been widely used mainly because it is superior to Fisher score. Considering the heavy redundancy in gene expression data, we proposed a new filter feature selection technique in this paper. It is named MFA score+ and is based on MFA score and redundancy excluding. We applied it to an artificial dataset and eight tumor gene expression datasets to select important features and then used support vector machine as the classifier to classify the samples. Compared with MFA score, t test and Fisher score, it achieved higher classification accuracy.

  2. Bioinformatics methods for identifying candidate disease genes

    NARCIS (Netherlands)

    Driel, M.A. van; Brunner, H.G.

    2006-01-01

    With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information i

  3. Minimum Bayesian error probability-based gene subset selection.

    Science.gov (United States)

    Li, Jian; Yu, Tian; Wei, Jin-Mao

    2015-01-01

    Sifting functional genes is crucial to the new strategies for drug discovery and prospective patient-tailored therapy. Generally, simply generating gene subset by selecting the top k individually superior genes may obtain an inferior gene combination, for some selected genes may be redundant with respect to some others. In this paper, we propose to select gene subset based on the criterion of minimum Bayesian error probability. The method dynamically evaluates all available genes and sifts only one gene at a time. A gene is selected if its combination with the other selected genes can gain better classification information. Within the generated gene subset, each individual gene is the most discriminative one in comparison with those that classify cancers in the same way as this gene does and different genes are more discriminative in combination than in individual. The genes selected in this way are likely to be functional ones from the system biology perspective, for genes tend to co-regulate rather than regulate individually. Experimental results show that the classifiers induced based on this method are capable of classifying cancers with high accuracy, while only a small number of genes are involved.

  4. Old genes experience stronger translational selection than young genes.

    Science.gov (United States)

    Yin, Hongyan; Ma, Lina; Wang, Guangyu; Li, Mengwei; Zhang, Zhang

    2016-09-15

    Selection on synonymous codon usage for translation efficiency and/or accuracy has been identified as a widespread mechanism in many living organisms. However, it remains unknown whether translational selection associates closely with gene age and acts differentially on genes with different evolutionary ages. To address this issue, here we investigate the strength of translational selection acting on different aged genes in human. Our results show that old genes present stronger translational selection than young genes, demonstrating that translational selection correlates positively with gene age. We further explore the difference of translational selection in duplicates vs. singletons and in housekeeping vs. tissue-specific genes. We find that translational selection acts comparably in old singletons and old duplicates and stronger translational selection in old genes is contributed primarily by housekeeping genes. For young genes, contrastingly, singletons experience stronger translational selection than duplicates, presumably due to redundant function of duplicated genes during their early evolutionary stage. Taken together, our results indicate that translational selection acting on a gene would not be constant during all stages of evolution, associating closely with gene age. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. A PCR-based sex determination method for possible application in caprine gender selection by simultaneous amplification of the Sry and Aml-X genes.

    Science.gov (United States)

    Phua, Alice Choon Yen; Abdullah, Ramli Bin; Mohamed, Zulqarnain

    2003-08-01

    Sex determination of livestock is performed to achieve the objectives of livestock breeding programmes. Techniques for sex determination have evolved from karyotyping to detecting Y-specific antigens and recently to the polymerase chain reaction (PCR), which appears to be the most sensitive, accurate, rapid and reliable method to date. In this study, a PCR-based sex determination method for potential application in goat breeding programmes was developed. Primers were designed to amplify a portion of the X amelogenin gene (Aml-X) on the X chromosome to give a 300 bp product and Sry gene on the Y chromosome to give a 116 bp product. PCR optimization was performed using DNA template extracted from a whole blood sample of Jermasia goats (German Fawn x Katjang) of both sexes. It was possible to identify the sex chromosomes by amplifying both male- and female-specific genes simultaneously in a duplex reaction with males yielding two bands and females yielding one band. The Aml-X primer set, which served as an internal control primer, did not interfere with amplification of the Y-specific sequence even when a low amount of DNA (1 ng) was used. The duplex reaction subjected to a blind test showed 100% (14/14) concordance, proving its accuracy and reliability. The primer sets used were found to be highly specific and were suitable for gender selection of goats.

  6. Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas; Andersson, Bo

    2014-01-01

    requires new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing...... of approaching the selection of COTS systems as viewing them as a ‘means’ to reach organizational ‘ends’ is different from the mainstream views of information systems development, namely the view that sees information systems development as a problem-solving process, and the underlying ontological view in other...

  7. A Bayesian variable selection procedure for ranking overlapping gene sets

    DEFF Research Database (Denmark)

    Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc

    2012-01-01

    described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian...... variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows. Results We used a Bayesian variable selection method to prioritize Kyoto Encyclopedia of Genes and Genomes pathways. We used our...... data to study how the variable selection method was affected by overlaps among the pathways. In addition, we compared our approach to another that ignores the overlaps, and studied the differences in the prioritization. The variable selection method was robust to a change in prior probability...

  8. Selection of Phototransduction Genes in Homo sapiens.

    Science.gov (United States)

    Christopher, Mark; Scheetz, Todd E; Mullins, Robert F; Abràmoff, Michael D

    2013-08-13

    We investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level. SNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively. Six of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes. There is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.

  9. A Bayesian variable selection procedure to rank overlapping gene sets

    Directory of Open Access Journals (Sweden)

    Skarman Axel

    2012-05-01

    Full Text Available Abstract Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows. Results We used a Bayesian variable selection method to prioritize Kyoto Encyclopedia of Genes and Genomes pathways. We used our data to study how the variable selection method was affected by overlaps among the pathways. In addition, we compared our approach to another that ignores the overlaps, and studied the differences in the prioritization. The variable selection method was robust to a change in prior probability and stable given a limited number of observations. Conclusions Bayesian variable selection is a useful way to prioritize gene sets while considering their overlaps. Ignoring the overlaps gives different and possibly misleading results. Additional procedures may be needed in cases of highly overlapping pathways that are hard to prioritize.

  10. Method selection in adaptation research

    NARCIS (Netherlands)

    Werners, Saskia Elisabeth; Loon-Steensma, van Jantsje Mintsje; Oost, Albert Peter

    2016-01-01

    Many methods are available to support adaptation planning. Yet there is little guidance on their selection. A recently developed diagnostic framework offers a structured set of criteria to choose research methods for specific adaptation questions. It has been derived from science-driven cases mos

  11. Selective Smoothed Finite Element Method

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The paper examines three selective schemes for the smoothed finite element method (SFEM) which was formulated by incorporating a cell-wise strain smoothing operation into the standard compatible finite element method (FEM). These selective SFEM schemes were formulated based on three selective integration FEM schemes with similar properties found between the number of smoothing cells in the SFEM and the number of Gaussian integration points in the FEM. Both scheme 1 and scheme 2 are free of nearly incompressible locking, but scheme 2 is more general and gives better results than scheme 1. In addition, scheme 2 can be applied to anisotropic and nonlinear situations, while scheme 1 can only be applied to isotropic and linear situations. Scheme 3 is free of shear locking. This scheme can be applied to plate and shell problems. Results of the numerical study show that the selective SFEM schemes give more accurate results than the FEM schemes.

  12. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  13. Bioinformatics methods for identifying candidate disease genes

    Directory of Open Access Journals (Sweden)

    van Driel Marc A

    2006-06-01

    Full Text Available Abstract With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies.

  14. Gene selection in class space for molecular classification of cancer

    Institute of Scientific and Technical Information of China (English)

    ZHANG Junying; Yue Joseph WANG; Javed KHAN; Robert CLARKE

    2004-01-01

    Gene selection (feature selection) is generally performed in gene space (feature space), where a very serious curse of dimensionality problem always exists because the number of genes is much larger than the number of samples in gene space (G-space). This results in difficulty in modeling the data set in this space and the low confidence of the result of gene selection. How to find a gene subset in this case is a challenging subject. In this paper, the above G-space is transformed into its dual space, referred to as class space (C-space) such that the number of dimensions is the very number of classes of the samples in G-space and the number of samples in C-space is the number of genes in G-space. It is obvious that the curse of dimensionality in C-space does not exist. A new gene selection method which is based on the principle of separating different classes as far as possible is presented with the help of Principal Component Analysis (PCA). The experimental results on gene selection for real data set are evaluated with Fisher criterion, weighted Fisher criterion as well as leave-one-out cross validation, showing that the method presented here is effective and efficient.

  15. Genes under positive selection in Escherichia coli

    DEFF Research Database (Denmark)

    Petersen, Lise; Bollback, J.P.; Dimmic, Matt

    2007-01-01

    We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome...

  16. Genes under positive selection in Escherichia coli

    DEFF Research Database (Denmark)

    Petersen, Lise; Bollback, J.P.; Dimmic, Matt

    2007-01-01

    We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome...

  17. Meta-analysis based variable selection for gene expression data.

    Science.gov (United States)

    Li, Quefeng; Wang, Sijian; Huang, Chiang-Ching; Yu, Menggang; Shao, Jun

    2014-12-01

    Recent advance in biotechnology and its wide applications have led to the generation of many high-dimensional gene expression data sets that can be used to address similar biological questions. Meta-analysis plays an important role in summarizing and synthesizing scientific evidence from multiple studies. When the dimensions of datasets are high, it is desirable to incorporate variable selection into meta-analysis to improve model interpretation and prediction. According to our knowledge, all existing methods conduct variable selection with meta-analyzed data in an "all-in-or-all-out" fashion, that is, a gene is either selected in all of studies or not selected in any study. However, due to data heterogeneity commonly exist in meta-analyzed data, including choices of biospecimens, study population, and measurement sensitivity, it is possible that a gene is important in some studies while unimportant in others. In this article, we propose a novel method called meta-lasso for variable selection with high-dimensional meta-analyzed data. Through a hierarchical decomposition on regression coefficients, our method not only borrows strength across multiple data sets to boost the power to identify important genes, but also keeps the selection flexibility among data sets to take into account data heterogeneity. We show that our method possesses the gene selection consistency, that is, when sample size of each data set is large, with high probability, our method can identify all important genes and remove all unimportant genes. Simulation studies demonstrate a good performance of our method. We applied our meta-lasso method to a meta-analysis of five cardiovascular studies. The analysis results are clinically meaningful.

  18. Genes under positive selection in Escherichia coli

    DEFF Research Database (Denmark)

    Petersen, Lise; Bollback, Jonathan P; Dimmic, Matt

    2007-01-01

    We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome......, including cell surface proteins such as beta barrel porins, presumably because of the involvement of these genes in evolutionary arms races with other bacteria, phages, and/or the host immune system. Structural mapping of positively selected sites on trans-membrane beta barrel porins reveals...... that the residues under positive selection occur almost exclusively in the extracellular region of the proteins that are enriched with sites known to be targets of phages, colicins, or the host immune system. More surprisingly, we also find a number of other categories of genes that show very strong evidence...

  19. Gene Ontology based housekeeping gene selection for RNA-seq normalization.

    Science.gov (United States)

    Chen, Chien-Ming; Lu, Yu-Lun; Sio, Chi-Pong; Wu, Guan-Chung; Tzou, Wen-Shyong; Pai, Tun-Wen

    2014-06-01

    RNA-seq analysis provides a powerful tool for revealing relationships between gene expression level and biological function of proteins. In order to identify differentially expressed genes among various RNA-seq datasets obtained from different experimental designs, an appropriate normalization method for calibrating multiple experimental datasets is the first challenging problem. We propose a novel method to facilitate biologists in selecting a set of suitable housekeeping genes for inter-sample normalization. The approach is achieved by adopting user defined experimentally related keywords, GO annotations, GO term distance matrices, orthologous housekeeping gene candidates, and stability ranking of housekeeping genes. By identifying the most distanced GO terms from query keywords and selecting housekeeping gene candidates with low coefficients of variation among different spatio-temporal datasets, the proposed method can automatically enumerate a set of functionally irrelevant housekeeping genes for pratical normalization. Novel and benchmark testing RNA-seq datasets were applied to demostrate that different selections of housekeeping gene lead to strong impact on differential gene expression analysis, and compared results have shown that our proposed method outperformed other traditional approaches in terms of both sensitivity and specificity. The proposed mechanism of selecting appropriate houskeeping genes for inter-dataset normalization is robust and accurate for differential expression analyses. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Gene Prediction Using Multinomial Probit Regression with Bayesian Gene Selection

    Directory of Open Access Journals (Sweden)

    Xiaodong Wang

    2004-01-01

    Full Text Available A critical issue for the construction of genetic regulatory networks is the identification of network topology from data. In the context of deterministic and probabilistic Boolean networks, as well as their extension to multilevel quantization, this issue is related to the more general problem of expression prediction in which we want to find small subsets of genes to be used as predictors of target genes. Given some maximum number of predictors to be used, a full search of all possible predictor sets is combinatorially prohibitive except for small predictors sets, and even then, may require supercomputing. Hence, suboptimal approaches to finding predictor sets and network topologies are desirable. This paper considers Bayesian variable selection for prediction using a multinomial probit regression model with data augmentation to turn the multinomial problem into a sequence of smoothing problems. There are multiple regression equations and we want to select the same strongest genes for all regression equations to constitute a target predictor set or, in the context of a genetic network, the dependency set for the target. The probit regressor is approximated as a linear combination of the genes and a Gibbs sampler is employed to find the strongest genes. Numerical techniques to speed up the computation are discussed. After finding the strongest genes, we predict the target gene based on the strongest genes, with the coefficient of determination being used to measure predictor accuracy. Using malignant melanoma microarray data, we compare two predictor models, the estimated probit regressors themselves and the optimal full-logic predictor based on the selected strongest genes, and we compare these to optimal prediction without feature selection.

  1. Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication

    Directory of Open Access Journals (Sweden)

    Sørensen Peter

    2007-11-01

    Full Text Available Abstract A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.

  2. Gene-level integrated metric of negative selection (GIMS prioritizes candidate genes for nephrotic syndrome.

    Directory of Open Access Journals (Sweden)

    Matthew G Sampson

    Full Text Available Nephrotic syndrome (NS gene discovery efforts are now occurring in small kindreds and cohorts of sporadic cases. Power to identify causal variants in these groups beyond a statistical significance threshold is challenging due to small sample size and/or lack of family information. There is a need to develop novel methods to identify NS-associated variants. One way to determine putative functional relevance of a gene is to measure its strength of negative selection, as variants in genes under strong negative selection are more likely to be deleterious. We created a gene-level, integrated metric of negative selection (GIMS score for 20,079 genes by combining multiple comparative genomics and population genetics measures. To understand the utility of GIMS for NS gene discovery, we examined this score in a diverse set of NS-relevant gene sets. These included genes known to cause monogenic forms of NS in humans as well as genes expressed in the cells of the glomerulus and, particularly, the podocyte. We found strong negative selection in the following NS-relevant gene sets: (1 autosomal-dominant Mendelian focal segmental glomerulosclerosis (FSGS genes (p = 0.03 compared to reference, (2 glomerular expressed genes (p = 4×10(-23, and (3 predicted podocyte genes (p = 3×10(-9. Eight genes causing autosomal dominant forms of FSGS had a stronger combined score of negative selection and podocyte enrichment as compared to all other genes (p = 1 x 10(-3. As a whole, recessive FSGS genes were not enriched for negative selection. Thus, we also created a transcript-level, integrated metric of negative selection (TIMS to quantify negative selection on an isoform level. These revealed transcripts of known autosomal recessive disease-causing genes that were nonetheless under strong selection. We suggest that a filtering strategy that includes measuring negative selection on a gene or isoform level could aid in identifying NS-related genes. Our GIMS and TIMS

  3. Gene-level integrated metric of negative selection (GIMS) prioritizes candidate genes for nephrotic syndrome.

    Science.gov (United States)

    Sampson, Matthew G; Gillies, Christopher E; Ju, Wenjun; Kretzler, Matthias; Kang, Hyun Min

    2013-01-01

    Nephrotic syndrome (NS) gene discovery efforts are now occurring in small kindreds and cohorts of sporadic cases. Power to identify causal variants in these groups beyond a statistical significance threshold is challenging due to small sample size and/or lack of family information. There is a need to develop novel methods to identify NS-associated variants. One way to determine putative functional relevance of a gene is to measure its strength of negative selection, as variants in genes under strong negative selection are more likely to be deleterious. We created a gene-level, integrated metric of negative selection (GIMS) score for 20,079 genes by combining multiple comparative genomics and population genetics measures. To understand the utility of GIMS for NS gene discovery, we examined this score in a diverse set of NS-relevant gene sets. These included genes known to cause monogenic forms of NS in humans as well as genes expressed in the cells of the glomerulus and, particularly, the podocyte. We found strong negative selection in the following NS-relevant gene sets: (1) autosomal-dominant Mendelian focal segmental glomerulosclerosis (FSGS) genes (p = 0.03 compared to reference), (2) glomerular expressed genes (p = 4×10(-23)), and (3) predicted podocyte genes (p = 3×10(-9)). Eight genes causing autosomal dominant forms of FSGS had a stronger combined score of negative selection and podocyte enrichment as compared to all other genes (p = 1 x 10(-3)). As a whole, recessive FSGS genes were not enriched for negative selection. Thus, we also created a transcript-level, integrated metric of negative selection (TIMS) to quantify negative selection on an isoform level. These revealed transcripts of known autosomal recessive disease-causing genes that were nonetheless under strong selection. We suggest that a filtering strategy that includes measuring negative selection on a gene or isoform level could aid in identifying NS-related genes. Our GIMS and TIMS scores are

  4. Chaotic genetic algorithm for gene selection and classification problems.

    Science.gov (United States)

    Chuang, Li-Yeh; Yang, Cheng-San; Li, Jung-Chike; Yang, Cheng-Hong

    2009-10-01

    Pattern recognition techniques suffer from a well-known curse, the dimensionality problem. The microarray data classification problem is a classical complex pattern recognition problem. Selecting relevant genes from microarray data poses a formidable challenge to researchers due to the high-dimensionality of features, multiclass categories being involved, and the usually small sample size. The goal of feature (gene) selection is to select those subsets of differentially expressed genes that are potentially relevant for distinguishing the sample classes. In this paper, information gain and chaotic genetic algorithm are proposed for the selection of relevant genes, and a K-nearest neighbor with the leave-one-out crossvalidation method serves as a classifier. The chaotic genetic algorithm is modified by using the chaotic mutation operator to increase the population diversity. The enhanced population diversity expands the GA's search ability. The proposed approach is tested on 10 microarray data sets from the literature. The experimental results show that the proposed method not only effectively reduced the number of gene expression levels, but also achieved lower classification error rates than other methods.

  5. Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

  6. Easy-to-use strategy for reference gene selection in quantitative real-time PCR experiments.

    Science.gov (United States)

    Klenke, Stefanie; Renckhoff, Kristina; Engler, Andrea; Peters, Jürgen; Frey, Ulrich H

    2016-12-01

    Real-time PCR is an indispensable technique for mRNA expression analysis but conclusions depend on appropriate reference gene selection. However, while reference gene selection has been a topic of publications, this issue is often disregarded when measuring target mRNA expression. Therefore, we (1) evaluated the frequency of appropriate reference gene selection, (2) suggest an easy-to-use tool for least variability reference gene selection, (3) demonstrate application of this tool, and (4) show effects on target gene expression profiles. All 2015 published articles in Naunyn-Schmiedeberg's Archives of Pharmacology were screened for the use of quantitative real-time PCR analysis and selection of reference genes. Target gene expression (Vegfa, Grk2, Sirt4, and Timp3) in H9c2 cells was analyzed following various interventions (hypoxia, hyperglycemia, and/or isoflurane exposure with and without subsequent hypoxia) in relation to putative reference genes (Actb, Gapdh, B2m, Sdha, and Rplp1) using the least variability method vs. an arbitrarily selected but established reference gene. In the vast majority (18 of 21) of papers, no information was provided regarding selection of an appropriate reference gene. In only 1 of 21 papers, a method of appropriate reference gene selection was described and in 2 papers reference gene selection remains unclear. The method of reference gene selection had major impact on interpretation of target gene expression. With hypoxia, for instance, the least variability gene was Rplp1 and target gene expression (Vefga) heavily showed a 2-fold up-regulation (p = 0.022) but no change (p = 0.3) when arbitrarily using Gapdh. Frequency of appropriate reference gene selection in this journal is low, and we propose our strategy for reference gene selection as an easy tool for proper target gene expression.

  7. An overview on selection methods

    Directory of Open Access Journals (Sweden)

    J. W. H. Swanepoel

    1982-03-01

    Full Text Available In many studies the experimenter has under consideration several (two or more alternatives, and is studying them in order to determine which is the best (with regard to certain specified criteria of “goodness”. Such an experimenter does not wish basically to test hypotheses, or construct confidence intervals, or perform regression analyses (though these may be appropriate parts of his analysis; he does wish to select the best of several alternatives, and the major part of his analysis should therefore be directed towards this goal. It is precisely for this problem that ranking and selection procedures were developed. This paper presents an overview of some recent work in this field, with emphasis on aspects important to experimenters confronted with selection problems. Fixed sample size and sequential procedures for both the indifference zone and subset formulations of the selection problem are discussed.

  8. Development of a Double Nuclear Gene-Targeting Method by Two-Step Transformation Based on a Newly Established Chloramphenicol-Selection System in the Red Alga Cyanidioschyzon merolae

    Science.gov (United States)

    Fujiwara, Takayuki; Ohnuma, Mio; Kuroiwa, Tsuneyoshi; Ohbayashi, Ryudo; Hirooka, Shunsuke; Miyagishima, Shin-Ya

    2017-01-01

    The unicellular red alga Cyanidioschyzon merolae possesses a simple cellular architecture that consists of one mitochondrion, one chloroplast, one peroxisome, one Golgi apparatus, and several lysosomes. The nuclear genome content is also simple, with very little genetic redundancy (16.5 Mbp, 4,775 genes). In addition, molecular genetic tools such as gene targeting and inducible gene expression systems have been recently developed. These cytological features and genetic tractability have facilitated various omics analyses. However, only a single transformation selection marker URA has been made available and thus the application of genetic modification has been limited. Here, we report the development of a nuclear targeting method by using chloramphenicol and the chloramphenicol acetyltransferase (CAT) gene. In addition, we found that at least 200-bp homologous arms are required and 500-bp arms are sufficient for a targeted single-copy insertion of the CAT selection marker into the nuclear genome. By means of a combination of the URA and CAT transformation systems, we succeeded in producing a C. merolae strain that expresses HA-cyclin 1 and FLAG-CDKA from the chromosomal CYC1 and CDKA loci, respectively. These methods of multiple nuclear targeting will facilitate genetic manipulation of C. merolae. PMID:28352279

  9. Development of a Double Nuclear Gene-Targeting Method by Two-Step Transformation Based on a Newly Established Chloramphenicol-Selection System in the Red Alga Cyanidioschyzon merolae.

    Science.gov (United States)

    Fujiwara, Takayuki; Ohnuma, Mio; Kuroiwa, Tsuneyoshi; Ohbayashi, Ryudo; Hirooka, Shunsuke; Miyagishima, Shin-Ya

    2017-01-01

    The unicellular red alga Cyanidioschyzon merolae possesses a simple cellular architecture that consists of one mitochondrion, one chloroplast, one peroxisome, one Golgi apparatus, and several lysosomes. The nuclear genome content is also simple, with very little genetic redundancy (16.5 Mbp, 4,775 genes). In addition, molecular genetic tools such as gene targeting and inducible gene expression systems have been recently developed. These cytological features and genetic tractability have facilitated various omics analyses. However, only a single transformation selection marker URA has been made available and thus the application of genetic modification has been limited. Here, we report the development of a nuclear targeting method by using chloramphenicol and the chloramphenicol acetyltransferase (CAT) gene. In addition, we found that at least 200-bp homologous arms are required and 500-bp arms are sufficient for a targeted single-copy insertion of the CAT selection marker into the nuclear genome. By means of a combination of the URA and CAT transformation systems, we succeeded in producing a C. merolae strain that expresses HA-cyclin 1 and FLAG-CDKA from the chromosomal CYC1 and CDKA loci, respectively. These methods of multiple nuclear targeting will facilitate genetic manipulation of C. merolae.

  10. Isolating gene-corrected stem cells without drug selection.

    Science.gov (United States)

    Hatada, Seigo; Arnold, Larry W; Hatada, Tomoko; Cowhig, John E; Ciavatta, Dominic; Smithies, Oliver

    2005-11-08

    Progress in isolating stem cells from tissues, or generating them from adult cells by nuclear transfer, encourages attempts to use stem cells from affected individuals for gene correction and autologous therapy. Current viral vectors are efficient at introducing transgenic sequences but result in random integrations. Gene targeting, in contrast, can directly correct an affected gene, or incorporate corrective sequences into a site free from undesirable side effects, but efficiency is low. Most current targeting procedures, consequently, use positive-negative selection with drugs, often requiring >/=10 days. This drug selection causes problems with stem cells that differentiate in this time or require feeder cells, because the feeders must be drug resistant and so are not eliminated by the selection. To overcome these problems, we have developed a procedure for isolating gene-corrected stem cells free from feeder cells after 3-5 days culture without drugs. The method is still positive-negative, but the positive and negative drug-resistance genes are replaced with differently colored fluorescence genes. Gene-corrected cells are isolated by FACS. We tested the method with mouse ES cells having a mutant hypoxanthine phosphoribosyltransferase (Hprt) gene and grown on feeder cells. After 5 days in culture, gene-corrected cells were obtained free from feeder cells at a "purity" of >30%, enriched >2,000-fold and with a recovery of approximately 20%. Corrected cells were also isolated singly for clonal expansion. Our FACS-based procedure should be applicable at small or large scale to stem cells that can be cultured (with feeder cells, if necessary) for >/=3 days.

  11. Strong purifying selection at genes escaping X chromosome inactivation.

    Science.gov (United States)

    Park, Chungoo; Carrel, Laura; Makova, Kateryna D

    2010-11-01

    To achieve dosage balance of X-linked genes between mammalian males and females, one female X chromosome becomes inactivated. However, approximately 15% of genes on this inactivated chromosome escape X chromosome inactivation (XCI). Here, using a chromosome-wide analysis of primate X-linked orthologs, we test a hypothesis that such genes evolve under a unique selective pressure. We find that escape genes are subject to stronger purifying selection than inactivated genes and that positive selection does not significantly affect the evolution of these genes. The strength of selection does not differ between escape genes with similar versus different expression levels in males versus females. Intriguingly, escape genes possessing Y homologs evolve under the strongest purifying selection. We also found evidence of stronger conservation in gene expression levels in escape than inactivated genes. We hypothesize that divergence in function and expression between X and Y gametologs is driving such strong purifying selection for escape genes.

  12. A Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas

    new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... the selection of COTS systems as viewing COTS systems as a ‘mean' to reach organizational ‘ends' is different from the mainstream view of information systems development, which view information systems development as a problem solving process, and the underlying ontological view in other COTS selection methods...

  13. Rough set-based feature selection method

    Institute of Scientific and Technical Information of China (English)

    ZHAN Yanmei; ZENG Xiangyang; SUN Jincai

    2005-01-01

    A new feature selection method is proposed based on the discern matrix in rough set in this paper. The main idea of this method is that the most effective feature, if used for classification, can distinguish the most number of samples belonging to different classes. Experiments are performed using this method to select relevant features for artificial datasets and real-world datasets. Results show that the selection method proposed can correctly select all the relevant features of artificial datasets and drastically reduce the number of features at the same time. In addition, when this method is used for the selection of classification features of real-world underwater targets,the number of classification features after selection drops to 20% of the original feature set, and the classification accuracy increases about 6% using dataset after feature selection.

  14. Selection of image acquisition methods

    Science.gov (United States)

    Donnelly, Joseph J.

    1991-05-01

    A comprehensive picture archiving and communications system (PACS), such as the medical diagnostic imaging support (MDIS) system, consists of several interrelated sub systems. The image acquisition subsystem is the means by which images are introduced into the system and as such it is analogous to the ''eyes'' of the system. Images from digital modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) are readily transferable to a PACS since they are acquired in a digital format. Conventional film based analog images are particularly challenging since at no point in their production or display do they exist in an electronic form suitable for transfer to the MDIS system. In recent years, commercial high resolution film digitizers and computed radiology (CR) devices have become available. These devices now provide us with the means to capture conventional radiographic images in a format suitable for transfer to a PACS. Through the careful selection of acquisition devices we can now design an image acquisition subsystem tailored to meet our clinical needs.

  15. Selected methods of nuclear astrophysics

    CERN Document Server

    Dubovichenko, S B

    2012-01-01

    The book covers the certain questions of nuclear physics and nuclear astrophysics of light atomic nuclei and their processes at low and ultralow energies. Some methods of calculation of nuclear characteristics of the thermonuclear processes considered in nuclear astrophysics are given here. The obtained results are directly applicable to the solution of certain nuclear astrophysics problems in the field of description of the thermonuclear processes in the Sun, the stars and the Universe. The book is based on the results of approximately three-four tens of scientific papers generally published in recent five-seven years and consists of three sections. The first of them covers the description of the general methods of calculation of certain nuclear characteristics for the bound states or the continuum of quantum particles. The second section deals with the methods, the computer programs and the results of the phase shift analysis of elastic scattering in the p3He, p6Li, p12C, n12C, p13C, 4He4He and 4He12C nucle...

  16. Methods for Selecting Phage Display Antibody Libraries.

    Science.gov (United States)

    Jara-Acevedo, Ricardo; Diez, Paula; Gonzalez-Gonzalez, Maria; Degano, Rosa Maria; Ibarrola, Nieves; Gongora, Rafael; Orfao, Alberto; Fuentes, Manuel

    2016-01-01

    The selection process aims sequential enrichment of phage antibody display library in clones that recognize the target of interest or antigen as the library undergoes successive rounds of selection. In this review, selection methods most commonly used for phage display antibody libraries have been comprehensively described.

  17. Informative Gene Selection and Direct Classification of Tumor Based on Chi-Square Test of Pairwise Gene Interactions

    Directory of Open Access Journals (Sweden)

    Hongyan Zhang

    2014-01-01

    Full Text Available In efforts to discover disease mechanisms and improve clinical diagnosis of tumors, it is useful to mine profiles for informative genes with definite biological meanings and to build robust classifiers with high precision. In this study, we developed a new method for tumor-gene selection, the Chi-square test-based integrated rank gene and direct classifier (χ2-IRG-DC. First, we obtained the weighted integrated rank of gene importance from chi-square tests of single and pairwise gene interactions. Then, we sequentially introduced the ranked genes and removed redundant genes by using leave-one-out cross-validation of the chi-square test-based Direct Classifier (χ2-DC within the training set to obtain informative genes. Finally, we determined the accuracy of independent test data by utilizing the genes obtained above with χ2-DC. Furthermore, we analyzed the robustness of χ2-IRG-DC by comparing the generalization performance of different models, the efficiency of different feature-selection methods, and the accuracy of different classifiers. An independent test of ten multiclass tumor gene-expression datasets showed that χ2-IRG-DC could efficiently control overfitting and had higher generalization performance. The informative genes selected by χ2-IRG-DC could dramatically improve the independent test precision of other classifiers; meanwhile, the informative genes selected by other feature selection methods also had good performance in χ2-DC.

  18. Selection for Genes Encoding Secreted Proteins and Receptors

    Science.gov (United States)

    Klein, Robert D.; Gu, Qimin; Goddard, Audrey; Rosenthal, Arnon

    1996-07-01

    Extracellular proteins play an essential role in the formation, differentiation, and maintenance of multicellular organisms. Despite that, the systematic identification of genes encoding these proteins has not been possible. We describe here a highly efficient method to isolate genes encoding secreted and membrane-bound proteins by using a single-step selection in yeast. Application of this method, termed signal peptide selection, to various tissues yielded 559 clones that appear to encode known or novel extracellular proteins. These include members of the transforming growth factor and epidermal growth factor protein families, endocrine hormones, tyrosine kinase receptors, serine/threonine kinase receptors, seven transmembrane receptors, cell adhesion molecules, extracellular matrix proteins, plasma proteins, and ion channels. The eventual identification of most, or all, extracellular signaling molecules will advance our understanding of fundamental biological processes and our ability to intervene in disease states.

  19. Evidence based selection of housekeeping genes.

    Directory of Open Access Journals (Sweden)

    Hendrik J M de Jonge

    Full Text Available For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes (reference or internal control genes is required. It is known that commonly used housekeeping genes (e.g. ACTB, GAPDH, HPRT1, and B2M vary considerably under different experimental conditions and therefore their use for normalization is limited. We performed a meta-analysis of 13,629 human gene array samples in order to identify the most stable expressed genes. Here we show novel candidate housekeeping genes (e.g. RPS13, RPL27, RPS20 and OAZ1 with enhanced stability among a multitude of different cell types and varying experimental conditions. None of the commonly used housekeeping genes were present in the top 50 of the most stable expressed genes. In addition, using 2,543 diverse mouse gene array samples we were able to confirm the enhanced stability of the candidate novel housekeeping genes in another mammalian species. Therefore, the identified novel candidate housekeeping genes seem to be the most appropriate choice for normalizing gene expression data.

  20. Mining method selection by integrated AHP and PROMETHEE method.

    Science.gov (United States)

    Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

    2012-03-01

    Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

  1. Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes

    NARCIS (Netherlands)

    Jafrezic, F.; Koning, de D.J.; Boettcher, P.; Bonnet, A.; Buitenhuis, B.; Closset, R.; Dejean, S.; Delmas, C.; Detilleux, J.C.; Dovc, P.; Duval, M.; Foulley, J.L.; Hedegaard, J.; Hoprnshoj, H.; Hulsegge, B.; Janss, L.; Jensen, K.; Jiang, L.; Lavric, M.; Cao Le, K.A.; Lund, M.S.; Malinverni, R.; Marot, G.; Nie, H.; Petzl, W.; Pool, M.H.; Robert-Granie, C.; Cristobal, M.; Schothorst, van E.M.; Schuberth, H.J.; Sorensen, P.; Stella, A.; Tosser-klopp, G.; Waddington, D.; Watson, M.; Yang, M.; Zerbe, H.; Seyfert, H.M.

    2007-01-01

    A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods

  2. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette

    2006-01-01

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

  3. Equipment Selection by using Fuzzy TOPSIS Method

    Science.gov (United States)

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

  4. Minimal gene selection for classification and diagnosis prediction based on gene expression profile

    Directory of Open Access Journals (Sweden)

    Alireza Mehridehnavi

    2013-01-01

    Conclusion: We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time.

  5. Variable selection by lasso-type methods

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2011-09-01

    Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

  6. Positive Selection and the Evolution of izumo Genes in Mammals.

    Science.gov (United States)

    Grayson, Phil; Civetta, Alberto

    2012-01-01

    Most genes linked to male reproductive function have been known to evolve rapidly among species and to show signatures of positive selection. Different male species-specific reproductive strategies have been proposed to underlie positive selection, such as sperm competitive advantage and control over females postmating physiology. However, an underexplored aspect potentially affecting male reproductive gene evolution in mammals is the effect of gene duplications. Here we analyze the molecular evolution of members of the izumo gene family in mammals, a family of four genes mostly expressed in the sperm with known and potential roles in sperm-egg fusion. We confirm a previously reported bout of selection for izumo1 and establish that the bout of selection is restricted to the diversification of species of the superorder Laurasiatheria. None of the izumo genes showed evidence of positive selection in Glires (Rodentia and Lagomorpha), and in the case of the non-testes-specific izumo4, rapid evolution was driven by relaxed selection. We detected evidence of positive selection for izumo3 among Primates. Interestingly, positively selected sites include several serine residues suggesting modifications in protein function and/or localization among Primates. Our results suggest that positive selection is driven by aspects related to species-specific adaptations to fertilization rather than sexual selection.

  7. Positive Selection and the Evolution of izumo Genes in Mammals

    Directory of Open Access Journals (Sweden)

    Phil Grayson

    2012-01-01

    Full Text Available Most genes linked to male reproductive function have been known to evolve rapidly among species and to show signatures of positive selection. Different male species-specific reproductive strategies have been proposed to underlie positive selection, such as sperm competitive advantage and control over females postmating physiology. However, an underexplored aspect potentially affecting male reproductive gene evolution in mammals is the effect of gene duplications. Here we analyze the molecular evolution of members of the izumo gene family in mammals, a family of four genes mostly expressed in the sperm with known and potential roles in sperm-egg fusion. We confirm a previously reported bout of selection for izumo1 and establish that the bout of selection is restricted to the diversification of species of the superorder Laurasiatheria. None of the izumo genes showed evidence of positive selection in Glires (Rodentia and Lagomorpha, and in the case of the non-testes-specific izumo4, rapid evolution was driven by relaxed selection. We detected evidence of positive selection for izumo3 among Primates. Interestingly, positively selected sites include several serine residues suggesting modifications in protein function and/or localization among Primates. Our results suggest that positive selection is driven by aspects related to species-specific adaptations to fertilization rather than sexual selection.

  8. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  9. Selectivity of catalytic methods of determination.

    Science.gov (United States)

    Otto, M; Mueller, H; Werner, G

    1978-03-01

    By means of catalytic analytical methods, extremely low levels can be determined at low cost and with a high sensitivity that is equal to that of physical methods of trace analysis. The selectivity of the catalytic determinations, is, however, usually rather lower than that of other methods of trace analysis. The selectivity can sometimes be improved by modification of the indicator reaction through variation of the reagents and their concentrations, or by use of masking reagents or activators, or by combination with a separation method. Modification of the indicator reaction can be exemplified by the selective determination of osmium and ruthenium by their catalysis of the nitrate oxidation of 1-naphthylamine. By variation of the nitrate concentration and the use of 1,10-phenanthroline and 8-hydroxyquinoline as complexing agents it is possible to determine these two elements simultaneously. An especially significant increase in the selectivity is made possible by use of a preliminary separation step. If the ion to be determined is separated by solvent extraction and then catalytically determined directly in the extract, a very specific determination is possible; this technique has been called "extractive catalytic determination". This method has been used for determination of molybdenum (0.5 ng/ml) in sea-water, iron (5 ng/ml) in heavy metal salts, and copper (3 ng/ml) in the presence of numerous elements.

  10. The Signature of Selection Mediated by Expression on Human Genes

    OpenAIRE

    Urrutia, Araxi O.; Hurst, Laurence D

    2003-01-01

    As the efficacy of natural selection is expected to be a function of population size, in humans it is usually presumed that selection is a weak force and hence that gene characteristics are mostly determined by stochastic forces. In contrast, in species with large population sizes, selection is expected to be a much more effective force. Evidence for this has come from examining how genic parameters vary with expression level, which appears to determine many of a gene's features, such as codo...

  11. Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don

    Directory of Open Access Journals (Sweden)

    Zheng Xiao

    2016-10-01

    Full Text Available The quantitative real-time polymerase chain reaction (qRT-PCR approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder and BestKeeper. The results showed that EF1-α (elongation factor 1-alpha, 18S (18s ribosomal RNA and RPL3 (ribosomal protein L3 were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin (TUB was the least stable. ACT5 (actin, RPL3, 18S and EF1-α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle. Furthermore, the expression profiles of RmPSY (phytoene synthase and RmPDS (phytoene dehydrogenase were assessed using EF1-α, 18S, ACT5, and RPL3 and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle.

  12. Jetset: selecting the optimal microarray probe set to represent a gene

    DEFF Research Database (Denmark)

    Li, Qiyuan; Birkbak, Nicolai Juul; Gyorffy, Balazs

    2011-01-01

    Background: Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining...... an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task. Results: We developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe...... set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes...

  13. Selection for the α-Thalassemia Genes

    OpenAIRE

    Yokoyama, Shozo

    1983-01-01

    Extremely high incidences of single and double deletions of α-globin genes are known among Asian populations. To study possible mechanisms for the maintenance of such deletions, mathematical analyses have been conducted. It has been shown that a stable polymorphism can be achieved easily through heterozygote advantage using deterministic models. The results strongly suggest that high incidences of single and double deletion of α-globin genes among Asian populations are maintained by some type...

  14. Selecting the drainage method for agricultural land

    NARCIS (Netherlands)

    Bos, M.G.

    2001-01-01

    To facilitate crop growth excess water should be drained from the rooting zone to allow root development of the crop and from the soil surface to facilitate access to the field. Basically, there are three drainage methods from which the designer can select being; surface drains, pumped tube wells an

  15. A review of methods supporting supplier selection

    NARCIS (Netherlands)

    Boer, de Luitzen; Labro, Eva; Morlacchi, Pierangela

    2001-01-01

    this paper we present a review of decision methods reported in the literature for supporting the supplier selection process. The review is based on an extensive search in the academic literature. We position the contributions in a framework that takes the diversity of procurement situations in terms

  16. Improving accuracy for cancer classification with a new algorithm for genes selection

    Directory of Open Access Journals (Sweden)

    Zhang Hongyan

    2012-11-01

    Full Text Available Abstract Background Even though the classification of cancer tissue samples based on gene expression data has advanced considerably in recent years, it faces great challenges to improve accuracy. One of the challenges is to establish an effective method that can select a parsimonious set of relevant genes. So far, most methods for gene selection in literature focus on screening individual or pairs of genes without considering the possible interactions among genes. Here we introduce a new computational method named the Binary Matrix Shuffling Filter (BMSF. It not only overcomes the difficulty associated with the search schemes of traditional wrapper methods and overfitting problem in large dimensional search space but also takes potential gene interactions into account during gene selection. This method, coupled with Support Vector Machine (SVM for implementation, often selects very small number of genes for easy model interpretability. Results We applied our method to 9 two-class gene expression datasets involving human cancers. During the gene selection process, the set of genes to be kept in the model was recursively refined and repeatedly updated according to the effect of a given gene on the contributions of other genes in reference to their usefulness in cancer classification. The small number of informative genes selected from each dataset leads to significantly improved leave-one-out (LOOCV classification accuracy across all 9 datasets for multiple classifiers. Our method also exhibits broad generalization in the genes selected since multiple commonly used classifiers achieved either equivalent or much higher LOOCV accuracy than those reported in literature. Conclusions Evaluation of a gene’s contribution to binary cancer classification is better to be considered after adjusting for the joint effect of a large number of other genes. A computationally efficient search scheme was provided to perform effective search in the extensive

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    differentially expressed between selected and control flies when measured at the same chronological age. The longevity-selected flies consistently showed expression profiles more similar to control flies one age class younger than control flies of the same age. This finding is in accordance with a younger gene...... the physiological age as the level of cumulative mortality. Eighty-four genes were differentially expressed between the control and longevity-selected lines at the same physiological age, and the overlap between the same chronological and physiological age gene lists included 40 candidate genes for increased...... longevity. Among these candidates were genes with roles in starvation resistance, immune response regulation, and several that have not yet been linked to longevity. Investigating these genes would provide new knowledge of the pathways that affect life span in invertebrates and, potentially, mammals....

  18. Optimization methods for activities selection problems

    Science.gov (United States)

    Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

    2017-08-01

    Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

  19. When natural selection gives gene function the cold shoulder.

    Science.gov (United States)

    Cutter, Asher D; Jovelin, Richard

    2015-11-01

    It is tempting to invoke organismal selection as perpetually optimizing the function of any given gene. However, natural selection can drive genic functional change without improvement of biochemical activity, even to the extinction of gene activity. Detrimental mutations can creep in owing to linkage with other selectively favored loci. Selection can promote functional degradation, irrespective of genetic drift, when adaptation occurs by loss of gene function. Even stabilizing selection on a trait can lead to divergence of the underlying molecular constituents. Selfish genetic elements can also proliferate independent of any functional benefits to the host genome. Here we review the logic and evidence for these diverse processes acting in genome evolution. This collection of distinct evolutionary phenomena - while operating through easily understandable mechanisms - all contribute to the seemingly counterintuitive notion that maintenance or improvement of a gene's biochemical function sometimes do not determine its evolutionary fate.

  20. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Science.gov (United States)

    2010-01-01

    Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

  1. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

    Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

  2. Hybrid Binary Imperialist Competition Algorithm and Tabu Search Approach for Feature Selection Using Gene Expression Data

    Science.gov (United States)

    Aorigele; Zeng, Weiming; Hong, Xiaomin

    2016-01-01

    Gene expression data composed of thousands of genes play an important role in classification platforms and disease diagnosis. Hence, it is vital to select a small subset of salient features over a large number of gene expression data. Lately, many researchers devote themselves to feature selection using diverse computational intelligence methods. However, in the progress of selecting informative genes, many computational methods face difficulties in selecting small subsets for cancer classification due to the huge number of genes (high dimension) compared to the small number of samples, noisy genes, and irrelevant genes. In this paper, we propose a new hybrid algorithm HICATS incorporating imperialist competition algorithm (ICA) which performs global search and tabu search (TS) that conducts fine-tuned search. In order to verify the performance of the proposed algorithm HICATS, we have tested it on 10 well-known benchmark gene expression classification datasets with dimensions varying from 2308 to 12600. The performance of our proposed method proved to be superior to other related works including the conventional version of binary optimization algorithm in terms of classification accuracy and the number of selected genes. PMID:27579323

  3. Root selection methods in flood analysis

    Directory of Open Access Journals (Sweden)

    B. Parmentier

    2003-01-01

    Full Text Available In the 1970s, de Laine developed a root-matching procedure for estimating unit hydrograph ordinates from estimates of the fast component of the total runoff from multiple storms. Later, Turner produced a root selection method which required only data from one storm event and was based on recognising a pattern typical of unit hydrograph roots. Both methods required direct runoff data, i.e. prior separation of the slow response. This paper introduces a further refinement, called root separation, which allows the estimation of both the unit hydrograph ordinates and the effective precipitation from the full discharge hydrograph. It is based on recognising and separating the quicker component of the response from the much slower components due to interflow and/or baseflow. The method analyses the z-transform roots of carefully selected segments of the full hydrograph. The root patterns of these separate segments tend to be dominated by either the fast response or the slow response. This paper shows how their respective time-scales can be distinguished with an accuracy sufficient for practical purposes. As an illustration, theoretical equations are derived for a conceptual rainfall-runoff system with the input split between fast and slow reservoirs in parallel. These are solved analytically to identify the reservoir constants and the input splitting parameter. The proposed method, called 'root separation', avoids the subjective selection of rainfall roots in the Turner method as well as the subjective matching of roots in the original de Laine method. Keywords: unit hydrograph,identification methods, z-transform, polynomial roots, root separation, fast andslow response, Nash cascade

  4. Classification of microarrays; synergistic effects between normalization, gene selection and machine learning

    Science.gov (United States)

    2011-01-01

    Background Machine learning is a powerful approach for describing and predicting classes in microarray data. Although several comparative studies have investigated the relative performance of various machine learning methods, these often do not account for the fact that performance (e.g. error rate) is a result of a series of analysis steps of which the most important are data normalization, gene selection and machine learning. Results In this study, we used seven previously published cancer-related microarray data sets to compare the effects on classification performance of five normalization methods, three gene selection methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly employing a double cross validation approach. Since performance varies greatly between data sets, we devised an analysis method that first compares methods within individual data sets and then visualizes the comparisons across data sets. We discovered both well performing individual methods and synergies between different methods. Conclusion Support Vector Machines with a radial basis kernel, linear kernel or polynomial kernel of degree 2 all performed consistently well across data sets. We show that there is a synergistic relationship between these methods and gene selection based on the T-test and the selection of a relatively high number of genes. Also, we find that these methods benefit significantly from using normalized data, although it is hard to draw general conclusions about the relative performance of different normalization procedures. PMID:21982277

  5. Supplier Selection Using Weighted Utility Additive Method

    Science.gov (United States)

    Karande, Prasad; Chakraborty, Shankar

    2015-10-01

    Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove

  6. κMicroarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

    Directory of Open Access Journals (Sweden)

    Urbanski Henryk F

    2010-06-01

    Full Text Available Abstract Background Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods. We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA on the Affymetrix® GeneChip® rhesus Macaque Genome Array. Having shown that qRT-PCR and Affymetrix® GeneChip® data from the same hormone replacement therapy (HRT study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study. Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages. Results Sequences co-annotated for ribosomal protein S27a (RPS27A, and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip®. In

  7. Selective spectroscopic methods for water analysis

    Energy Technology Data Exchange (ETDEWEB)

    Vaidya, Bikas [Iowa State Univ., Ames, IA (United States)

    1997-06-24

    This dissertation explores in large part the development of a few types of spectroscopic methods in the analysis of water. Methods for the determination of some of the most important properties of water like pH, metal ion content, and chemical oxygen demand are investigated in detail. This report contains a general introduction to the subject and the conclusions. Four chapters and an appendix have been processed separately. They are: chromogenic and fluorogenic crown ether compounds for the selective extraction and determination of Hg(II); selective determination of cadmium in water using a chromogenic crown ether in a mixed micellar solution; reduction of chloride interference in chemical oxygen demand determination without using mercury salts; structural orientation patterns for a series of anthraquinone sulfonates adsorbed at an aminophenol thiolate monolayer chemisorbed at gold; and the role of chemically modified surfaces in the construction of miniaturized analytical instrumentation.

  8. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy (Davis, CA); Bachkirova, Elena (Davis, CA); Rey, Michael (Davis, CA)

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  9. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  10. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  11. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  12. Possible diversifying selection in the imprinted gene, MEDEA, in Arabidopsis.

    Science.gov (United States)

    Miyake, Takashi; Takebayashi, Naoki; Wolf, Diana E

    2009-04-01

    Coevolutionary conflict among imprinted genes that influence traits such as offspring growth may arise when maternal and paternal genomes have different evolutionary optima. This conflict is expected in outcrossing taxa with multiple paternity, but not self-fertilizing taxa. MEDEA (MEA) is an imprinted plant gene that influences seed growth. Disagreement exists regarding the type of selection acting on this gene. We present new data and analyses of sequence diversity of MEA in self-fertilizing and outcrossing Arabidopsis and its relatives, to help clarify the form of selection acting on this gene. Codon-based branch analysis among taxa (PAML) suggests that selection on the coding region is changing over time, and nonsynonymous substitution is elevated in at least one outcrossing branch. Codon-based analysis of diversity within outcrossing Arabidopsis lyrata ssp. petraea (OmegaMap) suggests that diversifying selection is acting on a portion of the gene, to cause elevated nonsynonymous polymorphism. Providing further support for balancing selection in A. lyrata, Hudson, Kreitman and Aguadé analysis indicates that diversity/divergence at silent sites in the MEA promoter and genic region is elevated relative to reference genes, and there are deviations from the neutral frequency spectrum. This combination of positive selection as well as balancing and diversifying selection in outcrossing lineages is consistent with other genes influence by evolutionary conflict, such as disease resistance genes. Consistent with predictions that conflict would be eliminated in self-fertilizing taxa, we found no evidence of positive, balancing, or diversifying selection in A. thaliana promoter or genic region.

  13. Translational selection in human: More pronounced in housekeeping genes

    KAUST Repository

    Ma, Lina

    2014-07-10

    Background: Translational selection is a ubiquitous and significant mechanism to regulate protein expression in prokaryotes and unicellular eukaryotes. Recent evidence has shown that translational selection is weakly operative in highly expressed genes in human and other vertebrates. However, it remains unclear whether translational selection acts differentially on human genes depending on their expression patterns.Results: Here we report that human housekeeping (HK) genes that are strictly defined as genes that are expressed ubiquitously and consistently in most or all tissues, are under stronger translational selection.Conclusions: These observations clearly show that translational selection is also closely associated with expression pattern. Our results suggest that human HK genes are more efficiently and/or accurately translated into proteins, which will inevitably open up a new understanding of HK genes and the regulation of gene expression.Reviewers: This article was reviewed by Yuan Yuan, Baylor College of Medicine; Han Liang, University of Texas MD Anderson Cancer Center (nominated by Dr Laura Landweber) Eugene Koonin, NCBI, NLM, NIH, United States of America Sandor Pongor, International Centre for Genetic Engineering and biotechnology (ICGEB), Italy. © 2014 Ma et al.; licensee BioMed Central Ltd.

  14. HMM-Based Gene Annotation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Haussler, David; Hughey, Richard; Karplus, Keven

    1999-09-20

    Development of new statistical methods and computational tools to identify genes in human genomic DNA, and to provide clues to their functions by identifying features such as transcription factor binding sites, tissue, specific expression and splicing patterns, and remove homologies at the protein level with genes of known function.

  15. A simple method of selective bronchography

    Energy Technology Data Exchange (ETDEWEB)

    Han, Man Chung; Ha, Sung Whan [College of Medicine, Seoul National University, Seoul (Korea, Republic of)

    1980-12-15

    The value of bronchography in the diagnosis of pulmonary diseases, especially of bronchial diseases, is well known and bronchography is an essential procedure for evaluation of bronchial diseases. And, by visualization of a selected bronchial tree, lobar or segmental, we can obtain roentgenograms of superior quality and of higher diagnostic accuracy. In addition, the procedure can be carried out safely in patients with low respiratory reserve and samples for pathology and bacteriology can be obtained. And there is another therapeutic possibility of introducing drugs intrabronchially through the catheter. Authors introduce a simple new technique of selective bronchography which is a combination of transglottic intubation and Seldinger method. The technique is summarized as follows, 1. Anesthetize oral cavity, pharynx and larynx with 2% lidocaine. 2. Under fluoroscopic control, Nelaton catheter is introduced over a wire mandarin, as authors previously reported. 3. After removal of wire mandarin, angiographic guide wire is inserted through the catheter into the trachea. 4. Then, the Nelaton catheter is withdrawn and is changed with preshaped angiographic catheter, just as in introduction of catheter in arteriography. We carried out 18 cases of selective bronchography with this technique and selection of lobar, segmental and subsegmental bronchi was carried out without difficulty.

  16. Selection of suitable reference genes for gene expression studies in Staphylococcus capitis during growth under erythromycin stress.

    Science.gov (United States)

    Cui, Bintao; Smooker, Peter M; Rouch, Duncan A; Deighton, Margaret A

    2016-08-01

    Accurate and reproducible measurement of gene transcription requires appropriate reference genes, which are stably expressed under different experimental conditions to provide normalization. Staphylococcus capitis is a human pathogen that produces biofilm under stress, such as imposed by antimicrobial agents. In this study, a set of five commonly used staphylococcal reference genes (gyrB, sodA, recA, tuf and rpoB) were systematically evaluated in two clinical isolates of Staphylococcus capitis (S. capitis subspecies urealyticus and capitis, respectively) under erythromycin stress in mid-log and stationary phases. Two public software programs (geNorm and NormFinder) and two manual calculation methods, reference residue normalization (RRN) and relative quantitative (RQ), were applied. The potential reference genes selected by the four algorithms were further validated by comparing the expression of a well-studied biofilm gene (icaA) with phenotypic biofilm formation in S. capitis under four different experimental conditions. The four methods differed considerably in their ability to predict the most suitable reference gene or gene combination for comparing icaA expression under different conditions. Under the conditions used here, the RQ method provided better selection of reference genes than the other three algorithms; however, this finding needs to be confirmed with a larger number of isolates. This study reinforces the need to assess the stability of reference genes for analysis of target gene expression under different conditions and the use of more than one algorithm in such studies. Although this work was conducted using a specific human pathogen, it emphasizes the importance of selecting suitable reference genes for accurate normalization of gene expression more generally.

  17. Modification of Cre Gene by PCR Method

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Cre/LoxP site-specified recombination system is mainly used for excision,inversion and integration of target gene.Therefore,this system can be used for plant marker free genetic transformation,site-specific transgene expression and so on.However,the application of this system was limited due to its low expression and excision efficiency.In this study,an intron,which can enhance gene expression in plants,was inserted into Cre by using PCR method.And a modified Cre gene,named Crein,was obtained.This gene was ...

  18. Multiobjective binary biogeography based optimization for feature selection using gene expression data.

    Science.gov (United States)

    Li, Xiangtao; Yin, Minghao

    2013-12-01

    Gene expression data play an important role in the development of efficient cancer diagnoses and classification. However, gene expression data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a multi-objective biogeography based optimization method is proposed to select the small subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the Fisher-Markov selector is used to choose the 60 top gene expression data. Secondly, to make biogeography based optimization suitable for the discrete problem, binary biogeography based optimization, as called BBBO, is proposed based on a binary migration model and a binary mutation model. Then, multi-objective binary biogeography based optimization, as we called MOBBBO, is proposed by integrating the non-dominated sorting method and the crowding distance method into the BBBO framework. Finally, the MOBBBO method is used for gene selection, and support vector machine is used as the classifier with the leave-one-out cross-validation method (LOOCV). In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on ten gene expression dataset benchmarks. Experimental results demonstrate that the proposed method is better or at least comparable with previous particle swarm optimization (PSO) algorithm and support vector machine (SVM) from literature when considering the quality of the solutions obtained.

  19. Selection of reference genes for gene expression studies in pig tissues using SYBR green qPCR

    DEFF Research Database (Denmark)

    Hillig, Ann-Britt Nygaard; Jørgensen, Claus Bøttcher; Cirera, Susanna

    2007-01-01

    Background: Real-time quantitative PCR (qPCR) is a method for rapid and reliable quantification of mRNA transcription. Internal standards such as reference genes are used to normalise mRNA levels between different samples for an exact comparison of mRNA transcription level. Selection of high...... quality reference genes is of crucial importance for the interpretation of data generated by real-time qPCR. Results: In this study nine commonly used reference genes were investigated in 17 different pig tissues using real-time qPCR with SYBR green. The genes included beta-actin (ACTB), beta-2...

  20. A Gene Selection Approach based on Clustering for Classification Tasks in Colon Cancer

    Directory of Open Access Journals (Sweden)

    José Antonio CASTELLANOS GARZÓN

    2016-06-01

    Full Text Available Gene selection (GS is an important research area in the analysis of DNA-microarray data, since it involves gene discovery meaningful for a particular target annotation or able to discriminate expression profiles of samples coming from different populations. In this context, a wide number of filter methods have been proposed in the literature to identify subsets of relevant genes in accordance with prefixed targets. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem (GS remains a challenge. Hence, this paper proposes a novel approach for gene selection by using cluster techniques and filter methods on the found groupings to achieve informative gene subsets. As a result of applying our methodology to Colon cancer data, we have identified the best informative gene subset between several one subsets. According to the above, the reached results have proven the reliability of the approach given in this paper.

  1. Ranking, selecting, and prioritising genes with desirability functions

    Directory of Open Access Journals (Sweden)

    Stanley E. Lazic

    2015-11-01

    Full Text Available In functional genomics experiments, researchers often select genes to follow-up or validate from a long list of differentially expressed genes. Typically, sharp thresholds are used to bin genes into groups such as significant/non-significant or fold change above/below a cut-off value, and ad hoc criteria are also used such as favouring well-known genes. Binning, however, is inefficient and does not take the uncertainty of the measurements into account. Furthermore, p-values, fold-changes, and other outcomes are treated as equally important, and relevant genes may be overlooked with such an approach. Desirability functions are proposed as a way to integrate multiple selection criteria for ranking, selecting, and prioritising genes. These functions map any variable to a continuous 0–1 scale, where one is maximally desirable and zero is unacceptable. Multiple selection criteria are then combined to provide an overall desirability that is used to rank genes. In addition to p-values and fold-changes, further experimental results and information contained in databases can be easily included as criteria. The approach is demonstrated with a breast cancer microarray data set. The functions and an example data set can be found in the desiR package on CRAN (https://cran.r-project.org/web/packages/desiR/ and the development version is available on GitHub (https://github.com/stanlazic/desiR.

  2. Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Directory of Open Access Journals (Sweden)

    Serafini Maria

    2003-11-01

    Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  3. Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification.

    Science.gov (United States)

    Huang, Lingkang; Zhang, Hao Helen; Zeng, Zhao-Bang; Bushel, Pierre R

    2013-01-01

    Microarray techniques provide promising tools for cancer diagnosis using gene expression profiles. However, molecular diagnosis based on high-throughput platforms presents great challenges due to the overwhelming number of variables versus the small sample size and the complex nature of multi-type tumors. Support vector machines (SVMs) have shown superior performance in cancer classification due to their ability to handle high dimensional low sample size data. The multi-class SVM algorithm of Crammer and Singer provides a natural framework for multi-class learning. Despite its effective performance, the procedure utilizes all variables without selection. In this paper, we propose to improve the procedure by imposing shrinkage penalties in learning to enforce solution sparsity. The original multi-class SVM of Crammer and Singer is effective for multi-class classification but does not conduct variable selection. We improved the method by introducing soft-thresholding type penalties to incorporate variable selection into multi-class classification for high dimensional data. The new methods were applied to simulated data and two cancer gene expression data sets. The results demonstrate that the new methods can select a small number of genes for building accurate multi-class classification rules. Furthermore, the important genes selected by the methods overlap significantly, suggesting general agreement among different variable selection schemes. High accuracy and sparsity make the new methods attractive for cancer diagnostics with gene expression data and defining targets of therapeutic intervention. The source MATLAB code are available from http://math.arizona.edu/~hzhang/software.html.

  4. Selective gene expression in focal cerebral ischemia.

    Science.gov (United States)

    Jacewicz, M; Kiessling, M; Pulsinelli, W A

    1986-06-01

    Regional patterns of protein synthesis were examined in rat cortex made ischemic by the occlusion of the right common carotid and middle cerebral arteries. At 2 h of ischemia, proteins were pulse labeled with intracortical injections of a mixture of [3H]leucine, [3H]isoleucine, and [3H]proline. Newly synthesized proteins were analyzed by two-dimensional gel fluorography, and the results correlated with local CBF, measured with [14C]iodoantipyrine as tracer. Small blood flow reductions (CBF = 50-80 ml 100 g-1 min-1) were accompanied by a modest inhibition in synthesis of many proteins and a marked increase in one protein (Mr 27,000). With further reduction in blood flow (CBF = 40 ml 100 g-1 min-1), synthesis became limited to a small group of proteins (Mr 27,000, 34,000, 73,000, 79,000, and actin) including two new polypeptides (Mr 55,000 and 70,000). Severe ischemia (CBF = 15-25 ml 100 g-1 min-1) caused the isoelectric modification of several proteins (Mr 44,000, 55,000, and 70,000) and induced synthesis of another protein (Mr 40,000). Two polypeptides (Mr 27,000 and 70,000) dominated residual protein synthesis in severe ischemia. The changes in protein synthesis induced by different grades of ischemia most likely comprise a variation of the so-called "heat shock" or "stress" response found in all eukaryotic cells subjected to adverse conditions. Since heat shock genes are known to confer partial protection against anoxia and a variety of other noxious insults, their induction may be a factor in limiting the extent of ischemic tissue damage.

  5. Positive-negative-selection-mediated gene targeting in rice

    Directory of Open Access Journals (Sweden)

    Zenpei eShimatani

    2015-01-01

    Full Text Available Gene targeting (GT refers to the designed modification of genomic sequence(s through homologous recombination (HR. GT is a powerful tool both for the study of gene function and for molecular breeding. However, in transformation of higher plants, non-homologous end joining (NHEJ occurs overwhelmingly in somatic cells, masking HR-mediated GT. Positive-negative selection (PNS is an approach for finding HR-mediated GT events because it can eliminate NHEJ effectively by expression of a negative-selection marker gene. In rice—a major crop worldwide—reproducible PNS-mediated GT of endogenous genes has now been successfully achieved. The procedure is based on strong PNS using diphtheria toxin A-fragment as a negative marker, and has succeeded in the directed modification of several endogenous rice genes in various ways. In addition to gene knock-outs and knock-ins, a nucleotide substitution in a target gene was also achieved recently. This review presents a summary of the development of the rice PNS system, highlighting its advantages. Different types of gene modification and gene editing aimed at developing new plant breeding technology (NPBT based on PNS are discussed.

  6. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  7. Gene Selection Integrated with Biological Knowledge for Plant Stress Response Using Neighborhood System and Rough Set Theory.

    Science.gov (United States)

    Meng, Jun; Zhang, Jing; Luan, Yushi

    2015-01-01

    Mining knowledge from gene expression data is a hot research topic and direction of bioinformatics. Gene selection and sample classification are significant research trends, due to the large amount of genes and small size of samples in gene expression data. Rough set theory has been successfully applied to gene selection, as it can select attributes without redundancy. To improve the interpretability of the selected genes, some researchers introduced biological knowledge. In this paper, we first employ neighborhood system to deal directly with the new information table formed by integrating gene expression data with biological knowledge, which can simultaneously present the information in multiple perspectives and do not weaken the information of individual gene for selection and classification. Then, we give a novel framework for gene selection and propose a significant gene selection method based on this framework by employing reduction algorithm in rough set theory. The proposed method is applied to the analysis of plant stress response. Experimental results on three data sets show that the proposed method is effective, as it can select significant gene subsets without redundancy and achieve high classification accuracy. Biological analysis for the results shows that the interpretability is well.

  8. Natural selection on genes that underlie human disease susceptibility

    Science.gov (United States)

    Blekhman, Ran; Man, Orna; Herrmann, Leslie; Boyko, Adam R.; Indap, Amit; Kosiol, Carolin; Bustamante, Carlos D.; Teshima, Kosuke M.; Przeworski, Molly

    2008-01-01

    What evolutionary forces shape genes that contribute to the risk of human disease? Do similar selective pressures act on alleles that underlie simple vs. complex disorders? [1-3]. Answers to these questions will shed light on the origin of human disorders (e.g., [4]), and help to predict the population frequencies of alleles that contribute to disease risk, with important implications for the efficient design of mapping studies [5-7]. As a first step towards addressing them, we created a hand-curated version of the Mendelian Inheritance in Man database (OMIM). We then examined selective pressures on Mendelian disease genes, genes that contribute to complex disease risk and genes known to be essential in mouse, by analyzing patterns of human polymorphism and of divergence between human and rhesus macaque. We find that Mendelian disease genes appear to be under widespread purifying selection, especially when the disease mutations are dominant (rather than recessive). In contrast, the class of genes that influence complex disease risk shows little signs of evolutionary conservation, possibly because this category includes both targets of purifying and positive selection. PMID:18571414

  9. Sequence validation of candidates for selectively important genes in sunflower.

    Directory of Open Access Journals (Sweden)

    Mark A Chapman

    Full Text Available Analyses aimed at identifying genes that have been targeted by past selection provide a powerful means for investigating the molecular basis of adaptive differentiation. In the case of crop plants, such studies have the potential to not only shed light on important evolutionary processes, but also to identify genes of agronomic interest. In this study, we test for evidence of positive selection at the DNA sequence level in a set of candidate genes previously identified in a genome-wide scan for genotypic evidence of selection during the evolution of cultivated sunflower. In the majority of cases, we were able to confirm the effects of selection in shaping diversity at these loci. Notably, the genes that were found to be under selection via our sequence-based analyses were devoid of variation in the cultivated sunflower gene pool. This result confirms a possible strategy for streamlining the search for adaptively-important loci process by pre-screening the derived population to identify the strongest candidates before sequencing them in the ancestral population.

  10. Sex-related genes, directional sexual selection, and speciation.

    Science.gov (United States)

    Civetta, A; Singh, R S

    1998-07-01

    Reproductive isolation and speciation can result from the establishment of either premating or postmating barriers that restrict gene flow between populations. Recent studies of speciation have been dominated by a molecular approach to dissect the genetic basis of hybrid male sterility, a specific form of postmating reproductive isolation. However, relatively little attention has been paid to the evolution of genes involved in premating isolation and genes generally involved in other sex-related functions (e.g., mating behavior, fertilization, spermatogenesis, sex determination). We have assembled DNA sequences from 51 nuclear genes and classified them based on their functional characteristics. The proportion of nonsynonymous to synonymous nucleotide substitutions were compared between Drosophila melanogaster, Drosophila simulans, and Drosophila pseudoobscura, as well as between Caenorhabditis elegans and Caenorhabditis briggsae. We found a high ratio of nonsynonymous to synonymous substitutions for sex-related genes (i.e., genes involved in mating behavior, fertilization, spermatogenesis, or sex determination). The results suggest that directional sexual selection has shaped the evolution of sex-related genes and that these changes have more likely occurred during the early stages of speciation. It is possible that directional selection becomes relaxed after reproductive isolation has been completed between more distantly related species (e.g., D. melanogaster and D. pseudoobscura). However, a saturation in the number of nucleotide substitutions since the time of species separation may mask any sign of directional selection between more distantly related species.

  11. Combinatorial pooling enables selective sequencing of the barley gene space.

    Directory of Open Access Journals (Sweden)

    Stefano Lonardi

    2013-04-01

    Full Text Available For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

  12. Recursive Cluster Elimination (RCE for classification and feature selection from gene expression data

    Directory of Open Access Journals (Sweden)

    Showe Louise C

    2007-05-01

    Full Text Available Abstract Background Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE rather than recursive feature elimination (RFE. We have tested this algorithm on six datasets and compared its performance with that of two related classification procedures with RFE. Results We have developed a novel method for selecting significant genes in comparative gene expression studies. This method, which we refer to as SVM-RCE, combines K-means, a clustering method, to identify correlated gene clusters, and Support Vector Machines (SVMs, a supervised machine learning classification method, to identify and score (rank those gene clusters for the purpose of classification. K-means is used initially to group genes into clusters. Recursive cluster elimination (RCE is then applied to iteratively remove those clusters of genes that contribute the least to the classification performance. SVM-RCE identifies the clusters of correlated genes that are most significantly differentially expressed between the sample classes. Utilization of gene clusters, rather than individual genes, enhances the supervised classification accuracy of the same data as compared to the accuracy when either SVM or Penalized Discriminant Analysis (PDA with recursive feature elimination (SVM-RFE and PDA-RFE are used to remove genes based on their individual discriminant weights. Conclusion SVM-RCE provides improved classification accuracy with complex microarray data sets when it is compared to the classification accuracy of the same datasets using either SVM-RFE or PDA-RFE. SVM-RCE identifies clusters of correlated genes that when considered together

  13. Selection on meiosis genes in diploid and tetraploid Arabidopsis arenosa.

    Science.gov (United States)

    Wright, Kevin M; Arnold, Brian; Xue, Katherine; Šurinová, Maria; O'Connell, Jeremy; Bomblies, Kirsten

    2015-04-01

    Meiotic chromosome segregation is critical for fertility across eukaryotes, and core meiotic processes are well conserved even between kingdoms. Nevertheless, recent work in animals has shown that at least some meiosis genes are highly diverse or strongly differentiated among populations. What drives this remains largely unknown. We previously showed that autotetraploid Arabidopsis arenosa evolved stable meiosis, likely through reduced crossover rates, and that associated with this there is strong evidence for selection in a subset of meiosis genes known to affect axis formation, synapsis, and crossover frequency. Here, we use genome-wide data to study the molecular evolution of 70 meiosis genes in a much wider sample of A. arenosa. We sample the polyploid lineage, a diploid lineage from the Carpathian Mountains, and a more distantly related diploid lineage from the adjacent, but biogeographically distinct Pannonian Basin. We find that not only did selection act on meiosis genes in the polyploid lineage but also independently on a smaller subset of meiosis genes in Pannonian diploids. Functionally related genes are targeted by selection in these distinct contexts, and in two cases, independent sweeps occurred in the same loci. The tetraploid lineage has sustained selection on more genes, has more amino acid changes in each, and these more often affect conserved or potentially functional sites. We hypothesize that Pannonian diploid and tetraploid A. arenosa experienced selection on structural proteins that mediate sister chromatid cohesion, the formation of meiotic chromosome axes, and synapsis, likely for different underlying reasons. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. A feature selection approach for identification of signature genes from SAGE data

    Directory of Open Access Journals (Sweden)

    Silva Paulo JS

    2007-05-01

    Full Text Available Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS or the recent Sequencing-By-Synthesis (SBS technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

  15. Positive selection and functional divergence of farnesyl pyrophosphate synthase genes in plants.

    Science.gov (United States)

    Qian, Jieying; Liu, Yong; Chao, Naixia; Ma, Chengtong; Chen, Qicong; Sun, Jian; Wu, Yaosheng

    2017-02-04

    Farnesyl pyrophosphate synthase (FPS) belongs to the short-chain prenyltransferase family, and it performs a conserved and essential role in the terpenoid biosynthesis pathway. However, its classification, evolutionary history, and the forces driving the evolution of FPS genes in plants remain poorly understood. Phylogeny and positive selection analysis was used to identify the evolutionary forces that led to the functional divergence of FPS in plants, and recombinant detection was undertaken using the Genetic Algorithm for Recombination Detection (GARD) method. The dataset included 68 FPS variation pattern sequences (2 gymnosperms, 10 monocotyledons, 54 dicotyledons, and 2 outgroups). This study revealed that the FPS gene was under positive selection in plants. No recombinant within the FPS gene was found. Therefore, it was inferred that the positive selection of FPS had not been influenced by a recombinant episode. The positively selected sites were mainly located in the catalytic center and functional areas, which indicated that the 98S and 234D were important positively selected sites for plant FPS in the terpenoid biosynthesis pathway. They were located in the FPS conserved domain of the catalytic site. We inferred that the diversification of FPS genes was associated with functional divergence and could be driven by positive selection. It was clear that protein sequence evolution via positive selection was able to drive adaptive diversification in plant FPS proteins. This study provides information on the classification and positive selection of plant FPS genes, and the results could be useful for further research on the regulation of triterpenoid biosynthesis.

  16. Evaluation of gene importance in microarray data based upon probability of selection

    Directory of Open Access Journals (Sweden)

    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

  17. TSG: a new algorithm for binary and multi-class cancer classification and informative genes selection

    Directory of Open Access Journals (Sweden)

    Wang Haiyan

    2013-01-01

    Full Text Available Abstract Background One of the challenges in classification of cancer tissue samples based on gene expression data is to establish an effective method that can select a parsimonious set of informative genes. The Top Scoring Pair (TSP, k-Top Scoring Pairs (k-TSP, Support Vector Machines (SVM, and prediction analysis of microarrays (PAM are four popular classifiers that have comparable performance on multiple cancer datasets. SVM and PAM tend to use a large number of genes and TSP, k-TSP always use even number of genes. In addition, the selection of distinct gene pairs in k-TSP simply combined the pairs of top ranking genes without considering the fact that the gene set with best discrimination power may not be the combined pairs. The k-TSP algorithm also needs the user to specify an upper bound for the number of gene pairs. Here we introduce a computational algorithm to address the problems. The algorithm is named Chisquare-statistic-based Top Scoring Genes (Chi-TSG classifier simplified as TSG. Results The TSG classifier starts with the top two genes and sequentially adds additional gene into the candidate gene set to perform informative gene selection. The algorithm automatically reports the total number of informative genes selected with cross validation. We provide the algorithm for both binary and multi-class cancer classification. The algorithm was applied to 9 binary and 10 multi-class gene expression datasets involving human cancers. The TSG classifier outperforms TSP family classifiers by a big margin in most of the 19 datasets. In addition to improved accuracy, our classifier shares all the advantages of the TSP family classifiers including easy interpretation, invariant to monotone transformation, often selects a small number of informative genes allowing follow-up studies, resistant to sampling variations due to within sample operations. Conclusions Redefining the scores for gene set and the classification rules in TSP family

  18. Location of airports - selected quantitative methods

    Directory of Open Access Journals (Sweden)

    Agnieszka Merkisz-Guranowska

    2016-09-01

    Full Text Available Background: The role of air transport in  the economic development of a country and its regions cannot be overestimated. The decision concerning an airport's location must be in line with the expectations of all the stakeholders involved. This article deals with the issues related to the choice of  sites where airports should be located. Methods: Two main quantitative approaches related to the issue of airport location are presented in this article, i.e. the question of optimizing such a choice and the issue of selecting the location from a predefined set. The former involves mathematical programming and formulating the problem as an optimization task, the latter, however, involves ranking the possible variations. Due to various methodological backgrounds, the authors present the advantages and disadvantages of both approaches and point to the one which currently has its own practical application. Results: Based on real-life examples, the authors present a multi-stage procedure, which renders it possible to solve the problem of airport location. Conclusions: Based on the overview of literature of the subject, the authors point to three types of approach to the issue of airport location which could enable further development of currently applied methods.

  19. Comparative study of selected parallel tempering methods

    Science.gov (United States)

    Malakis, A.; Papakonstantinou, T.

    2013-07-01

    We review several parallel tempering schemes and examine their main ingredients for accuracy and efficiency. The present study covers two selection methods of temperatures and several choices for the exchange of replicas, including a recent novel all-pair exchange method. We compare the resulting schemes and measure specific heat errors and efficiency using the two-dimensional (2D) Ising model. Our tests suggest that an earlier proposal for using numbers of local moves related to the canonical correlation times is one of the key ingredients for increasing efficiency, and protocols using cluster algorithms are found to be very effective. Some of the protocols are also tested for efficiency and ground state production in 3D spin-glass models where we find that a simple nearest-neighbor approach using a local n-fold-way algorithm is the most effective. Finally, we present evidence that the asymptotic limits of the ground state energy for the isotropic case and for an anisotropic case of the 3D spin-glass model are very close and may even coincide.

  20. Construction of human antibody gene libraries and selection of antibodies by phage display.

    Science.gov (United States)

    Frenzel, André; Kügler, Jonas; Wilke, Sonja; Schirrmann, Thomas; Hust, Michael

    2014-01-01

    Antibody phage display is the most commonly used in vitro selection technology and has yielded thousands of useful antibodies for research, diagnostics, and therapy.The prerequisite for successful generation and development of human recombinant antibodies using phage display is the construction of a high-quality antibody gene library. Here, we describe the methods for the construction of human immune and naive scFv gene libraries.The success also depends on the panning strategy for the selection of binders from these libraries. In this article, we describe a panning strategy that is high-throughput compatible and allows parallel selection in microtiter plates.

  1. Plasmid selection in Escherichia coli using an endogenous essential gene marker

    Directory of Open Access Journals (Sweden)

    Good Liam

    2008-08-01

    Full Text Available Abstract Background Antibiotic resistance genes are widely used for selection of recombinant bacteria, but their use risks contributing to the spread of antibiotic resistance. In particular, the practice is inappropriate for some intrinsically resistant bacteria and in vaccine production, and costly for industrial scale production. Non-antibiotic systems are available, but require mutant host strains, defined media or expensive reagents. An unexplored concept is over-expression of a host essential gene to enable selection in the presence of a chemical inhibitor of the gene product. To test this idea in E. coli, we used the growth essential target gene fabI as the plasmid-borne marker and the biocide triclosan as the selective agent. Results The new cloning vector, pFab, enabled selection by triclosan at 1 μM. Interestingly, pFab out-performed the parent pUC19-ampicillin system in cell growth, plasmid stability and plasmid yield. Also, pFab was toxic to host cells in a way that was reversed by triclosan. Therefore, pFab and triclosan are toxic when used alone but in combination they enhance growth and plasmid production through a gene-inhibitor interaction. Conclusion The fabI-triclosan model system provides an alternative plasmid selection method based on essential gene over-expression, without the use of antibiotic-resistance genes and conventional antibiotics.

  2. Imprints of natural selection along environmental gradients in phenology-related genes of Quercus petraea.

    Science.gov (United States)

    Alberto, Florian J; Derory, Jérémy; Boury, Christophe; Frigerio, Jean-Marc; Zimmermann, Niklaus E; Kremer, Antoine

    2013-10-01

    We explored single nucleotide polymorphism (SNP) variation in candidate genes for bud burst from Quercus petraea populations sampled along gradients of latitude and altitude in Western Europe. SNP diversity was monitored for 106 candidate genes, in 758 individuals from 32 natural populations. We investigated whether SNP variation reflected the clinal pattern of bud burst observed in common garden experiments. We used different methods to detect imprints of natural selection (FST outlier, clinal variation at allelic frequencies, association tests) and compared the results obtained for the two gradients. FST outlier SNPs were found in 15 genes, 5 of which were common to both gradients. The type of selection differed between the two gradients (directional or balancing) for 3 of these 5. Clinal variations were observed for six SNPs, and one cline was conserved across both gradients. Association tests between the phenotypic or breeding values of trees and SNP genotypes identified 14 significant associations, involving 12 genes. The results of outlier detection on the basis of population differentiation or clinal variation were not very consistent with the results of association tests. The discrepancies between these approaches may reflect the different hierarchical levels of selection considered (inter- and intrapopulation selection). Finally, we obtained evidence for convergent selection (similar for gradients) and clinal variation for a few genes, suggesting that comparisons between parallel gradients could be used to screen for major candidate genes responding to natural selection in trees.

  3. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression.

  4. A survey on filter techniques for feature selection in gene expression microarray analysis.

    Science.gov (United States)

    Lazar, Cosmin; Taminau, Jonatan; Meganck, Stijn; Steenhoff, David; Coletta, Alain; Molter, Colin; de Schaetzen, Virginie; Duque, Robin; Bersini, Hugues; Nowé, Ann

    2012-01-01

    A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted rule, these methods are grouped in filters, wrappers, and embedded methods. More recently, a new group of methods has been added in the general framework of FS: ensemble techniques. The focus in this survey is on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery. We present them in a unified framework, using standardized notations in order to reveal their technical details and to highlight their common characteristics as well as their particularities.

  5. SELECTION OF METHOD FOR RESTORATION OF PARTS

    Directory of Open Access Journals (Sweden)

    V. P. Ivanov

    2016-01-01

    Full Text Available The paper contains definitions for a process and a methodology for restoration of parts on the basis of the analysis of the known methods and their selection. Geometric parameters and operational properties that should be provided for restoration of parts have been determined in the paper. A process for selection of the required method for restoration parts has been improved and it makes it possible to synthesize an optimal process of the restoration according to a criterion of industrial resource consumption with due account of quality, productivity and security limits. A justification on measures that meet the required limits has been presented in the paper. The paper shows a direction of technical solutions that ensure complete use of residual life of repair fund parts. These solutions can be achieved through close application of all repair sizes of work-pieces with revision of their values, uniform removal of the allowance while cutting the work-pieces at optimum locating, application of coating processes only in technically justified cases, application of straightening with thermal fixing of its results or all-around compression of deformable elements. The paper proposes to limit a number of overhauls for the units together with restoration of basic and fundamental parts by two repairs for the whole period of their lifetime. Number of shaft journal building-up should be limited by one building-up operation throughout the whole life cycle of the part with the purpose to preserve its length within the prescribed limits. It has been recommended to expand an application area of volumetric plastic deformation of material in the form of thermoplastic distribution or reduction of repair work-pieces representing class of rotation bodies with holes that ensures an allowance to machine external and internal surfaces for nominal dimensions without coating. A structure of the coating material with fine inclusions of carbides or nitrides of metals and

  6. Minimum redundancy maximum relevance feature selection approach for temporal gene expression data.

    Science.gov (United States)

    Radovic, Milos; Ghalwash, Mohamed; Filipovic, Nenad; Obradovic, Zoran

    2017-01-03

    Feature selection, aiming to identify a subset of features among a possibly large set of features that are relevant for predicting a response, is an important preprocessing step in machine learning. In gene expression studies this is not a trivial task for several reasons, including potential temporal character of data. However, most feature selection approaches developed for microarray data cannot handle multivariate temporal data without previous data flattening, which results in loss of temporal information. We propose a temporal minimum redundancy - maximum relevance (TMRMR) feature selection approach, which is able to handle multivariate temporal data without previous data flattening. In the proposed approach we compute relevance of a gene by averaging F-statistic values calculated across individual time steps, and we compute redundancy between genes by using a dynamical time warping approach. The proposed method is evaluated on three temporal gene expression datasets from human viral challenge studies. Obtained results show that the proposed method outperforms alternatives widely used in gene expression studies. In particular, the proposed method achieved improvement in accuracy in 34 out of 54 experiments, while the other methods outperformed it in no more than 4 experiments. We developed a filter-based feature selection method for temporal gene expression data based on maximum relevance and minimum redundancy criteria. The proposed method incorporates temporal information by combining relevance, which is calculated as an average F-statistic value across different time steps, with redundancy, which is calculated by employing dynamical time warping approach. As evident in our experiments, incorporating the temporal information into the feature selection process leads to selection of more discriminative features.

  7. Computational methods for Gene Orthology inference

    Science.gov (United States)

    Kristensen, David M.; Wolf, Yuri I.; Mushegian, Arcady R.

    2011-01-01

    Accurate inference of orthologous genes is a pre-requisite for most comparative genomics studies, and is also important for functional annotation of new genomes. Identification of orthologous gene sets typically involves phylogenetic tree analysis, heuristic algorithms based on sequence conservation, synteny analysis, or some combination of these approaches. The most direct tree-based methods typically rely on the comparison of an individual gene tree with a species tree. Once the two trees are accurately constructed, orthologs are straightforwardly identified by the definition of orthology as those homologs that are related by speciation, rather than gene duplication, at their most recent point of origin. Although ideal for the purpose of orthology identification in principle, phylogenetic trees are computationally expensive to construct for large numbers of genes and genomes, and they often contain errors, especially at large evolutionary distances. Moreover, in many organisms, in particular prokaryotes and viruses, evolution does not appear to have followed a simple ‘tree-like’ mode, which makes conventional tree reconciliation inapplicable. Other, heuristic methods identify probable orthologs as the closest homologous pairs or groups of genes in a set of organisms. These approaches are faster and easier to automate than tree-based methods, with efficient implementations provided by graph-theoretical algorithms enabling comparisons of thousands of genomes. Comparisons of these two approaches show that, despite conceptual differences, they produce similar sets of orthologs, especially at short evolutionary distances. Synteny also can aid in identification of orthologs. Often, tree-based, sequence similarity- and synteny-based approaches can be combined into flexible hybrid methods. PMID:21690100

  8. Selective Gene Regulation by Androgen Receptor in Prostate Cancer

    Science.gov (United States)

    2014-07-01

    assays and in chromatin precipitation assays, and in the expression of select AR target genes associated with proliferation and differentiation. Cell...2013;3(11):1254-1271. 26. Polkinghorn WR, Parker JS, Lee MX , Kass EM, Spratt DE, Iaquinta PJ, Arora VK, Yen WF, Cai L, Zheng D, Carver BS, Chen Y

  9. A mixture model-based strategy for selecting sets of genes in multiclass response microarray experiments.

    Science.gov (United States)

    Broët, Philippe; Lewin, Alex; Richardson, Sylvia; Dalmasso, Cyril; Magdelenat, Henri

    2004-11-01

    Multiclass response (MCR) experiments are those in which there are more than two classes to be compared. In these experiments, though the null hypothesis is simple, there are typically many patterns of gene expression changes across the different classes that led to complex alternatives. In this paper, we propose a new strategy for selecting genes in MCR that is based on a flexible mixture model for the marginal distribution of a modified F-statistic. Using this model, false positive and negative discovery rates can be estimated and combined to produce a rule for selecting a subset of genes. Moreover, the method proposed allows calculation of these rates for any predefined subset of genes. We illustrate the performance our approach using simulated datasets and a real breast cancer microarray dataset. In this latter study, we investigate predefined subset of genes and point out interesting differences between three distinct biological pathways. http://www.bgx.org.uk/software.html

  10. Tag SNP selection for candidate gene association studies using HapMap and gene resequencing data.

    Science.gov (United States)

    Xu, Zongli; Kaplan, Norman L; Taylor, Jack A

    2007-10-01

    HapMap provides linkage disequilibrium (LD) information on a sample of 3.7 million SNPs that can be used for tag SNP selection in whole-genome association studies. HapMap can also be used for tag SNP selection in candidate genes, although its performance has yet to be evaluated against gene resequencing data, where there is near-complete SNP ascertainment. The Environmental Genome Project (EGP) is the largest gene resequencing effort to date with over 500 resequenced genes. We used HapMap data to select tag SNPs and calculated the proportions of common SNPs (MAF>or=0.05) tagged (rho2>or=0.8) for each of 127 EGP Panel 2 genes where individual ethnic information was available. Median gene-tagging proportions are 50, 80 and 74% for African, Asian, and European groups, respectively. These low gene-tagging proportions may be problematic for some candidate gene studies. In addition, although HapMap targeted nonsynonymous SNPs (nsSNPs), we estimate only approximately 30% of nonsynonymous SNPs in EGP are in high LD with any HapMap SNP. We show that gene-tagging proportions can be improved by adding a relatively small number of tag SNPs that were selected based on resequencing data. We also demonstrate that ethnic-mixed data can be used to improve HapMap gene-tagging proportions, but are not as efficient as ethnic-specific data. Finally, we generalized the greedy algorithm proposed by Carlson et al (2004) to select tag SNPs for multiple populations and implemented the algorithm into a freely available software package mPopTag.

  11. PL1 fusion gene: a novel visual selectable marker gene that confers tolerance to multiple abiotic stresses in transgenic tomato.

    Science.gov (United States)

    Jin, Feng; Li, Shu; Dang, Lijie; Chai, Wenting; Li, Pengli; Wang, Ning Ning

    2012-10-01

    Visual selectable markers, including the purple color caused by the accumulation of anthocyanins, have been proposed for use as antibiotic-free alternatives. However, the excessive accumulation of anthocyanins seriously inhibits the growth and development of transgenic plants. In our study, the AtDWF4 promoter from Arabidopsis and the tomato LeANT1 gene, encoding a MYB transcription factor, were used to construct the PL1 fusion gene to test whether it could be used as a visual selectable marker gene for tomato transformation. All the PL1 transgenic shoots exhibited intense purple color on shoot induction medium. In the transgenic tomato plants, PL1 was highly expressed in the cotyledons, but expressed only slightly in the true leaves and other organs. The expression of PL1 had no significantly adverse effects on the growth or development of the transgenic tomato plants, and conferred tolerance to multiple abiotic stresses in them. With the “cut off green shoots” method, multiple independent 35S::GFP transgenic tomato lines were successfully obtained using PL1 as the selectable marker gene. These results suggest that PL1 has potential application of visual selectable marker gene for tomato transformation.

  12. Comprehensive selection of reference genes for gene expression normalization in sugarcane by real time quantitative rt-PCR.

    Directory of Open Access Journals (Sweden)

    Hui Ling

    Full Text Available The increasingly used real time quantitative reverse transcription-PCR (qRT-PCR method for gene expression analysis requires one or several reference gene(s acting as normalization factor(s. In order to facilitate gene expression studies in sugarcane (Saccharum officinarum, a non-model plant with limited genome information, the stability of 13 candidate reference genes was evaluated. The geNorm, NormFinder and deltaCt methods were used for selecting stably expressed internal controls across different tissues and under various experimental treatments. These results revealed that, among these 13 candidate reference genes, GAPDH, eEF-1a and eIF-4α were the most stable and suitable for use as normalization factors across all various experimental samples. In addition, APRT could be a candidate for examining the relationship between gene copy number and transcript levels in sugarcane tissue samples. According to the results evaluated by geNorm, combining CUL and eEF-1α in hormone treatment experiments; CAC and CUL in abiotic stress tests; GAPDH, eEF-1a and CUL in all treatment samples plus CAC, CUL, APRT and TIPS-41 in cultivar tissues as groups for normalization would lead to more accurate and reliable expression quantification in sugarcane. This is the first systematic validation of reference genes for quantification of transcript expression profiles in sugarcane. This study should provide useful information for selecting reference genes for more accurate quantification of gene expression in sugarcane and other plant species.

  13. Global patterns of diversity and selection in human tyrosinase gene.

    Directory of Open Access Journals (Sweden)

    Georgi Hudjashov

    Full Text Available Global variation in skin pigmentation is one of the most striking examples of environmental adaptation in humans. More than two hundred loci have been identified as candidate genes in model organisms and a few tens of these have been found to be significantly associated with human skin pigmentation in genome-wide association studies. However, the evolutionary history of different pigmentation genes is rather complex: some loci have been subjected to strong positive selection, while others evolved under the relaxation of functional constraints in low UV environment. Here we report the results of a global study of the human tyrosinase gene, which is one of the key enzymes in melanin production, to assess the role of its variation in the evolution of skin pigmentation differences among human populations. We observe a higher rate of non-synonymous polymorphisms in the European sample consistent with the relaxation of selective constraints. A similar pattern was previously observed in the MC1R gene and concurs with UV radiation-driven model of skin color evolution by which mutations leading to lower melanin levels and decreased photoprotection are subject to purifying selection at low latitudes while being tolerated or even favored at higher latitudes because they facilitate UV-dependent vitamin D production. Our coalescent date estimates suggest that the non-synonymous variants, which are frequent in Europe and North Africa, are recent and have emerged after the separation of East and West Eurasian populations.

  14. Novel roles for selected genes in meiotic DNA processing.

    Directory of Open Access Journals (Sweden)

    Philip W Jordan

    2007-12-01

    Full Text Available High-throughput studies of the 6,200 genes of Saccharomyces cerevisiae have provided valuable data resources. However, these resources require a return to experimental analysis to test predictions. An in-silico screen, mining existing interaction, expression, localization, and phenotype datasets was developed with the aim of selecting minimally characterized genes involved in meiotic DNA processing. Based on our selection procedure, 81 deletion mutants were constructed and tested for phenotypic abnormalities. Eleven (13.6% genes were identified to have novel roles in meiotic DNA processes including DNA replication, recombination, and chromosome segregation. In particular, this analysis showed that Def1, a protein that facilitates ubiquitination of RNA polymerase II as a response to DNA damage, is required for efficient synapsis between homologues and normal levels of crossover recombination during meiosis. These characteristics are shared by a group of proteins required for Zip1 loading (ZMM proteins. Additionally, Soh1/Med31, a subunit of the RNA pol II mediator complex, Bre5, a ubiquitin protease cofactor and an uncharacterized protein, Rmr1/Ygl250w, are required for normal levels of gene conversion events during meiosis. We show how existing datasets may be used to define gene sets enriched for specific roles and how these can be evaluated by experimental analysis.

  15. HTLV-1 p30II: selective repressor of gene expression

    Directory of Open Access Journals (Sweden)

    Green Patrick L

    2004-11-01

    Full Text Available Abstract Human T-lymphotropic virus type-1 (HTLV-1 is a complex retrovirus that causes adult T-cell leukemia/lymphoma (ATL and is implicated in a variety of lymphocyte-mediated disorders. HTLV-1 pX ORF II encodes two proteins, p13II and p30II whose roles are beginning to be defined in the virus life cycle. Previous studies indicate the importance of these viral proteins in the ability of the virus to maintain viral loads and persist in an animal model of HTLV-1 infection. Intriguing new studies indicate that p30II is a multifunctional regulator that differentially modulates CREB and Tax-responsive element-mediated transcription through its interaction with CREB-binding protein (CBP/p300 and specifically binds and represses tax/rex mRNA nuclear export. A new study characterized the role of p30II in regulation of cellular gene expression using comprehensive human gene arrays. Interestingly, p30II is an overall repressor of cellular gene expression, while selectively favoring the expression of regulatory gene pathways important to T lymphocytes. These new findings suggest that HTLV-1, which is associated with lymphoproliferative diseases, uses p30II to selectively repress cellular and viral gene expression to favor the survival of cellular targets ultimately resulting in leukemogenesis.

  16. Regularized logistic regression with adjusted adaptive elastic net for gene selection in high dimensional cancer classification.

    Science.gov (United States)

    Algamal, Zakariya Yahya; Lee, Muhammad Hisyam

    2015-12-01

    Cancer classification and gene selection in high-dimensional data have been popular research topics in genetics and molecular biology. Recently, adaptive regularized logistic regression using the elastic net regularization, which is called the adaptive elastic net, has been successfully applied in high-dimensional cancer classification to tackle both estimating the gene coefficients and performing gene selection simultaneously. The adaptive elastic net originally used elastic net estimates as the initial weight, however, using this weight may not be preferable for certain reasons: First, the elastic net estimator is biased in selecting genes. Second, it does not perform well when the pairwise correlations between variables are not high. Adjusted adaptive regularized logistic regression (AAElastic) is proposed to address these issues and encourage grouping effects simultaneously. The real data results indicate that AAElastic is significantly consistent in selecting genes compared to the other three competitor regularization methods. Additionally, the classification performance of AAElastic is comparable to the adaptive elastic net and better than other regularization methods. Thus, we can conclude that AAElastic is a reliable adaptive regularized logistic regression method in the field of high-dimensional cancer classification.

  17. CASCADE, a platform for controlled gene amplification for high, tunable and selection-free gene expression in yeast

    Science.gov (United States)

    Strucko, Tomas; Buron, Line Due; Jarczynska, Zofia Dorota; Nødvig, Christina Spuur; Mølgaard, Louise; Halkier, Barbara Ann; Mortensen, Uffe Hasbro

    2017-01-01

    Over-expression of a gene by increasing its copy number is often desirable in the model yeast Saccharomyces cerevisiae. It may facilitate elucidation of enzyme functions, and in cell factory design it is used to increase production of proteins and metabolites. Current methods are typically exploiting expression from the multicopy 2 μ-derived plasmid or by targeting genes repeatedly into sequences like Ty or rDNA; in both cases, high gene expression levels are often reached. However, with 2 μ-based plasmid expression, the population of cells is very heterogeneous with respect to protein production; and for integration into repeated sequences it is difficult to determine the genetic setup of the resulting strains and to achieve specific gene doses. For both types of systems, the strains often suffer from genetic instability if proper selection pressure is not applied. Here we present a gene amplification system, CASCADE, which enables construction of strains with defined gene copy numbers. One or more genes can be amplified simultaneously and the resulting strains can be stably propagated on selection-free medium. As proof-of-concept, we have successfully used CASCADE to increase heterologous production of two fluorescent proteins, the enzyme β-galactosidase the fungal polyketide 6-methyl salicylic acid and the plant metabolite vanillin glucoside. PMID:28134264

  18. Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

    Science.gov (United States)

    Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

    2016-01-15

    As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species.

  19. Sexual selection and magic traits in speciation with gene flow

    Institute of Scientific and Technical Information of China (English)

    Maria R.SERVEDIO; Michael KOPP

    2012-01-01

    The extent to which sexual selection is involved in speciation with gene flow remains an open question and the subject of much research.Here,we propose that some insight can be gained from considering the concept of magic traits (i.e.,traits involved in both reproductive isolation and ecological divergence).Both magic traits and other,“non-magic”,traits can contribute to speciation via a number of specific mechanisms.We argue that many of these mechanisms are likely to differ widely in the extent to which they involve sexual selection.Furthermore,in some cases where sexual selection is present,it may be prone to inhibit rather than drive speciation.Finally,there are a priori reasons to believe that certain categories of traits are much more effective than others in driving speciation.The combination of these points suggests a classification of traits that may shed light on the broader role of sexual selection in speciation with gene flow.In particular,we suggest that sexual selection can act as a driver of speciation in some scenarios,but may play a negligible role in potentially common categories of magic traits,and may be likely to inhibit speeiation in common categories of non-magic traits.

  20. Scalable gene synthesis by selective amplification of DNA pools from high-fidelity microchips.

    Science.gov (United States)

    Kosuri, Sriram; Eroshenko, Nikolai; Leproust, Emily M; Super, Michael; Way, Jeffrey; Li, Jin Billy; Church, George M

    2010-12-01

    Development of cheap, high-throughput and reliable gene synthesis methods will broadly stimulate progress in biology and biotechnology. Currently, the reliance on column-synthesized oligonucleotides as a source of DNA limits further cost reductions in gene synthesis. Oligonucleotides from DNA microchips can reduce costs by at least an order of magnitude, yet efforts to scale their use have been largely unsuccessful owing to the high error rates and complexity of the oligonucleotide mixtures. Here we use high-fidelity DNA microchips, selective oligonucleotide pool amplification, optimized gene assembly protocols and enzymatic error correction to develop a method for highly parallel gene synthesis. We tested our approach by assembling 47 genes, including 42 challenging therapeutic antibody sequences, encoding a total of ∼35 kilobase pairs of DNA. These assemblies were performed from a complex background containing 13,000 oligonucleotides encoding ∼2.5 megabases of DNA, which is at least 50 times larger than in previously published attempts.

  1. PERFORMANCE OF SELECTED AGGLOMERATIVE HIERARCHICAL CLUSTERING METHODS

    Directory of Open Access Journals (Sweden)

    Nusa Erman

    2015-01-01

    Full Text Available A broad variety of different methods of agglomerative hierarchical clustering brings along problems how to choose the most appropriate method for the given data. It is well known that some methods outperform others if the analysed data have a specific structure. In the presented study we have observed the behaviour of the centroid, the median (Gower median method, and the average method (unweighted pair-group method with arithmetic mean – UPGMA; average linkage between groups. We have compared them with mostly used methods of hierarchical clustering: the minimum (single linkage clustering, the maximum (complete linkage clustering, the Ward, and the McQuitty (groups method average, weighted pair-group method using arithmetic averages - WPGMA methods. We have applied the comparison of these methods on spherical, ellipsoid, umbrella-like, “core-and-sphere”, ring-like and intertwined three-dimensional data structures. To generate the data and execute the analysis, we have used R statistical software. Results show that all seven methods are successful in finding compact, ball-shaped or ellipsoid structures when they are enough separated. Conversely, all methods except the minimum perform poor on non-homogenous, irregular and elongated ones. Especially challenging is a circular double helix structure; it is being correctly revealed only by the minimum method. We can also confirm formerly published results of other simulation studies, which usually favour average method (besides Ward method in cases when data is assumed to be fairly compact and well separated.

  2. Using effective subnetworks to predict selected properties of gene networks.

    Directory of Open Access Journals (Sweden)

    Gemunu H Gunaratne

    Full Text Available BACKGROUND: Difficulties associated with implementing gene therapy are caused by the complexity of the underlying regulatory networks. The forms of interactions between the hundreds of genes, proteins, and metabolites in these networks are not known very accurately. An alternative approach is to limit consideration to genes on the network. Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. Furthermore, error estimates of the network make verifiable predictions impossible. METHODOLOGY/PRINCIPAL FINDINGS: Here, we propose an alternative approach. Rather than attempting to derive an accurate model of the network, we ask what questions can be addressed using lower dimensional, highly simplified models. More importantly, is it possible to use such robust features in applications? We first identify a small group of genes that can be used to affect changes in other nodes of the network. The reduced effective empirical subnetwork (EES can be computed using steady state measurements on a small number of genetically perturbed systems. We show that the EES can be used to make predictions on expression profiles of other mutants, and to compute how to implement pre-specified changes in the steady state of the underlying biological process. These assertions are verified in a synthetic influence network. We also use previously published experimental data to compute the EES associated with an oxygen deprivation network of E.coli, and use it to predict gene expression levels on a double mutant. The predictions are significantly different from the experimental results for less than of genes. CONCLUSIONS/SIGNIFICANCE: The constraints imposed by gene expression levels of mutants can be used to address a selected set of questions about a gene network.

  3. NEW FEATURE SELECTION METHOD IN MACHINE FAULT DIAGNOSIS

    Institute of Scientific and Technical Information of China (English)

    Wang Xinfeng; Qiu Jing; Liu Guanjun

    2005-01-01

    Aiming to deficiency of the filter and wrapper feature selection methods, a new method based on composite method of filter and wrapper method is proposed. First the method filters original features to form a feature subset which can meet classification correctness rate, then applies wrapper feature selection method select optimal feature subset. A successful technique for solving optimization problems is given by genetic algorithm (GA). GA is applied to the problem of optimal feature selection. The composite method saves computing time several times of the wrapper method with holding the classification accuracy in data simulation and experiment on bearing fault feature selection. So this method possesses excellent optimization property, can save more selection time, and has the characteristics of high accuracy and high efficiency.

  4. Color selective photodetector and methods of making

    Science.gov (United States)

    Walker, Brian J.; Dorn, August; Bulovic, Vladimir; Bawendi, Moungi G.

    2013-03-19

    A photoelectric device, such as a photodetector, can include a semiconductor nanowire electrostatically associated with a J-aggregate. The J-aggregate can facilitate absorption of a desired wavelength of light, and the semiconductor nanowire can facilitate charge transport. The color of light detected by the device can be chosen by selecting a J-aggregate with a corresponding peak absorption wavelength.

  5. Genome-wide scans provide evidence for positive selection of genes implicated in Lassa fever.

    Science.gov (United States)

    Andersen, Kristian G; Shylakhter, Ilya; Tabrizi, Shervin; Grossman, Sharon R; Happi, Christian T; Sabeti, Pardis C

    2012-03-19

    Rapidly evolving viruses and other pathogens can have an immense impact on human evolution as natural selection acts to increase the prevalence of genetic variants providing resistance to disease. With the emergence of large datasets of human genetic variation, we can search for signatures of natural selection in the human genome driven by such disease-causing microorganisms. Based on this approach, we have previously hypothesized that Lassa virus (LASV) may have been a driver of natural selection in West African populations where Lassa haemorrhagic fever is endemic. In this study, we provide further evidence for this notion. By applying tests for selection to genome-wide data from the International Haplotype Map Consortium and the 1000 Genomes Consortium, we demonstrate evidence for positive selection in LARGE and interleukin 21 (IL21), two genes implicated in LASV infectivity and immunity. We further localized the signals of selection, using the recently developed composite of multiple signals method, to introns and putative regulatory regions of those genes. Our results suggest that natural selection may have targeted variants giving rise to alternative splicing or differential gene expression of LARGE and IL21. Overall, our study supports the hypothesis that selective pressures imposed by LASV may have led to the emergence of particular alleles conferring resistance to Lassa fever, and opens up new avenues of research pursuit.

  6. Utility of the pat gene as a selectable marker gene in production of transgenic Dunaliella salina

    Directory of Open Access Journals (Sweden)

    Hyo Sun Jung

    2016-09-01

    Full Text Available Abstract Background The objective of this study was to develop an efficient selectable marker for transgenic Dunaliella salina. Results Tests of the sensitivity of D. salina to the antibiotic chloramphenicol and the herbicide Basta® showed that cells (1.0 × 106 cells/ml treated with 1000 or 1500 μg/ml chloramphenicol died in 8 or 6 days, respectively, whereas D. salina cells (1.0 × 106 cells/ml treated with 5, 10, 20, or 40 μg/ml Basta® died in 2 days. Therefore, D. salina is more sensitive to Basta® than to chloramphenicol. To examine the possibility of using the phosphinothricin N-acetyltransferase (pat gene as a selectable marker gene, we introduced the pat genes into D. salina with particle bombardment system under the condition of helium pressure of 900 psi from a distance of 3 cm. PCR analysis confirmed that the gene was stably inserted into the cells and that the cells survived in 5 μg/ml Basta®, the medium used to select the transformed cells. Conclusions The findings of this study suggest that the pat gene can be used as an efficient selectable marker when producing transgenic D. salina.

  7. OrthoSelect: a web server for selecting orthologous gene alignments from EST sequences.

    Science.gov (United States)

    Schreiber, Fabian; Wörheide, Gert; Morgenstern, Burkhard

    2009-07-01

    In the absence of whole genome sequences for many organisms, the use of expressed sequence tags (EST) offers an affordable approach for researchers conducting phylogenetic analyses to gain insight about the evolutionary history of organisms. Reliable alignments for phylogenomic analyses are based on orthologous gene sequences from different taxa. So far, researchers have not sufficiently tackled the problem of the completely automated construction of such datasets. Existing software tools are either semi-automated, covering only part of the necessary data processing, or implemented as a pipeline, requiring the installation and configuration of a cascade of external tools, which may be time-consuming and hard to manage. To simplify data set construction for phylogenomic studies, we set up a web server that uses our recently developed OrthoSelect approach. To the best of our knowledge, our web server is the first web-based EST analysis pipeline that allows the detection of orthologous gene sequences in EST libraries and outputs orthologous gene alignments. Additionally, OrthoSelect provides the user with an extensive results section that lists and visualizes all important results, such as annotations, data matrices for each gene/taxon and orthologous gene alignments. The web server is available at http://orthoselect.gobics.de.

  8. Reference genes selection and normalization of oxidative stress responsive genes upon different temperature stress conditions in Hypericum perforatum L.

    Science.gov (United States)

    Velada, Isabel; Ragonezi, Carla; Arnholdt-Schmitt, Birgit; Cardoso, Hélia

    2014-01-01

    Reverse transcription-quantitative real-time PCR (RT-qPCR) is a widely used technique for gene expression analysis. The reliability of this method depends largely on the suitable selection of stable reference genes for accurate data normalization. Hypericum perforatum L. (St. John's wort) is a field growing plant that is frequently exposed to a variety of adverse environmental stresses that can negatively affect its productivity. This widely known medicinal plant with broad pharmacological properties (anti-depressant, anti-tumor, anti-inflammatory, antiviral, antioxidant, anti-cancer, and antibacterial) has been overlooked with respect to the identification of reference genes suitable for RT-qPCR data normalization. In this study, 11 candidate reference genes were analyzed in H. perforatum plants subjected to cold and heat stresses. The expression stability of these genes was assessed using GeNorm, NormFinder and BestKeeper algorithms. The results revealed that the ranking of stability among the three algorithms showed only minor differences within each treatment. The best-ranked reference genes differed between cold- and heat-treated samples; nevertheless, TUB was the most stable gene in both experimental conditions. GSA and GAPDH were found to be reliable reference genes in cold-treated samples, while GAPDH showed low expression stability in heat-treated samples. 26SrRNA and H2A had the highest stabilities in the heat assay, whereas H2A was less stable in the cold assay. Finally, AOX1, AOX2, CAT1 and CHS genes, associated with plant stress responses and oxidative stress, were used as target genes to validate the reliability of identified reference genes. These target genes showed differential expression profiles over time in treated samples. This study not only is the first systematic analysis for the selection of suitable reference genes for RT-qPCR studies in H. perforatum subjected to temperature stress conditions, but may also provide valuable information

  9. Reference genes selection and normalization of oxidative stress responsive genes upon different temperature stress conditions in Hypericum perforatum L.

    Directory of Open Access Journals (Sweden)

    Isabel Velada

    Full Text Available Reverse transcription-quantitative real-time PCR (RT-qPCR is a widely used technique for gene expression analysis. The reliability of this method depends largely on the suitable selection of stable reference genes for accurate data normalization. Hypericum perforatum L. (St. John's wort is a field growing plant that is frequently exposed to a variety of adverse environmental stresses that can negatively affect its productivity. This widely known medicinal plant with broad pharmacological properties (anti-depressant, anti-tumor, anti-inflammatory, antiviral, antioxidant, anti-cancer, and antibacterial has been overlooked with respect to the identification of reference genes suitable for RT-qPCR data normalization. In this study, 11 candidate reference genes were analyzed in H. perforatum plants subjected to cold and heat stresses. The expression stability of these genes was assessed using GeNorm, NormFinder and BestKeeper algorithms. The results revealed that the ranking of stability among the three algorithms showed only minor differences within each treatment. The best-ranked reference genes differed between cold- and heat-treated samples; nevertheless, TUB was the most stable gene in both experimental conditions. GSA and GAPDH were found to be reliable reference genes in cold-treated samples, while GAPDH showed low expression stability in heat-treated samples. 26SrRNA and H2A had the highest stabilities in the heat assay, whereas H2A was less stable in the cold assay. Finally, AOX1, AOX2, CAT1 and CHS genes, associated with plant stress responses and oxidative stress, were used as target genes to validate the reliability of identified reference genes. These target genes showed differential expression profiles over time in treated samples. This study not only is the first systematic analysis for the selection of suitable reference genes for RT-qPCR studies in H. perforatum subjected to temperature stress conditions, but may also provide

  10. A Scan for Positively Selected Genes in the Genomes of Humans and Chimpanzees

    DEFF Research Database (Denmark)

    Nielsen, Rasmus; Bustamente, Carlos; Clark, Andrew G.

    2005-01-01

    of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome...... such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved...... in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some...

  11. Rapid evolution and gene-specific patterns of selection for three genes of spermatogenesis in Drosophila.

    Science.gov (United States)

    Civetta, Alberto; Rajakumar, Sujeetha A; Brouwers, Barb; Bacik, John P

    2006-03-01

    Hybrid males resulting from crosses between closely related species of Drosophila are sterile. The F1 hybrid sterility phenotype is mainly due to defects occurring during late stages of development that relate to sperm individualization, and so genes controlling sperm development may have been subjected to selective diversification between species. It is also possible that genes of spermatogenesis experience selective constraints given their role in a developmental pathway. We analyzed the molecular evolution of three genes playing a role during the sperm developmental pathway in Drosophila at an early (bam), a mid (aly), and a late (dj) stage. The complete coding region of these genes was sequenced in different strains of Drosophila melanogaster and Drosophila simulans. All three genes showed rapid divergence between species, with larger numbers of nonsynonymous to synonymous differences between species than polymorphisms. Although this could be interpreted as evidence for positive selection at all three genes, formal tests of selection do not support such a conclusion. Departures from neutrality were detected only for dj and bam but not aly. The role played by selection is unique and determined by gene-specific characteristics rather than site of expression. In dj, the departure was due to a high proportion of neutral synonymous polymorphisms in D. simulans, and there was evidence of purifying selection maintaining a high lysine amino acid protein content that is characteristic of other DNA-binding proteins. The earliest spermatogenesis gene surveyed, which plays a role in both male and female gametogenesis, was bam, and its significant departure from neutrality was due to an excess of nonsynonymous substitutions between species. Bam is degraded at the end of mitosis, and rapid evolutionary changes among species might be a characteristic shared with other degradable transient proteins. However, the large number of nonsynonymous changes between D. melanogaster and

  12. Efficient Selection of Data Mining Method

    Directory of Open Access Journals (Sweden)

    Mirela Danubianu

    2011-10-01

    Full Text Available Data mining tools can access large amounts of data and find patterns that can solve various problems, often with surprising solutions. We have analyzed the data mining methods, techniques and algorithms with their characteristics, with their advantages and weakness. Taking into account the tasks to be resolved in order to discover the different types of knowledge, the kind of databases to work on and the type of data, as well as the area for which on desire the implementation of the data mining system we have try to find a way to efficiently choose the proper methods in a given situation. ExpertDM system has the aim to find the best data mining methods for solving a task and specifying the transformation which need to be made for bringing the data at a proper form for applying these methods.

  13. Classification of Cancer Gene Selection Using Random Forest and Neural Network Based Ensemble Classifier

    Directory of Open Access Journals (Sweden)

    Jogendra Kushwah

    2013-06-01

    Full Text Available The free radical gene classification of cancer diseases is challenging job in biomedical data engineering. The improving of classification of gene selection of cancer diseases various classifier are used, but the classification of classifier are not validate. So ensemble classifier is used for cancer gene classification using neural network classifier with random forest tree. The random forest tree is ensembling technique of classifier in this technique the number of classifier ensemble of their leaf node of class of classifier. In this paper we combined neural network with random forest ensemble classifier for classification of cancer gene selection for diagnose analysis of cancer diseases. The proposed method is different from most of the methods of ensemble classifier, which follow an input output paradigm of neural network, where the members of the ensemble are selected from a set of neural network classifier. the number of classifiers is determined during the rising procedure of the forest. Furthermore, the proposed method produces an ensemble not only correct, but also assorted, ensuring the two important properties that should characterize an ensemble classifier. For empirical evaluation of our proposed method we used UCI cancer diseases data set for classification. Our experimental result shows that better result in compression of random forest tree classification.

  14. LCIA selection methods for assessing toxic releases

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    2002-01-01

    Characterization of toxic emissions in life cycle impact assessment (LCIA) is in many cases severely limited by the lack of characterization factors for the emissions mapped in the inventory. The number of substances assigned characterization factors for (eco)toxicity included in the dominating LCA...... methods in use to day (e.g. Eco-indicator 99 and EDIP) is in the range of 40 – 330 and often they only cover a minor part of the substances in the inventory. The user of the LCA method should in principle be able to calculate any missing factors (if needed substance data are available which is often....... The methods are evaluated against a set of pre-defined criteria (comprising consistency with characterization and data requirement) and applied to case studies and a test set of chemicals. The reported work is part of the EU-project OMNIITOX....

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

    Directory of Open Access Journals (Sweden)

    Benjamin A Logsdon

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

  16. Selection of reliable reference genes for gene expression studies in peach using real-time PCR

    Directory of Open Access Journals (Sweden)

    Zhou Jun

    2009-07-01

    Full Text Available Abstract Background RT-qPCR is a preferred method for rapid and reliable quantification of gene expression studies. Appropriate application of RT-qPCR in such studies requires the use of reference gene(s as an internal control to normalize mRNA levels between different samples for an exact comparison of gene expression level. However, recent studies have shown that no single reference gene is universal for all experiments. Thus, the identification of high quality reference gene(s is of paramount importance for the interpretation of data generated by RT-qPCR. Only a few studies on reference genes have been done in plants and none in peach (Prunus persica L. Batsch. Therefore, the present study was conducted to identify suitable reference gene(s for normalization of gene expression in peach. Results In this work, eleven reference genes were investigated in different peach samples using RT-qPCR with SYBR green. These genes are: actin 2/7 (ACT, cyclophilin (CYP2, RNA polymerase II (RP II, phospholipase A2 (PLA2, ribosomal protein L13 (RPL13, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, 18S ribosomal RNA (18S rRNA, tubblin beta (TUB, tubblin alpha (TUA, translation elongation factor 2 (TEF2 and ubiquitin 10 (UBQ10. All eleven reference genes displayed a wide range of Cq values in all samples, indicating that they expressed variably. The stability of these genes except for RPL13 was determined by three different descriptive statistics, geNorm, NormFinder and BestKeeper, which produced highly comparable results. Conclusion Our study demonstrates that expression stability varied greatly between genes studied in peach. Based on the results from geNorm, NormFinder and BestKeeper analyses, for all the sample pools analyzed, TEF2, UBQ10 and RP II were found to be the most suitable reference genes with a very high statistical reliability, and TEF2 and RP II for the other sample series, while 18S rRNA, RPL13 and PLA2 were unsuitable as internal controls

  17. Component Thermodynamical Selection Based Gene Expression Programming for Function Finding

    Directory of Open Access Journals (Sweden)

    Zhaolu Guo

    2014-01-01

    Full Text Available Gene expression programming (GEP, improved genetic programming (GP, has become a popular tool for data mining. However, like other evolutionary algorithms, it tends to suffer from premature convergence and slow convergence rate when solving complex problems. In this paper, we propose an enhanced GEP algorithm, called CTSGEP, which is inspired by the principle of minimal free energy in thermodynamics. In CTSGEP, it employs a component thermodynamical selection (CTS operator to quantitatively keep a balance between the selective pressure and the population diversity during the evolution process. Experiments are conducted on several benchmark datasets from the UCI machine learning repository. The results show that the performance of CTSGEP is better than the conventional GEP and some GEP variations.

  18. Method for producing size selected particles

    Energy Technology Data Exchange (ETDEWEB)

    Krumdick, Gregory K.; Shin, Young Ho; Takeya, Kaname

    2016-09-20

    The invention provides a system for preparing specific sized particles, the system comprising a continuous stir tank reactor adapted to receive reactants; a centrifugal dispenser positioned downstream from the reactor and in fluid communication with the reactor; a particle separator positioned downstream of the dispenser; and a solution stream return conduit positioned between the separator and the reactor. Also provided is a method for preparing specific sized particles, the method comprising introducing reagent into a continuous stir reaction tank and allowing the reagents to react to produce product liquor containing particles; contacting the liquor particles with a centrifugal force for a time sufficient to generate particles of a predetermined size and morphology; and returning unused reagents and particles of a non-predetermined size to the tank.

  19. Method for producing size selected particles

    Science.gov (United States)

    Krumdick, Gregory K.; Shin, Young Ho; Takeya, Kaname

    2016-09-20

    The invention provides a system for preparing specific sized particles, the system comprising a continuous stir tank reactor adapted to receive reactants; a centrifugal dispenser positioned downstream from the reactor and in fluid communication with the reactor; a particle separator positioned downstream of the dispenser; and a solution stream return conduit positioned between the separator and the reactor. Also provided is a method for preparing specific sized particles, the method comprising introducing reagent into a continuous stir reaction tank and allowing the reagents to react to produce product liquor containing particles; contacting the liquor particles with a centrifugal force for a time sufficient to generate particles of a predetermined size and morphology; and returning unused reagents and particles of a non-predetermined size to the tank.

  20. UPRE method for total variation parameter selection

    Energy Technology Data Exchange (ETDEWEB)

    Wohlberg, Brendt [Los Alamos National Laboratory; Lin, Youzuo [Los Alamos National Laboratory

    2008-01-01

    Total Variation (TV) Regularization is an important method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is important to choose the optimal regularization parameter. The Unbiased Predictive Risk Estimator (UPRE) has been shown to give a very good estimate of this parameter for Tikhonov Regularization. In this paper we propose an approach to extend UPRE method to the TV problem. However, applying the extended UPRE is impractical in the case of inverse problems such as de blurring, due to the large scale of the associated linear problem. We also propose an approach to reducing the large scale problem to a small problem, significantly reducing computational requirements while providing a good approximation to the original problem.

  1. SELECTION METHOD FOR AUTOMOTIVE PARTS RECONDITIONING

    Directory of Open Access Journals (Sweden)

    Dan Florin NITOI

    2015-05-01

    Full Text Available Paper presents technological methods for metal deposition, costs calculation and clasification for the main process that helps in automotive technologies to repair or to increase pieces properties. Paper was constructed based on many technological experiments that starts from practicans and returns to them. The main aim is to help young engineers or practicians engineers to choose the proper reconditioning process with the best information in repairing pieces from automotive industry.

  2. Signatures of positive selection in LY96 gene in vertebrates

    Indian Academy of Sciences (India)

    Tonghai Dou; Maobin Fu; Yixia Wang; Yang Zhao; Zhengshi Wang; Zhengqian Bian; Yan Zhou

    2013-12-01

    As a secreted glycoprotein that binds to the extracellular domain of Toll-like receptor 4 (TLR4), Lymphocyte Antigen 96 (LY96), also called myeloid differentiation 2 (MD2), is required for the activation of TLR4 by lipopolysaccharide (LPS) and plays an important role in innate immunity, which is the first line of defence against microbial infections. Previous studies have proposed that mammalian toll-like receptors (TLRs) have evolved under diversifying selection due to their role in pathogen detection. Given the fact that LY96 is highly functionally linked to TLR4, it would be interesting to test whether LY96 is under the intense pressure of natural selection. To investigate the natural selection hypothesis, we compared the coding sequences from 13 vertebrates and evaluated the molecular evolution of LY96 gene in these species. Result shows that natural selection at exon 4 has indeed played a role in shaping the function of LY96 in the course of evolution. In addition to the study of Nakajima, we found the two branch nodes with Ka/Ks ratios greater than 1: the one leading to cow and pig and the other to rabbit and the primates.

  3. A gene-based information gain method for detecting gene-gene interactions in case-control studies.

    Science.gov (United States)

    Li, Jin; Huang, Dongli; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Zhang, Ruijie; Jiang, Yongshuai; Lv, Hongchao; Wang, Limei

    2015-11-01

    Currently, most methods for detecting gene-gene interactions (GGIs) in genome-wide association studies are divided into SNP-based methods and gene-based methods. Generally, the gene-based methods can be more powerful than SNP-based methods. Some gene-based entropy methods can only capture the linear relationship between genes. We therefore proposed a nonparametric gene-based information gain method (GBIGM) that can capture both linear relationship and nonlinear correlation between genes. Through simulation with different odds ratio, sample size and prevalence rate, GBIGM was shown to be valid and more powerful than classic KCCU method and SNP-based entropy method. In the analysis of data from 17 genes on rheumatoid arthritis, GBIGM was more effective than the other two methods as it obtains fewer significant results, which was important for biological verification. Therefore, GBIGM is a suitable and powerful tool for detecting GGIs in case-control studies.

  4. Evolutionary history of pearl millet (Pennisetum glaucum [L.] R. Br.) and selection on flowering genes since its domestication.

    Science.gov (United States)

    Clotault, Jérémy; Thuillet, Anne-Céline; Buiron, Marylène; De Mita, Stéphane; Couderc, Marie; Haussmann, Bettina I G; Mariac, Cédric; Vigouroux, Yves

    2012-04-01

    The plant domestication process is associated with considerable modifications of plant phenotype. The identification of the genetic basis of this adaptation is of great interest for evolutionary biology. One of the methods used to identify such genes is the detection of signatures of selection. However, domestication is generally associated with major demographic effects. It is therefore crucial to disentangle the effects of demography and selection on diversity. In this study, we investigated selection in a flowering time pathway during domestication of pearl millet. We first used a random set of 20 genes to model pearl millet domestication using approximate Bayesian computation. This analysis showed that a model with exponential growth and wild-cultivated gene flow was well supported by our data set. Under this model, the domestication date of pearl millet is estimated at around 4,800 years ago. We assessed selection in 15 pearl millet DNA sequences homologous to flowering time genes and showed that these genes underwent selection more frequently than expected. We highlighted significant signatures of selection in six pearl millet flowering time genes associated with domestication or improvement of pearl millet. Moreover, higher deviations from neutrality were found for circadian clock-associated genes. Our study provides new insights into the domestication process of pearl millet and shows that a category of genes of the flowering pathway were preferentially selected during pearl millet domestication.

  5. Methods of selectively incorporating metals onto substrates

    Energy Technology Data Exchange (ETDEWEB)

    Ernst; Richard D. (Salt Lake City, UT), Eyring; Edward M. (Salt Lake City, UT), Turpin; Gregory C. (Salt Lake City, UT), Dunn; Brian C. (Salt Lake City, UT)

    2008-09-30

    A method for forming multi-metallic sites on a substrate is disclosed and described. A substrate including active groups such as hydroxyl can be reacted with a pretarget metal complex. The target metal attached to the active group can then be reacted with a secondary metal complex such that an oxidation-reduction (redox) reaction occurs to form a multi-metallic species. The substrate can be a highly porous material such as aerogels, xerogels, zeolites, and similar materials. Additional metal complexes can be reacted to increase catalyst loading or control co-catalyst content. The resulting compounds can be oxidized to form oxides or reduced to form metals in the ground state which are suitable for practical use.

  6. A method to select between Gompertz and logistic trend curves

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    1994-01-01

    textabstractIn this paper a simple method is proposed to select between two often applied trend curves; the Gompertz and the logistic curve. The method is based on one auxilliary regression. Two applications illustrate its merits.

  7. Selection of suitable endogenous reference genes for relative copy number detection in sugarcane.

    Science.gov (United States)

    Xue, Bantong; Guo, Jinlong; Que, Youxiong; Fu, Zhiwei; Wu, Luguang; Xu, Liping

    2014-05-19

    Transgene copy number has a great impact on the expression level and stability of exogenous gene in transgenic plants. Proper selection of endogenous reference genes is necessary for detection of genetic components in genetically modification (GM) crops by quantitative real-time PCR (qPCR) or by qualitative PCR approach, especially in sugarcane with polyploid and aneuploid genomic structure. qPCR technique has been widely accepted as an accurate, time-saving method on determination of copy numbers in transgenic plants and on detection of genetically modified plants to meet the regulatory and legislative requirement. In this study, to find a suitable endogenous reference gene and its real-time PCR assay for sugarcane (Saccharum spp. hybrids) DNA content quantification, we evaluated a set of potential "single copy" genes including P4H, APRT, ENOL, CYC, TST and PRR, through qualitative PCR and absolute quantitative PCR. Based on copy number comparisons among different sugarcane genotypes, including five S. officinarum, one S. spontaneum and two S. spp. hybrids, these endogenous genes fell into three groups: ENOL-3--high copy number group, TST-1 and PRR-1--medium copy number group, P4H-1, APRT-2 and CYC-2--low copy number group. Among these tested genes, P4H, APRT and CYC were the most stable, while ENOL and TST were the least stable across different sugarcane genotypes. Therefore, three primer pairs of P4H-3, APRT-2 and CYC-2 were then selected as the suitable reference gene primer pairs for sugarcane. The test of multi-target reference genes revealed that the APRT gene was a specific amplicon, suggesting this gene is the most suitable to be used as an endogenous reference target for sugarcane DNA content quantification. These results should be helpful for establishing accurate and reliable qualitative and quantitative PCR analysis of GM sugarcane.

  8. Selection of Suitable Endogenous Reference Genes for Relative Copy Number Detection in Sugarcane

    Directory of Open Access Journals (Sweden)

    Bantong Xue

    2014-05-01

    Full Text Available Transgene copy number has a great impact on the expression level and stability of exogenous gene in transgenic plants. Proper selection of endogenous reference genes is necessary for detection of genetic components in genetically modification (GM crops by quantitative real-time PCR (qPCR or by qualitative PCR approach, especially in sugarcane with polyploid and aneuploid genomic structure. qPCR technique has been widely accepted as an accurate, time-saving method on determination of copy numbers in transgenic plants and on detection of genetically modified plants to meet the regulatory and legislative requirement. In this study, to find a suitable endogenous reference gene and its real-time PCR assay for sugarcane (Saccharum spp. hybrids DNA content quantification, we evaluated a set of potential “single copy” genes including P4H, APRT, ENOL, CYC, TST and PRR, through qualitative PCR and absolute quantitative PCR. Based on copy number comparisons among different sugarcane genotypes, including five S. officinarum, one S. spontaneum and two S. spp. hybrids, these endogenous genes fell into three groups: ENOL-3—high copy number group, TST-1 and PRR-1—medium copy number group, P4H-1, APRT-2 and CYC-2—low copy number group. Among these tested genes, P4H, APRT and CYC were the most stable, while ENOL and TST were the least stable across different sugarcane genotypes. Therefore, three primer pairs of P4H-3, APRT-2 and CYC-2 were then selected as the suitable reference gene primer pairs for sugarcane. The test of multi-target reference genes revealed that the APRT gene was a specific amplicon, suggesting this gene is the most suitable to be used as an endogenous reference target for sugarcane DNA content quantification. These results should be helpful for establishing accurate and reliable qualitative and quantitative PCR analysis of GM sugarcane.

  9. Optimal Route Selection Method Based on Vague Sets

    Institute of Scientific and Technical Information of China (English)

    GUO Rui; DU Li min; WANG Chun

    2015-01-01

    Optimal route selection is an important function of vehicle trac flow guidance system. Its core is to determine the index weight for measuring the route merits and to determine the evaluation method for selecting route. In this paper, subjective weighting method which relies on driver preference is used to determine the weight and the paper proposes the multi-criteria weighted decision method based on vague sets for selecting the optimal route. Examples show that, the usage of vague sets to describe route index value can provide more decision-making information for route selection.

  10. Fuzzy Assessment Method and Its Application to Selecting Project Managers

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Open competition is a new form of the assessment of candidates and selection of project managers. This has many merits compared to the traditional administrative method of appointment. This article introduces a method of fuzzy assessment of project manager candidates. Fuzzy assessment unifies objective qualitative and quantitative appraisal and can be used for improving decision-making in the selection process.

  11. Degenerative primer design and gene sequencing validation for select turkey genes.

    Science.gov (United States)

    Hutsko, Stephanie L; Lilburn, Michael S; Wick, Macdonald

    2016-06-01

    We successfully designed and validated degenerative primers for turkey genes MUC2, RPS13, TBP and TFF2 based on chicken sequences in order to use gene transcription analysis to evaluate (quantify) the mucin transcription to probiotic supplementation in turkeys. Primers were designed for the genes MUC2, TFF2, RPS13 and TBP using a degenerative primer design method based on the available Gallus gallus sequences. All primer sets, which produced a single PCR amplicon of the expected sizes, were cloned into the TOPO(®) vector and then transformed into TOP 10(®) competent cells. Plasmid DNA isolation was performed on the TOP10(®) cell culture and sent for sequencing. Sequences were analyzed using NCBI BLAST. All genes sequenced had over 90% homology with both the chicken and predicted turkey sequences. The sequences were used to design new 100% homologous primer sets for the genes of interest. © 2016 Poultry Science Association Inc.

  12. Primate ABO Gene is under Weak Positive Selection

    Directory of Open Access Journals (Sweden)

    Eliane Santos EVANOVICH

    2012-05-01

    Full Text Available ABO locus presents three main alleles: A, B and O. A and B encode glycosyltransferases that catalyze the addiction of an N-GalNac and D-galactose to a precursor substance (H substance, producing A and B antigens, while the O allele does not produce a functional protein. The presence of A and B antigens have been associated to resistance against infectious agents which could use them as attachment factors increasing the virulence of some parasitic agents. As these antigens are not restrict to humans, analyses them in others species, for instance non-human primates, may be crucial to understand the relationship between pathogens and ABO phenotypes. Despite of the relevance of this issue, in the last decade few studies have addressed, mainly in New World Monkeys (NWM, natural reservoir of tropical diseases in Amazon Region. In order to understand the evolution of the ABO system in the primates, it has been obtained the partial sequence of the most important exon of ABO gene (exon 7, in platyrrhini families: Atelidae, Pithecidae and Cebidae. Then, it has been compared the sequences obtained those present in the literature, and measured the selective pressure. The present results shown that residues 266 and 268 are also crucial to distinguish A and B phenotypes in the platyrrhines, such as in catarrhines, and the 266 codon is under positive selection, although the most site codons are under action of purifying selection.

  13. A method for selecting training samples based on camera response

    Science.gov (United States)

    Zhang, Leihong; Li, Bei; Pan, Zilan; Liang, Dong; Kang, Yi; Zhang, Dawei; Ma, Xiuhua

    2016-09-01

    In the process of spectral reflectance reconstruction, sample selection plays an important role in the accuracy of the constructed model and in reconstruction effects. In this paper, a method for training sample selection based on camera response is proposed. It has been proved that the camera response value has a close correlation with the spectral reflectance. Consequently, in this paper we adopt the technique of drawing a sphere in camera response value space to select the training samples which have a higher correlation with the test samples. In addition, the Wiener estimation method is used to reconstruct the spectral reflectance. Finally, we find that the method of sample selection based on camera response value has the smallest color difference and root mean square error after reconstruction compared to the method using the full set of Munsell color charts, the Mohammadi training sample selection method, and the stratified sampling method. Moreover, the goodness of fit coefficient of this method is also the highest among the four sample selection methods. Taking all the factors mentioned above into consideration, the method of training sample selection based on camera response value enhances the reconstruction accuracy from both the colorimetric and spectral perspectives.

  14. Mathematical analysis of antigen selection in somatically mutated immunoglobulin genes associated with autoimmunity.

    Science.gov (United States)

    MacDonald, C M; Boursier, L; D'Cruz, D P; Dunn-Walters, D K; Spencer, J

    2010-09-01

    Affinity maturation is a process by which low-affinity antibodies are transformed into highly specific antibodies in germinal centres. This process occurs by hypermutation of immunoglobulin heavy chain variable (IgH V) region genes followed by selection for high-affinity variants. It has been proposed that statistical tests can identify affinity maturation and antigen selection by analysing the frequency of replacement and silent mutations in the complementarity determining regions (CDRs) that contact antigen and the framework regions (FRs) that encode structural integrity. In this study three different methods that have been proposed for detecting selection: the binomial test, the multinomial test and the focused binomial test, have been assessed for their reliability and ability to detect selection in human IgH V genes. We observe first that no statistical test is able to identify selection in the CDR antigen-binding sites, second that tests can reliably detect selection in the FR and third that antibodies from nasal biopsies from patients with Wegener's granulomatosis and pathogenic antibodies from systemic lupus erythematosus do not appear to be as stringently selected for structural integrity as other groups of functional sequences.

  15. Positive Selection of a Pre-Expansion CAG Repeat of the Human SCA2 Gene.

    Directory of Open Access Journals (Sweden)

    2005-09-01

    Full Text Available A region of approximately one megabase of human Chromosome 12 shows extensive linkage disequilibrium in Utah residents with ancestry from northern and western Europe. This strikingly large linkage disequilibrium block was analyzed with statistical and experimental methods to determine whether natural selection could be implicated in shaping the current genome structure. Extended Haplotype Homozygosity and Relative Extended Haplotype Homozygosity analyses on this region mapped a core region of the strongest conserved haplotype to the exon 1 of the Spinocerebellar ataxia type 2 gene (SCA2. Direct DNA sequencing of this region of the SCA2 gene revealed a significant association between a pre-expanded allele [(CAG(8CAA(CAG(4CAA(CAG(8] of CAG repeats within exon 1 and the selected haplotype of the SCA2 gene. A significantly negative Tajima's D value (-2.20, p < 0.01 on this site consistently suggested selection on the CAG repeat. This region was also investigated in the three other populations, none of which showed signs of selection. These results suggest that a recent positive selection of the pre-expansion SCA2 CAG repeat has occurred in Utah residents with European ancestry.

  16. Positive selection of a pre-expansion CAG repeat of the human SCA2 gene.

    Directory of Open Access Journals (Sweden)

    Fuli Yu

    2005-09-01

    Full Text Available A region of approximately one megabase of human Chromosome 12 shows extensive linkage disequilibrium in Utah residents with ancestry from northern and western Europe. This strikingly large linkage disequilibrium block was analyzed with statistical and experimental methods to determine whether natural selection could be implicated in shaping the current genome structure. Extended Haplotype Homozygosity and Relative Extended Haplotype Homozygosity analyses on this region mapped a core region of the strongest conserved haplotype to the exon 1 of the Spinocerebellar ataxia type 2 gene (SCA2. Direct DNA sequencing of this region of the SCA2 gene revealed a significant association between a pre-expanded allele [(CAG8CAA(CAG4CAA(CAG8] of CAG repeats within exon 1 and the selected haplotype of the SCA2 gene. A significantly negative Tajima's D value (-2.20, p < 0.01 on this site consistently suggested selection on the CAG repeat. This region was also investigated in the three other populations, none of which showed signs of selection. These results suggest that a recent positive selection of the pre-expansion SCA2 CAG repeat has occurred in Utah residents with European ancestry.

  17. A scan for positively selected genes in the genomes of humans and chimpanzees.

    Directory of Open Access Journals (Sweden)

    Rasmus Nielsen

    2005-06-01

    Full Text Available Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome also tend to show an elevated tendency for positive selection. We also present polymorphism data from 20 Caucasian Americans and 19 African Americans for the 50 annotated genes showing the strongest evidence for positive selection. The polymorphism analysis further supports the presence of positive selection in these genes by showing an excess of high-frequency derived nonsynonymous mutations.

  18. When is hub gene selection better than standard meta-analysis?

    Directory of Open Access Journals (Sweden)

    Peter Langfelder

    Full Text Available Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data. Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA in three comprehensive and unbiased empirical studies: (1 Finding genes predictive of lung cancer survival, (2 finding methylation markers related to age, and (3 finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1. However, standard meta-analysis methods perform as good as (if not better than a consensus network approach in terms of validation success (criterion 2. The article also reports a comparison of meta-analysis techniques

  19. A New Feature Selection Method for Text Clustering

    Institute of Scientific and Technical Information of China (English)

    XU Junling; XU Baowen; ZHANG Weifeng; CUI Zifeng; ZHANG Wei

    2007-01-01

    Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this paper, a new feature selection method for text clustering based on expectation maximization and cluster validity is proposed. It uses supervised feature selection method on the intermediate clustering result which is generated during iterative clustering to do feature selection for text clustering; meanwhile, the Davies-Bouldin's index is used to evaluate the intermediate feature subsets indirectly. Then feature subsets are selected according to the curve of the DaviesBouldin's index. Experiment is carried out on several popular datasets and the results show the advantages of the proposed method.

  20. A Fast Adaptive Receive Antenna Selection Method in MIMO System

    Directory of Open Access Journals (Sweden)

    Chaowei Wang

    2013-01-01

    Full Text Available Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

  1. Inventory of LCIA selection methods for assessing toxic releases. Methods and typology report part B

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    This report describes an inventory of Life Cycle Impact Assessment (LCIA) selection methods for assessing toxic releases. It consists of an inventory of current selection methods and other Chemical Ranking and Scoring (CRS) methods assessed to be relevant for the development of (a) new selection...... method(s) in Work package 8 (WP8) of the OMNIITOX project. The selection methods and the other CRS methods are described in detail, a set of evaluation criteria are developed and the methods are evaluated against these criteria. This report (Deliverable 11B (D11B)) gives the results from task 7.1d, 7.1e...

  2. Double suicide genes selectively kill human umbilical vein endothelial cells

    Directory of Open Access Journals (Sweden)

    Liu Lunxu

    2011-02-01

    Full Text Available Abstract Background To construct a recombinant adenovirus containing CDglyTK double suicide genes and evaluate the killing effect of the double suicide genes driven by kinase domain insert containing receptor (KDR promoter on human umbilical vein endothelial cells. Methods Human KDR promoter, Escherichia coli (E. coli cytosine deaminase (CD gene and the herpes simplex virus-thymidine kinase (TK gene were cloned using polymerase chain reaction (PCR. Plasmid pKDR-CDglyTK was constructed with the KDR promoter and CDglyTK genes. A recombinant adenoviral plasmid AdKDR-CDglyTK was then constructed and transfected into 293 packaging cells to grow and harvest adenoviruses. KDR-expressing human umbilical vein endothelial cells (ECV304 and KDR-negative liver cancer cell line (HepG2 were infected with the recombinant adenoviruses at different multiplicity of infection (MOI. The infection rate was measured by green fluorescent protein (GFP expression. The infected cells were cultured in culture media containing different concentrations of prodrugs ganciclovir (GCV and/or 5-fluorocytosine (5-FC. The killing effects were measured using two different methods, i.e. annexin V-FITC staining and terminal transferase-mediated dUTP nick end-labeling (TUNEL staining. Results Recombinant adenoviruses AdKDR-CDglyTK were successfully constructed and they infected ECV304 and HepG2 cells efficiently. The infection rate was dependent on MOI of recombinant adenoviruses. ECV304 cells infected with AdKDR-CDglyTK were highly sensitive to GCV and 5-FC. The cell survival rate was dependent on both the concentration of the prodrugs and the MOI of recombinant adenoviruses. In contrast, there were no killing effects in the HepG2 cells. The combination of two prodrugs was much more effective in killing ECV304 cells than GCV or 5-FC alone. The growth of transgenic ECV304 cells was suppressed in the presence of prodrugs. Conclusion AdKDR-CDglyTK/double prodrog system may be a useful

  3. Rapid and targeted introgression of genes into popular wheat cultivars using marker-assisted background selection.

    Directory of Open Access Journals (Sweden)

    Harpinder S Randhawa

    Full Text Available A marker-assisted background selection (MABS-based gene introgression approach in wheat (Triticum aestivum L. was optimized, where 97% or more of a recurrent parent genome (RPG can be recovered in just two backcross (BC generations. A four-step MABS method was developed based on 'Plabsim' computer simulations and wheat genome structure information. During empirical optimization of this method, double recombinants around the target gene were selected in a step-wise fashion during the two BC cycles followed by selection for recurrent parent genotype on non-carrier chromosomes. The average spacing between carrier chromosome markers was <4 cM. For non-carrier chromosome markers that flanked each of the 48 wheat gene-rich regions, this distance was approximately 12 cM. Employed to introgress seedling stripe rust (Puccinia striiformis f. sp. tritici resistance gene Yr15 into the spring wheat cultivar 'Zak', marker analysis of 2,187 backcross-derived progeny resulted in the recovery of a BC(2F(2ratio3 plant with 97% of the recurrent parent genome. In contrast, only 82% of the recurrent parent genome was recovered in phenotypically selected BC(4F(7 plants developed without MABS. Field evaluation results from 17 locations indicated that the MABS-derived line was either equal or superior to the recurrent parent for the tested agronomic characteristics. Based on these results, MABS is recommended as a strategy for rapidly introgressing a targeted gene into a wheat genotype in just two backcross generations while recovering 97% or more of the recurrent parent genotype.

  4. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

    Directory of Open Access Journals (Sweden)

    Nisrine Jrad

    2009-01-01

    rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers.

  5. Hybrid SPR algorithm to select predictive genes for effectual cancer classification

    OpenAIRE

    2012-01-01

    Designing an automated system for classifying DNA microarray data is an extremely challenging problem because of its high dimension and low amount of sample data. In this paper, a hybrid statistical pattern recognition algorithm is proposed to reduce the dimensionality and select the predictive genes for the classification of cancer. Colon cancer gene expression profiles having 62 samples of 2000 genes were used for the experiment. A gene subset of 6 highly informative genes was selecte...

  6. Genetic subdivision and candidate genes under selection in North American grey wolves.

    Science.gov (United States)

    Schweizer, Rena M; vonHoldt, Bridgett M; Harrigan, Ryan; Knowles, James C; Musiani, Marco; Coltman, David; Novembre, John; Wayne, Robert K

    2016-01-01

    Previous genetic studies of the highly mobile grey wolf (Canis lupus) found population structure that coincides with habitat and phenotype differences. We hypothesized that these ecologically distinct populations (ecotypes) should exhibit signatures of selection in genes related to morphology, coat colour and metabolism. To test these predictions, we quantified population structure related to habitat using a genotyping array to assess variation in 42 036 single-nucleotide polymorphisms (SNPs) in 111 North American grey wolves. Using these SNP data and individual-level measurements of 12 environmental variables, we identified six ecotypes: West Forest, Boreal Forest, Arctic, High Arctic, British Columbia and Atlantic Forest. Next, we explored signals of selection across these wolf ecotypes through the use of three complementary methods to detect selection: FST /haplotype homozygosity bivariate percentilae, bayescan, and environmentally correlated directional selection with bayenv. Across all methods, we found consistent signals of selection on genes related to morphology, coat coloration, metabolism, as predicted, as well as vision and hearing. In several high-ranking candidate genes, including LEPR, TYR and SLC14A2, we found variation in allele frequencies that follow environmental changes in temperature and precipitation, a result that is consistent with local adaptation rather than genetic drift. Our findings show that local adaptation can occur despite gene flow in a highly mobile species and can be detected through a moderately dense genomic scan. These patterns of local adaptation revealed by SNP genotyping likely reflect high fidelity to natal habitats of dispersing wolves, strong ecological divergence among habitats, and moderate levels of linkage in the wolf genome. © 2015 John Wiley & Sons Ltd.

  7. Methods for the isolation of genes encoding novel PHB cycle enzymes from complex microbial communities.

    Science.gov (United States)

    Nordeste, Ricardo F; Trainer, Maria A; Charles, Trevor C

    2010-01-01

    Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bioplastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti allows for the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates finding functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

  8. Evaluation of the effect and profitability of gene-assisted selection in pig breeding system

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Objective: To evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS). Methods: Three populations (100, 200, or 300 sows plus 10 boars within each group)with segregating QTL were simulated stochastically. Five economic traits were investigated, including number of born alive(NBA), average daily gain to 100 kg body weight (ADG), feed conversion ratio (FCR), back fat at 100 kg body weight (BF) and intramuscular fat (IMF). Selection was based on the estimated breeding value (EBV) of each trait. The starting frequencies of the QTL's favorable allele were 0.1, 0.3 and 0.5, respectively. The economic return was calculated by gene flow method. Results: The selection efficiency was higher than 100% when DR markers were used in GAS for 5 traits. The selection efficiency for NBA was the highest, and the lowest was for ADG whose QTL had the lowest variance. The mixed model applied DR markers and obtained higher extra genetic gain and extra economic returns. We also found that the lower the frequency of the favorable allele of the QTL,the higher the extra return obtained. Conclusion: GAS is an effective selection scheme to increase the genetic gain and the economic returns in pig breeding.

  9. Selection of Equipment by Using Saw and Vikor Methods

    Directory of Open Access Journals (Sweden)

    P.Venkateswarlu

    2016-11-01

    Full Text Available Now a days, Lean manufacturing becomes a key strategy for global competition. In this environment the most important process is the selection of the equipment. Equipment selection is a very important issue for effective manufacturing companies due to the fact that improperly selected machines can negatively affect the overall performance of manufacturing system. The availability of large number of equipments are more hence, the selection of suitable equipment for certain operation/ product becomes difficult. On the other hand selecting the best equipment among many alternatives is a Multi-criteria decision making ( MCDM Problems. In this Paper an approach which employs SAW, VIKOR Methods proposed for the equipment selection problem. The SAW and VIKOR is used to analyze the structure of the equipment selection problem and to determine weights of criteria and to obtain Final Ranking.

  10. A Method of Determining Selectivity Coefficients Based on the Practical Slope of Ion Selective Electrodes

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    It is a problem to be solved that the experimental selectivity coefficients of ion selective electrodes (ISEs) depend on the activity.This paper studied the new method of determining selectivity coefficients.A mixed ion response equation,which was similar to Nicolsky-Eisenman (N-E) equation recommended by IUPAC,was proposed.The equation includes the practical response slope of ISEs to the primary ion and the interfering ion.The selectivity coefficient was defined by the equation instead of the N-E equation.The experimental part of the method is similar to that based on the N-E equation.The values of selectivity coefficients obtained with this method do not depend on the activity whether the electrodes exhibit the Nernst response or non-Nernst response.The feasibility of the new method is illustrated experimentally.

  11. Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data

    Directory of Open Access Journals (Sweden)

    He Miao

    2009-12-01

    Full Text Available Abstract Background More studies based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification methods. The main purpose of this research was to compare the performance of linear discriminant analysis (LDA and its modification methods for the classification of cancer based on gene expression data. Methods The classification performance of linear discriminant analysis (LDA and its modification methods was evaluated by applying these methods to six public cancer gene expression datasets. These methods included linear discriminant analysis (LDA, prediction analysis for microarrays (PAM, shrinkage centroid regularized discriminant analysis (SCRDA, shrinkage linear discriminant analysis (SLDA and shrinkage diagonal discriminant analysis (SDDA. The procedures were performed by software R 2.80. Results PAM picked out fewer feature genes than other methods from most datasets except from Brain dataset. For the two methods of shrinkage discriminant analysis, SLDA selected more genes than SDDA from most datasets except from 2-class lung cancer dataset. When comparing SLDA with SCRDA, SLDA selected more genes than SCRDA from 2-class lung cancer, SRBCT and Brain dataset, the result was opposite for the rest datasets. The average test error of LDA modification methods was lower than LDA method. Conclusions The classification performance of LDA modification methods was superior to that of traditional LDA with respect to the average error and there was no significant difference between theses modification methods.

  12. Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

    Science.gov (United States)

    Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

    2015-01-01

    Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural.

  13. Alternative microbial methods: An overview and selection criteria.

    NARCIS (Netherlands)

    Jasson, V.; Jacxsens, L.; Luning, P.A.; Rajkovic, A.; Uyttendaele, M.

    2010-01-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant

  14. The Hull Method for Selecting the Number of Common Factors

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L.

    2011-01-01

    A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

  15. Game Methodology for Design Methods and Tools Selection

    Science.gov (United States)

    Ahmad, Rafiq; Lahonde, Nathalie; Omhover, Jean-françois

    2014-01-01

    Design process optimisation and intelligence are the key words of today's scientific community. A proliferation of methods has made design a convoluted area. Designers are usually afraid of selecting one method/tool over another and even expert designers may not necessarily know which method is the best to use in which circumstances. This…

  16. Alternative microbial methods: An overview and selection criteria.

    NARCIS (Netherlands)

    Jasson, V.; Jacxsens, L.; Luning, P.A.; Rajkovic, A.; Uyttendaele, M.

    2010-01-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant

  17. The DNA aptamers that specifically recognize ricin toxin are selected by two in vitro selection methods.

    Science.gov (United States)

    Tang, Jijun; Xie, Jianwei; Shao, Ningsheng; Yan, Yan

    2006-04-01

    Aptamers which specifically recognize cytotoxin ricin were successfully selected using the two different in vitro selection methods. One selection method was used to isolate aptamers by affinity chromatography. Another selection method, named CE-SELEX, was carried out using CE as a separation approach. The high separation efficiency of CE evidently improved the rate of enrichment and obviously shortened the selection rounds, with near 87.2% binding just after the fourth round of selection. The aptamers A3, C1, and C5, derived from the two selection methods, were found to possess high affinity and specificity for ricin with the Kd values in the low nanomolar range, and did not recognize abrin toxin similar to ricin in the structures and properties, or BSA. Among the aptamers selected, A3 isolated by affinity chromatography shared extensive sequence similarity with C1 and C5 derived from CE-SELEX. They differed by only one base from each other. Their stable secondary structures predicted also had very similar structure motifs, and all folded a long and internal loop-embedded loop stem structure by base pairing. The ELISA and dot-blot analysis also proved that the selected DNA aptamers had the high specificity to ricin toxin.

  18. NetDiff - Bayesian model selection for differential gene regulatory network inference.

    Science.gov (United States)

    Thorne, Thomas

    2016-12-16

    Differential networks allow us to better understand the changes in cellular processes that are exhibited in conditions of interest, identifying variations in gene regulation or protein interaction between, for example, cases and controls, or in response to external stimuli. Here we present a novel methodology for the inference of differential gene regulatory networks from gene expression microarray data. Specifically we apply a Bayesian model selection approach to compare models of conserved and varying network structure, and use Gaussian graphical models to represent the network structures. We apply a variational inference approach to the learning of Gaussian graphical models of gene regulatory networks, that enables us to perform Bayesian model selection that is significantly more computationally efficient than Markov Chain Monte Carlo approaches. Our method is demonstrated to be more robust than independent analysis of data from multiple conditions when applied to synthetic network data, generating fewer false positive predictions of differential edges. We demonstrate the utility of our approach on real world gene expression microarray data by applying it to existing data from amyotrophic lateral sclerosis cases with and without mutations in C9orf72, and controls, where we are able to identify differential network interactions for further investigation.

  19. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.

    Directory of Open Access Journals (Sweden)

    Neutelings Godfrey

    2010-04-01

    Full Text Available Abstract Background Quantitative real-time PCR (qRT-PCR is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs. Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L. Results Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups. qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59. LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both ge

  20. SELECTION MOMENTS AND GENERALIZED METHOD OF MOMENTS FOR HETEROSKEDASTIC MODELS

    Directory of Open Access Journals (Sweden)

    Constantin ANGHELACHE

    2016-06-01

    Full Text Available In this paper, the authors describe the selection methods for moments and the application of the generalized moments method for the heteroskedastic models. The utility of GMM estimators is found in the study of the financial market models. The selection criteria for moments are applied for the efficient estimation of GMM for univariate time series with martingale difference errors, similar to those studied so far by Kuersteiner.

  1. Supplier selection based on multi-criterial AHP method

    Directory of Open Access Journals (Sweden)

    Jana Pócsová

    2010-03-01

    Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

  2. Methods for selective functionalization and separation of carbon nanotubes

    Science.gov (United States)

    Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

    2011-01-01

    The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

  3. Use of Maximum Likelihood-Mixed Models to select stable reference genes: a case of heat stress response in sheep

    Directory of Open Access Journals (Sweden)

    Salces Judit

    2011-08-01

    Full Text Available Abstract Background Reference genes with stable expression are required to normalize expression differences of target genes in qPCR experiments. Several procedures and companion software have been proposed to find the most stable genes. Model based procedures are attractive because they provide a solid statistical framework. NormFinder, a widely used software, uses a model based method. The pairwise comparison procedure implemented in GeNorm is a simpler procedure but one of the most extensively used. In the present work a statistical approach based in Maximum Likelihood estimation under mixed models was tested and compared with NormFinder and geNorm softwares. Sixteen candidate genes were tested in whole blood samples from control and heat stressed sheep. Results A model including gene and treatment as fixed effects, sample (animal, gene by treatment, gene by sample and treatment by sample interactions as random effects with heteroskedastic residual variance in gene by treatment levels was selected using goodness of fit and predictive ability criteria among a variety of models. Mean Square Error obtained under the selected model was used as indicator of gene expression stability. Genes top and bottom ranked by the three approaches were similar; however, notable differences for the best pair of genes selected for each method and the remaining genes of the rankings were shown. Differences among the expression values of normalized targets for each statistical approach were also found. Conclusions Optimal statistical properties of Maximum Likelihood estimation joined to mixed model flexibility allow for more accurate estimation of expression stability of genes under many different situations. Accurate selection of reference genes has a direct impact over the normalized expression values of a given target gene. This may be critical when the aim of the study is to compare expression rate differences among samples under different environmental

  4. An Improved Parallelized mRMR for Gene Subset Selection in Cancer Classification

    Directory of Open Access Journals (Sweden)

    Rohani Mohammad Kusairi

    2017-09-01

    Full Text Available DNA microarray technique has become a more attractive tool for cancer classification in the scientific and industrial fields. Based on the previous researchers, the conventional approach for cancer classification is primarily based on morphological appearance of the tumor. The limitations of this approach are bias in identify the tumors by expert and faced the difficulty in differentiate the cancer subtypes due to most cancers being highly related to the specific biological insight.  Thus, this study propose an improved parallelized Minimum Redundancy Maximum Relevance (mRMR, which is a particularly fast feature selection method for finding a set of both relevant and complementary features. The mRMR can identify genes more relevance to biological context that leads to richer biological interpretations. The proposed method is expected to achieve accurate classification performance using small number of predictive genes when tested using two datasets from Cancer Genome Project and compared to previous methods.

  5. SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis

    Directory of Open Access Journals (Sweden)

    Vulpe Chris D

    2008-03-01

    Full Text Available Abstract Background We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis. Methods We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform. Results Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the ≥ 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays. Conclusion A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.

  6. The experiments and analysis of several selective video encryption methods

    Science.gov (United States)

    Zhang, Yue; Yang, Cheng; Wang, Lei

    2013-07-01

    This paper presents four methods for selective video encryption based on the MPEG-2 video compression,including the slices, the I-frames, the motion vectors, and the DCT coefficients. We use the AES encryption method for simulation experiment for the four methods on VS2010 Platform, and compare the video effects and the processing speed of each frame after the video encrypted. The encryption depth can be arbitrarily selected, and design the encryption depth by using the double limit counting method, so the accuracy can be increased.

  7. A Molecular Selection Index Method Based on Eigenanalysis

    Science.gov (United States)

    Cerón-Rojas, J. Jesús; Castillo-González, Fernando; Sahagún-Castellanos, Jaime; Santacruz-Varela, Amalio; Benítez-Riquelme, Ignacio; Crossa, José

    2008-01-01

    The traditional molecular selection index (MSI) employed in marker-assisted selection maximizes the selection response by combining information on molecular markers linked to quantitative trait loci (QTL) and phenotypic values of the traits of the individuals of interest. This study proposes an MSI based on an eigenanalysis method (molecular eigen selection index method, MESIM), where the first eigenvector is used as a selection index criterion, and its elements determine the proportion of the trait's contribution to the selection index. This article develops the theoretical framework of MESIM. Simulation results show that the genotypic means and the expected selection response from MESIM for each trait are equal to or greater than those from the traditional MSI. When several traits are simultaneously selected, MESIM performs well for traits with relatively low heritability. The main advantages of MESIM over the traditional molecular selection index are that its statistical sampling properties are known and that it does not require economic weights and thus can be used in practical applications when all or some of the traits need to be improved simultaneously. PMID:18716338

  8. A Method for Identification of Selenoprotein Genes in Archaeal Genomes

    Institute of Scientific and Technical Information of China (English)

    Mingfeng Li; Yanzhao Huang; Yi Xiao

    2009-01-01

    The genetic codon UGA has a dual function: serving as a terminator and encoding selenocysteine. However, most popular gene annotation programs only take it as a stop signal, resulting in misannotation or completely missing selenoprotein genes. We developed a computational method named Asec-Prediction that is specific for the prediction of archaeal selenoprotein genes. To evaluate its effectiveness, we first applied it to 14 archaeal genomes with previously known selenoprotein genes, and Asec-Prediction identified all reported selenoprotein genes without redundant results. When we applied it to 12 archaeal genomes that had not been researched for selenoprotein genes, Asec-Prediction detected a novel selenoprotein gene in Methanosarcina acetivorans. Further evidence was also collected to support that the predicted gene should be a real selenoprotein gene. The result shows that Asec-Prediction is effective for the prediction of archaeal selenoprotein genes.

  9. Premise Selection for Mathematics by Corpus Analysis and Kernel Methods

    CERN Document Server

    Alama, Jesse; Tsivtsivadze, Evgeni; Urban, Josef; Heskes, Tom

    2011-01-01

    Smart premise selection is essential when using automated reasoning as a tool for large-theory formal verification, formal proof development, and experimental reverse mathematics. A strong method for premise selection in complex mathematical libraries is the application of machine learning to large corpora of proofs. This work develops learning-based premise selection in two ways. First, a newly available minimal dependency analysis of existing high-level formal mathematical proofs is used to build a large knowledge base of proof dependencies, providing new precise data for ATP-based re-verification and for training premise selection algorithms. Second, a new machine learning algorithm for premise selection based on kernel methods is proposed and implemented. To evaluate the impact of both techniques, a new benchmark consisting of 2078 large-theory mathematical problems is constructed, extending the older MPTP Challenge benchmark. The combined effect of the both techniques developed shows 40% improvement on t...

  10. GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest

    Directory of Open Access Journals (Sweden)

    Diaz-Uriarte Ramón

    2007-09-01

    Full Text Available Abstract Background Microarray data are often used for patient classification and gene selection. An appropriate tool for end users and biomedical researchers should combine user friendliness with statistical rigor, including carefully avoiding selection biases and allowing analysis of multiple solutions, together with access to additional functional information of selected genes. Methodologically, such a tool would be of greater use if it incorporates state-of-the-art computational approaches and makes source code available. Results We have developed GeneSrF, a web-based tool, and varSelRF, an R package, that implement, in the context of patient classification, a validated method for selecting very small sets of genes while preserving classification accuracy. Computation is parallelized, allowing to take advantage of multicore CPUs and clusters of workstations. Output includes bootstrapped estimates of prediction error rate, and assessments of the stability of the solutions. Clickable tables link to additional information for each gene (GO terms, PubMed citations, KEGG pathways, and output can be sent to PaLS for examination of PubMed references, GO terms, KEGG and and Reactome pathways characteristic of sets of genes selected for class prediction. The full source code is available, allowing to extend the software. The web-based application is available from http://genesrf2.bioinfo.cnio.es. All source code is available from Bioinformatics.org or The Launchpad. The R package is also available from CRAN. Conclusion varSelRF and GeneSrF implement a validated method for gene selection including bootstrap estimates of classification error rate. They are valuable tools for applied biomedical researchers, specially for exploratory work with microarray data. Because of the underlying technology used (combination of parallelization with web-based application they are also of methodological interest to bioinformaticians and biostatisticians.

  11. Use of the pyrG gene as a food-grade selection marker in Monascus.

    Science.gov (United States)

    Wang, Bo-hua; Xu, Yang; Li, Yan-ping

    2010-11-01

    Ma-pyrG was cloned from Monascus aurantiacus AS3.4384 using degenerate PCR with primers designed with an algorithm called CODEHOP, and its complete sequence was obtained by a PCR-based strategy for screening a Monascus fosmid library. Ma-pyrG encodes orotidine-5'-phosphate decarboxylase (OMPdecase), a 283-aminoacid protein with 81% sequence identity to that from Aspergillus flavus NRRL 3357. A pyrG mutant strain from M. aurantiacus AS3.4384, named UM28, was isolated by resistance to 5-fluoroorotic acid after UV mutagenesis. Sequence analysis of this mutated gene revealed that it contained a point mutation at nucleotide position +220. Plasmid pGFP-pyrG, bearing the green fluorescent protein gene (GFP) as a model gene and Ma-pyrG as a selection marker, were constructed. pGFP-pyrG were successfully transformed into UM28 by using the PEG method.

  12. Using MACBETH method for supplier selection in manufacturing environment

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2013-04-01

    Full Text Available Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

  13. Channel selection methods for the P300 Speller.

    Science.gov (United States)

    Colwell, K A; Ryan, D B; Throckmorton, C S; Sellers, E W; Collins, L M

    2014-07-30

    The P300 Speller brain-computer interface (BCI) allows a user to communicate without muscle activity by reading electrical signals on the scalp via electroencephalogram. Modern BCI systems use multiple electrodes ("channels") to collect data, which has been shown to improve speller accuracy; however, system cost and setup time can increase substantially with the number of channels in use, so it is in the user's interest to use a channel set of modest size. This constraint increases the importance of using an effective channel set, but current systems typically utilize the same channel montage for each user. We examine the effect of active channel selection for individuals on speller performance, using generalized standard feature-selection methods, and present a new channel selection method, termed jumpwise regression, that extends the Stepwise Linear Discriminant Analysis classifier. Simulating the selections of each method on real P300 Speller data, we obtain results demonstrating that active channel selection can improve speller accuracy for most users relative to a standard channel set, with particular benefit for users who experience low performance using the standard set. Of the methods tested, jumpwise regression offers accuracy gains similar to the best-performing feature-selection methods, and is robust enough for online use. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

    Science.gov (United States)

    Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

    2009-01-01

    Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

  15. Dual selection mechanisms drive efficient single-gene reverse genetics for rotavirus

    OpenAIRE

    Trask, Shane D.; Taraporewala, Zenobia F.; Boehme, Karl W.; Dermody, Terence S.; Patton, John T.

    2010-01-01

    Current methods for engineering the segmented double-stranded RNA genome of rotavirus (RV) are limited by inefficient recovery of the recombinant virus. In an effort to expand the utility of RV reverse genetics, we developed a method to recover recombinant viruses in which independent selection strategies are used to engineer single-gene replacements. We coupled a mutant SA11 RV encoding a temperature-sensitive (ts) defect in the NSP2 protein with RNAi-mediated degradation of NSP2 mRNAs to is...

  16. A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

    Directory of Open Access Journals (Sweden)

    Qihua Tan

    2009-01-01

    Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

  17. The xylose isomerase gene from Thermoanaerobacterium thermosulfurogenes allows effective selection of transgenic plant cells using D-xylose as the selection agent.

    Science.gov (United States)

    Haldrup, A; Petersen, S G; Okkels, F T

    1998-05-01

    The xylose isomerase gene (xylA) from Thermoanaerobacterium thermosulfurogenes (formerly Clostridium thermosulfurogenes) has been expressed in three plant species (potato, tobacco, and tomato) and transgenic plants have been selected on xylose-containing medium. The xylose isomerase gene was transferred to the target plant by Agrobacterium-mediated transformation. The xylose isomerase gene was expressed using the enhanced cauliflower mosaic virus (CaMV) 35S promoter and the omega' translation enhancer sequence from tobacco mosaic virus. Unoptimized selection studies showed that, in potato and tomato, the xylose isomerase selection was more efficient than the established kanamycin resistance selection, whereas in tobacco the opposite was observed. Efficiency may be increased by optimization. The xylose isomerase system enables the transgenic cells to utilize xylose as a carbohydrate source. It is an example of a positive selection system because transgenic cells proliferate while non-transgenic cells are starved but still survive. This contrasts to antibiotic or herbicide resistance where transgenic cells survive on a selective medium but non-transgenic cells are killed. The results give access to a new selection method which is devoid of the disadvantages of antibiotic or herbicide selection.

  18. Evidence for negative selection on the gene encoding rhoptry-associated protein 1 (RAP-1) in Plasmodium spp.

    Science.gov (United States)

    Pacheco, M Andreína; Ryan, Elizabeth M; Poe, Amanda C; Basco, Leonardo; Udhayakumar, Venkatachalam; Collins, Williams E; Escalante, Ananias A

    2010-07-01

    Assessing how natural selection, negative or positive, operates on genes with low polymorphism is challenging. We investigated the genetic diversity of orthologous genes encoding the rhoptry-associated protein 1 (RAP-1), a low polymorphic protein of malarial parasites that is involved in erythrocyte invasion. We applied evolutionary genetic methods to study the polymorphism in RAP-1 from Plasmodium falciparum (n=32) and Plasmodium vivax (n=6), the two parasites responsible for most human malaria morbidity and mortality, as well as RAP-1 orthologous in closely related malarial species found in non-human primates (NHPs). Overall, genes encoding RAP-1 are highly conserved in all Plasmodium spp. included in this investigation. We found no evidence for natural selection, positive or negative, acting on the gene encoding RAP-1 in P. falciparum or P. vivax. However, we found evidence that the orthologous genes in non-human primate parasites (Plasmodium cynomolgi, Plasmodium inui, and Plasmodium knowlesi) are under purifying (negative) selection. We discuss the importance of considering negative selection while studying genes encoding proteins with low polymorphism and how selective pressures may differ among orthologous genes in closely related malarial parasites species. Copyright 2010 Elsevier B.V. All rights reserved.

  19. Flexible metabolic pathway construction using modular and divisible selection gene regulators.

    Science.gov (United States)

    Rugbjerg, Peter; Myling-Petersen, Nils; Sommer, Morten O A

    2015-09-01

    Genetic selections are important to biological engineering. Although selectable traits are limited, currently each trait only permits simultaneous introduction of a single DNA fragment. Complex pathway and strain construction however depends on rapid, combinatorial introduction of many genes that encode putative pathway candidates and homologs. To triple the utility of existing selection genes, we have developed divisible selection in Saccharomyces cerevisiae. Here, independent DNA fragments can be introduced and selected for simultaneously using a set of split hybrid transcription factors composed of parts from Escherichia coli LexA and Herpes simplex VP16 to regulate one single selectable phenotype of choice. Only when co-expressed, these split hybrid transcription factors promote transcription of a selection gene, causing tight selection of transformants containing all desired DNA fragments. Upon transformation, 94% of the selected colonies resulted strictly from transforming all three modules based on ARS/CEN plasmids. Similarly when used for chromosome integration, 95% of the transformants contained all three modules. The divisible selection system acts dominantly and thus expands selection gene utility from one to three without any genomic pre-modifications of the strain. We demonstrate the approach by introducing the fungal rubrofusarin polyketide pathway at a gene load of 11 kb distributed on three different plasmids, using a single selection trait and one yeast transformation step. By tripling the utility of existing selection genes, the employment of divisible selection improves flexibility and freedom in the strain engineering process.

  20. Method for production of sorghum hybrids with selected flowering times

    Science.gov (United States)

    Mullet, John E.; Rooney, William L.

    2016-08-30

    Methods and composition for the production of sorghum hybrids with selected and different flowering times are provided. In accordance with the invention, a substantially continual and high-yield harvest of sorghum is provided. Improved methods of seed production are also provided.

  1. A Method for Severely Constrained Item Selection in Adaptive Testing.

    Science.gov (United States)

    Stocking, Martha L.; Swanson, Len

    1993-01-01

    A method is presented for incorporating a large number of constraints on adaptive item selection in the construction of computerized adaptive tests. The method, which emulates practices of expert test specialists, is illustrated for verbal and quantitative measures. Its foundation is application of a weighted deviations model and algorithm. (SLD)

  2. Method for production of sorghum hybrids with selected flowering times

    Energy Technology Data Exchange (ETDEWEB)

    Mullet, John E.; Rooney, William L.

    2016-08-30

    Methods and composition for the production of sorghum hybrids with selected and different flowering times are provided. In accordance with the invention, a substantially continual and high-yield harvest of sorghum is provided. Improved methods of seed production are also provided.

  3. Some selected quantitative methods of thermal image analysis in Matlab.

    Science.gov (United States)

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image.

  4. Selectivity in analytical chemistry: two interpretations for univariate methods.

    Science.gov (United States)

    Dorkó, Zsanett; Verbić, Tatjana; Horvai, George

    2015-01-01

    Selectivity is extremely important in analytical chemistry but its definition is elusive despite continued efforts by professional organizations and individual scientists. This paper shows that the existing selectivity concepts for univariate analytical methods broadly fall in two classes: selectivity concepts based on measurement error and concepts based on response surfaces (the response surface being the 3D plot of the univariate signal as a function of analyte and interferent concentration, respectively). The strengths and weaknesses of the different definitions are analyzed and contradictions between them unveiled. The error based selectivity is very general and very safe but its application to a range of samples (as opposed to a single sample) requires the knowledge of some constraint about the possible sample compositions. The selectivity concepts based on the response surface are easily applied to linear response surfaces but may lead to difficulties and counterintuitive results when applied to nonlinear response surfaces. A particular advantage of this class of selectivity is that with linear response surfaces it can provide a concentration independent measure of selectivity. In contrast, the error based selectivity concept allows only yes/no type decision about selectivity.

  5. Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

    Science.gov (United States)

    Chaharsooghi, S K; Ashrafi, Mehdi

    2014-01-01

    Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

  6. Selection of construction methods: a knowledge-based approach.

    Science.gov (United States)

    Ferrada, Ximena; Serpell, Alfredo; Skibniewski, Miroslaw

    2013-01-01

    The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects.

  7. Constructing Minimal Spanning Tree Based on Rough Set Theory for Gene Selection

    Directory of Open Access Journals (Sweden)

    Soumen Kumar Pati

    2013-02-01

    Full Text Available Microarray gene dataset often contains high dimensionalities which cause difficulty in clustering andclassification. Datasets containing huge number of genes lead to increased complexity and therefore,degradation of dataset handling performance. Often, all the measured features of these high-dimensionaldatasets are not relevant for understanding the underlying phenomena of interest. Dimensionality reductionby reduct generation is hence performed as an important step before clustering and classification. Thereduced attribute set has the same characteristics as the entire set of attributes in the information system.In this paper, a new attribute reduction technique, based on directed minimal spanning tree and rough settheory is done, for unsupervised learning. The method, firstly, computes a similarity factor between eachpair of attributes using indiscernibility relation, a concept of rough set theory. Based on the similarityfactors, an attribute similarity set is formed from which a directed weighted graph with vertices asattributes and edge weights as the inverse of the similarity factor is constructed. Then, all possible minimalspanning trees of the graph are generated. From each tree, iteratively, the most important vertex isincluded in the reduct set and all its out-going edges are removed. The process stops when the edge set isempty, thus producing multiple reducts. The proposed method and some well-known attribute reductiontechniques have been applied on several microarray gene datasets for gene selection. The results obtainedshow the effectiveness of the method.

  8. Constructing Minimal Spanning Tree Based on Rough Set Theory for Gene Selection

    Directory of Open Access Journals (Sweden)

    Soumen Kumar Pati

    2012-11-01

    Full Text Available Microarray gene dataset often contains high dimensionalities which cause difficulty in clustering and classification. Datasets containing huge number of genes lead to increased complexity and therefore, degradation of dataset handling performance. Often, all the measured features of these high-dimensional datasets are not relevant for understanding the underlying phenomena of interest. Dimensionality reduction by reduct generation is hence performed as an important step before clustering and classification. The reduced attribute set has the same characteristics as the entire set of attributes in the information system. In this paper, a new attribute reduction technique, based on directed minimal spanning tree and rough set theory is done, for unsupervised learning. The method, firstly, computes a similarity factor between each pair of attributes using indiscernibility relation, a concept of rough set theory. Based on the similarity factors, an attribute similarity set is formed from which a directed weighted graph with vertices as attributes and edge weights as the inverse of the similarity factor is constructed. Then, all possible minimal spanning trees of the graph are generated. From each tree, iteratively, the most important vertex is included in the reduct set and all its out-going edges are removed. The process stops when the edge set is empty, thus producing multiple reducts. The proposed method and some well-known attribute reduction techniques have been applied on several microarray gene datasets for gene selection. The results obtained show the effectiveness of the method.

  9. CONSTRUCTING MINIMAL SPANNING TREE BASED ON ROUGH SET THEORY FOR GENE SELECTION

    Directory of Open Access Journals (Sweden)

    Soumen Kumar Pati

    2013-01-01

    Full Text Available Microarray gene dataset often contains high dimensionalities which cause difficulty in clustering and classification. Datasets containing huge number of genes lead to increased complexity and therefore, degradation of dataset handling performance. Often, all the measured features of these high-dimensional datasets are not relevant for understanding the underlying phenomena of interest. Dimensionality reduction by reduct generation is hence performed as an important step before clustering and classification. The reduced attribute set has the same characteristics as the entire set of attributes in the information system. In this paper, a new attribute reduction technique, based on directed minimal spanning tree and rough set theory is done, for unsupervised learning. The method, firstly, computes a similarity factor between each pair of attributes using indiscernibility relation, a concept of rough set theory. Based on the similarity factors, an attribute similarity set is formed from which a directed weighted graph with vertices as attributes and edge weights as the inverse of the similarity factor is constructed. Then, all possible minimal spanning trees of the graph are generated. From each tree, iteratively, the most important vertex is included in the reduct set and all its out-going edges are removed. The process stops when the edge set is empty, thus producing multiple reducts. The proposed method and some well-known attribute reduction techniques have been applied on several microarray gene datasets for gene selection. The results obtained show the effectiveness of the method.

  10. A simple and efficient algorithm for gene selection using sparse logistic regression.

    Science.gov (United States)

    Shevade, S K; Keerthi, S S

    2003-11-22

    This paper gives a new and efficient algorithm for the sparse logistic regression problem. The proposed algorithm is based on the Gauss-Seidel method and is asymptotically convergent. It is simple and extremely easy to implement; it neither uses any sophisticated mathematical programming software nor needs any matrix operations. It can be applied to a variety of real-world problems like identifying marker genes and building a classifier in the context of cancer diagnosis using microarray data. The gene selection method suggested in this paper is demonstrated on two real-world data sets and the results were found to be consistent with the literature. The implementation of this algorithm is available at the site http://guppy.mpe.nus.edu.sg/~mpessk/SparseLOGREG.shtml Supplementary material is available at the site http://guppy.mpe.nus.edu.sg/~mpessk/SparseLOGREG.shtml

  11. Flexible metabolic pathway construction using modular and divisible selection gene regulators

    DEFF Research Database (Denmark)

    Rugbjerg, Peter; Myling-Petersen, Nils; Sommer, Morten Otto Alexander

    2015-01-01

    Genetic selections are important to biological engineering. Although selectable traits are limited,currently each trait only permits simultaneous introduction of a single DNA fragment. Complex pathwayand strain construction however depends on rapid, combinatorial introduction of many genes...

  12. A novel fuzzy set based multifactor dimensionality reduction method for detecting gene-gene interaction.

    Science.gov (United States)

    Jung, Hye-Young; Leem, Sangseob; Lee, Sungyoung; Park, Taesung

    2016-12-01

    Gene-gene interaction (GGI) is one of the most popular approaches for finding the missing heritability of common complex traits in genetic association studies. The multifactor dimensionality reduction (MDR) method has been widely studied for detecting GGIs. In order to identify the best interaction model associated with disease susceptibility, MDR compares all possible genotype combinations in terms of their predictability of disease status from a simple binary high(H) and low(L) risk classification. However, this simple binary classification does not reflect the uncertainty of H/L classification. We regard classifying H/L as equivalent to defining the degree of membership of two risk groups H/L. By adopting the fuzzy set theory, we propose Fuzzy MDR which takes into account the uncertainty of H/L classification. Fuzzy MDR allows the possibility of partial membership of H/L through a membership function which transforms the degree of uncertainty into a [0,1] scale. The best genotype combinations can be selected which maximizes a new fuzzy set based accuracy measure. Two simulation studies are conducted to compare the power of the proposed Fuzzy MDR with that of MDR. Our results show that Fuzzy MDR has higher power than MDR. We illustrate the proposed Fuzzy MDR by analysing bipolar disorder (BD) trait of the WTCCC dataset to detect GGI associated with BD. We propose a novel Fuzzy MDR method to detect gene-gene interaction by taking into account the uncertainly of H/L classification and show that it has higher power than MDR. Fuzzy MDR can be easily extended to handle continuous phenotypes as well. The program written in R for the proposed Fuzzy MDR is available at https://statgen.snu.ac.kr/software/FuzzyMDR. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Random frog: an efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification.

    Science.gov (United States)

    Li, Hong-Dong; Xu, Qing-Song; Liang, Yi-Zeng

    2012-08-31

    The identification of disease-relevant genes represents a challenge in microarray-based disease diagnosis where the sample size is often limited. Among established methods, reversible jump Markov Chain Monte Carlo (RJMCMC) methods have proven to be quite promising for variable selection. However, the design and application of an RJMCMC algorithm requires, for example, special criteria for prior distributions. Also, the simulation from joint posterior distributions of models is computationally extensive, and may even be mathematically intractable. These disadvantages may limit the applications of RJMCMC algorithms. Therefore, the development of algorithms that possess the advantages of RJMCMC methods and are also efficient and easy to follow for selecting disease-associated genes is required. Here we report a RJMCMC-like method, called random frog that possesses the advantages of RJMCMC methods and is much easier to implement. Using the colon and the estrogen gene expression datasets, we show that random frog is effective in identifying discriminating genes. The top 2 ranked genes for colon and estrogen are Z50753, U00968, and Y10871_at, Z22536_at, respectively. (The source codes with GNU General Public License Version 2.0 are freely available to non-commercial users at: http://code.google.com/p/randomfrog/.).

  14. Application of Participatory Method to Selection of Project Demonstration Area

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The Sino-Japan cooperation project of "Vegetation Rehabilitation Demonstration and Planning in Sandstorm Jeopardized Area around Beijing" introduced participatory method to select the project area. Through investigating the socioeconomic indicators of 9 villages in Beijing and Hebei Province as well as the farmers’ willingness to participate in forestry operation activities, the vegetation restoration demonstration areas were selected, including Hantai Village, Baicaowa Village and Xiabachi Village, respect...

  15. Methods for model selection in applied science and engineering.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  16. Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

    Science.gov (United States)

    Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

    2016-01-01

    Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

  17. Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae).

    Science.gov (United States)

    Piron Prunier, Florence; Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

    2016-01-01

    Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms.

  18. Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Sapna Kumari

    Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

  19. Contrasted patterns of selective pressure in three recent paralogous gene pairs in the Medicago genus (L.

    Directory of Open Access Journals (Sweden)

    Ho-Huu Joan

    2012-10-01

    Full Text Available Abstract Background Gene duplications are a molecular mechanism potentially mediating generation of functional novelty. However, the probabilities of maintenance and functional divergence of duplicated genes are shaped by selective pressures acting on gene copies immediately after the duplication event. The ratio of non-synonymous to synonymous substitution rates in protein-coding sequences provides a means to investigate selective pressures based on genic sequences. Three molecular signatures can reveal early stages of functional divergence between gene copies: change in the level of purifying selection between paralogous genes, occurrence of positive selection, and transient relaxed purifying selection following gene duplication. We studied three pairs of genes that are known to be involved in an interaction with symbiotic bacteria and were recently duplicated in the history of the Medicago genus (Fabaceae. We sequenced two pairs of polygalacturonase genes (Pg11-Pg3 and Pg11a-Pg11c and one pair of auxine transporter-like genes (Lax2-Lax4 in 17 species belonging to the Medicago genus, and sought for molecular signatures of differentiation between copies. Results Selective histories revealed by these three signatures of molecular differentiation were found to be markedly different between each pair of paralogs. We found sites under positive selection in the Pg11 paralogs while Pg3 has mainly evolved under purifying selection. The most recent paralogs examined Pg11a and Pg11c, are both undergoing positive selection and might be acquiring new functions. Lax2 and Lax4 paralogs are both under strong purifying selection, but still underwent a temporary relaxation of purifying selection immediately after duplication. Conclusions This study illustrates the variety of selective pressures undergone by duplicated genes and the effect of age of the duplication. We found that relaxation of selective constraints immediately after duplication might promote

  20. Personalized chemotherapy selection for breast cancer using gene expression profiles

    Science.gov (United States)

    Yu, Kaixian; Sang, Qing-Xiang Amy; Lung, Pei-Yau; Tan, Winston; Lively, Ty; Sheffield, Cedric; Bou-Dargham, Mayassa J.; Liu, Jun S.; Zhang, Jinfeng

    2017-01-01

    Choosing the optimal chemotherapy regimen is still an unmet medical need for breast cancer patients. In this study, we reanalyzed data from seven independent data sets with totally 1079 breast cancer patients. The patients were treated with three different types of commonly used neoadjuvant chemotherapies: anthracycline alone, anthracycline plus paclitaxel, and anthracycline plus docetaxel. We developed random forest models with variable selection using both genetic and clinical variables to predict the response of a patient using pCR (pathological complete response) as the measure of response. The models were then used to reassign an optimal regimen to each patient to maximize the chance of pCR. An independent validation was performed where each independent study was left out during model building and later used for validation. The expected pCR rates of our method are significantly higher than the rates of the best treatments for all the seven independent studies. A validation study on 21 breast cancer cell lines showed that our prediction agrees with their drug-sensitivity profiles. In conclusion, the new strategy, called PRES (Personalized REgimen Selection), may significantly increase response rates for breast cancer patients, especially those with HER2 and ER negative tumors, who will receive one of the widely-accepted chemotherapy regimens. PMID:28256629

  1. Ageing Drosophila selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete

      We have investigated how the gene-expression profile of longevity selected lines of Drosophila melanogaster differed from control lines in young, middle-aged and old male flies. 530 genes were differentially expressed between selected and control flies at the same chronological age. We used...... these genes in an analysis of hierarchical clustering of lines and age groups. The results showed that longevity selected flies consistently clustered with control flies that were one age class younger. Most of the genes that were upregulated in old longevity selected flies compared to control flies of equal...... chronological age were downregulated with age in both control and longevity lines. This is in accordance with a younger gene expression profile of longevity selected lines. Similarly genes that were downregulated in old longevity flies compared to control flies were upregulated with older age in both control...

  2. A mixed model reduction method for preserving selected physical information

    Science.gov (United States)

    Zhang, Jing; Zheng, Gangtie

    2017-03-01

    A new model reduction method in the frequency domain is presented. By mixedly using the model reduction techniques from both the time domain and the frequency domain, the dynamic model is condensed to selected physical coordinates, and the contribution of slave degrees of freedom is taken as a modification to the model in the form of effective modal mass of virtually constrained modes. The reduced model can preserve the physical information related to the selected physical coordinates such as physical parameters and physical space positions of corresponding structure components. For the cases of non-classical damping, the method is extended to the model reduction in the state space but still only contains the selected physical coordinates. Numerical results are presented to validate the method and show the effectiveness of the model reduction.

  3. Ground Fault Line Selection with Improved Residual Flow Incremental Method

    Directory of Open Access Journals (Sweden)

    Wenhong Li

    2013-08-01

    Full Text Available According to the shortcoming of single-phase ground fault line selection method in the resonant grounded system such as the uncertainty of its device by fast compensation with the automatic compensation equipment, an arc suppression and residual flow incremental method is proposed to effectively choose the earth fault line. Firstly, when the single-phase ground fault occurs, the arc suppression coil parameters are adjusted to realize compensation and arc suppression. Then the arc suppression coil inductance values are modulated to make the zero-sequence current of fault line changed, at the same time, the zero-sequence current value is detected and its change will be captured to select the fault line. The simulation experiments prove that the arc grounding over voltage damage can be effectively reduced by arc suppression coil full compensation and fault line can be effectively selected by arc suppression and residual flow increment method.

  4. Standard methods for rearing and selection of Apis mellifera queens

    DEFF Research Database (Denmark)

    Büchler, Ralph; Andonov, Sreten; Bienefeld, Kaspar;

    2013-01-01

    Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques...... methods and data preconditions for the estimation of breeding values which integrate pedigree and performance data from as many colonies as possible are described as the most efficient selection method for large populations. Alternative breeding programmes for small populations or certain scientific...... and quality control of queens complete the queen rearing section. The improvement of colony traits usually depends on a comparative testing of colonies. Standardized recommendations for the organization of performance tests and the measurement of the most common selection characters are presented. Statistical...

  5. Selection of Supplier by Using Saw and Vikor Methods

    Directory of Open Access Journals (Sweden)

    P.Venkateswarlu

    2016-09-01

    Full Text Available Now a days, Lean manufacturing becomes a key strategy for global competition. In this environment the most important process is the efficient selection of suppliers. In any organization various criteria such as quality, cost, location etc are used for the selection of supplier which plays a vital role in the industry. In the present work multi criteria decision making (MCDM methods are used such as SAW method and VIKOR method. It is used to select the best supplier for implementing the spring manufacturing industry. Choice of the efficient supplier could be a complicated and is a complex problem and this draw back associate degreed a key success for an organization. In this paper linguistic fuzzy data is used to search out the ratings and weights and also the introduced methodologies employed to pick the efficient supplier.

  6. Selective gene expression by postnatal electroporation during olfactory interneuron neurogenesis.

    Directory of Open Access Journals (Sweden)

    Alexander T Chesler

    Full Text Available Neurogenesis persists in the olfactory system throughout life. The mechanisms of how new neurons are generated, how they integrate into circuits, and their role in coding remain mysteries. Here we report a technique that will greatly facilitate research into these questions. We found that electroporation can be used to robustly and selectively label progenitors in the Subventicular Zone. The approach was performed postnatally, without surgery, and with near 100% success rates. Labeling was found in all classes of interneurons in the olfactory bulb, persisted to adulthood and had no adverse effects. The broad utility of electroporation was demonstrated by encoding a calcium sensor and markers of intracellular organelles. The approach was found to be effective in wildtype and transgenic mice as well as rats. Given its versatility, robustness, and both time and cost effectiveness, this method offers a powerful new way to use genetic manipulation to understand adult neurogenesis.

  7. A selective HPLC method for determination of lercanidipine in tablets.

    Science.gov (United States)

    Alvarez-Lueje, A; Pujol, S; Squella, J A; Núñez-Vergara, L J

    2003-02-05

    An HPLC reversed phase method using both UV (356 nm) and electrochemical (1000 mV) detection was developed in order to determine lercanidipine in commercial tablets. Repeatability and reproducibility were adequate. For quantification we have used the calibration plot method for lercanidipine concentration ranging between 1 x 10(-5) and 1 x 10(-4) M. Also, the proposed method is sufficiently selective to distinguish the parent drug and the degradation products after hydrolysis, photolysis or chemical oxidation. Furthermore, the typical excipients included in the drug formulation (talc, lactose, cornstarch, microcrystalline cellulose, carboxymethylcellulose and magnesium stearate) do not interfere with the selectivity of the method. Finally, the proposed chromatographic method was successfully applied to the quantitative determination of lercanidipine in commercial tablets.

  8. Computational method for discovery of estrogen responsive genes

    DEFF Research Database (Denmark)

    Tang, Suisheng; Tan, Sin Lam; Ramadoss, Suresh Kumar;

    2004-01-01

    Estrogen has a profound impact on human physiology and affects numerous genes. The classical estrogen reaction is mediated by its receptors (ERs), which bind to the estrogen response elements (EREs) in target gene's promoter region. Due to tedious and expensive experiments, a limited number...... of human genes are functionally well characterized. It is still unclear how many and which human genes respond to estrogen treatment. We propose a simple, economic, yet effective computational method to predict a subclass of estrogen responsive genes. Our method relies on the similarity of ERE frames...... across different promoters in the human genome. Matching ERE frames of a test set of 60 known estrogen responsive genes to the collection of over 18,000 human promoters, we obtained 604 candidate genes. Evaluating our result by comparison with the published microarray data and literature, we found...

  9. A high efficiency gene disruption strategy using a positive-negative split selection marker and electroporation for Fusarium oxysporum.

    Science.gov (United States)

    Liang, Liqin; Li, Jianqiang; Cheng, Lin; Ling, Jian; Luo, Zhongqin; Bai, Miao; Xie, Bingyan

    2014-11-01

    The Fusarium oxysporum species complex consists of fungal pathogens that cause serial vascular wilt disease on more than 100 cultivated species throughout the world. Gene function analysis is rapidly becoming more and more important as the whole-genome sequences of various F. oxysporum strains are being completed. Gene-disruption techniques are a common molecular tool for studying gene function, yet are often a limiting step in gene function identification. In this study we have developed a F. oxysporum high-efficiency gene-disruption strategy based on split-marker homologous recombination cassettes with dual selection and electroporation transformation. The method was efficiently used to delete three RNA-dependent RNA polymerase (RdRP) genes. The gene-disruption cassettes of three genes can be constructed simultaneously within a short time using this technique. The optimal condition for electroporation is 10μF capacitance, 300Ω resistance, 4kV/cm field strength, with 1μg of DNA (gene-disruption cassettes). Under these optimal conditions, we were able to obtain 95 transformants per μg DNA. And after positive-negative selection, the transformants were efficiently screened by PCR, screening efficiency averaged 85%: 90% (RdRP1), 85% (RdRP2) and 77% (RdRP3). This gene-disruption strategy should pave the way for high throughout genetic analysis in F. oxysporum. Copyright © 2014 Elsevier GmbH. All rights reserved.

  10. Standard methods for rearing and selection of Apis mellifera queens

    DEFF Research Database (Denmark)

    Büchler, Ralph; Andonov, Sreten; Bienefeld, Kaspar

    2013-01-01

    and quality control of queens complete the queen rearing section. The improvement of colony traits usually depends on a comparative testing of colonies. Standardized recommendations for the organization of performance tests and the measurement of the most common selection characters are presented. Statistical...... methods and data preconditions for the estimation of breeding values which integrate pedigree and performance data from as many colonies as possible are described as the most efficient selection method for large populations. Alternative breeding programmes for small populations or certain scientific...

  11. A selection method of the horizontal wells completion

    Directory of Open Access Journals (Sweden)

    Ivica Ristović

    2006-10-01

    Full Text Available The completion of horizontal wells can be done by different ways and depends on production constraints and the reservoir characteristics.The selection of a completon method is directly influenced by the degree of rock consolidation, the need for water or gas shut off,the anticipated flow rate, the completion longevity, the shale reactivity and the stability, the degree of grain sorting and the lamination.In this article, the possible methods for the horizontal well completion are shown. Also, it is presented the horizontal well completion selection flowchart. This algorithm is made on the basis of a large number of wells’ analysis considering reservoir characteristics and production constraints.

  12. AccelKey Selection Method for Mobile Devices

    CERN Document Server

    Zaliva, Vadim

    2007-01-01

    Portable Electronic Devices usually utilize a small screen with limited viewing area and a keyboard with a limited number of keys. This makes it difficult to perform quick searches in data arrays containing more than dozen items such an address book or song list. In this article we present a new data selection method which allows the user to quickly select an entry from a list using 4-way navigation device such as joystick, trackball or 4-way key pad. This method allows for quick navigation using just one hand, without looking at the screen.

  13. Method for Selection of Solvents for Promotion of Organic Reactions

    DEFF Research Database (Denmark)

    Gani, Rafiqul; Jiménez-González, Concepción; Constable, David J.C.

    2005-01-01

    A method to select appropriate green solvents for the promotion of a class of organic reactions has been developed. The method combines knowledge from industrial practice and physical insights with computer-aided property estimation tools for selection/design of solvents. In particular, it employs...... is to produce, for a given reaction, a short list of chemicals that could be considered as potential solvents, to evaluate their performance in the reacting system, and, based on this, to rank them according to a scoring system. Several examples of application are given to illustrate the main features and steps...

  14. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Directory of Open Access Journals (Sweden)

    Anna Tóth

    Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  15. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Science.gov (United States)

    Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

    2014-01-01

    Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  16. Selection and validation of appropriate reference genes for quantitative real-time PCR analysis of gene expression in Lycoris aurea

    Directory of Open Access Journals (Sweden)

    Rui eMa

    2016-04-01

    Full Text Available Lycoris aurea (L' Hér. Herb, a perennial grass species, produces a unique variety of pharmacologically active Amaryllidaceae alkaloids. However, the key enzymes and their expression pattern involved in the biosynthesis of Amaryllidaceae alkaloids (especially for galanthamine are far from being fully understood. Quantitative real-time polymerase chain reaction (qRT-PCR, a commonly used method for quantifying gene expression, requires stable reference genes to normalize its data. In this study, to choose the appropriate reference genes under different experimental conditions, 14 genes including YLS8 (mitosis protein YLS8, CYP2 (Cyclophilin 2, CYP 1 (Cyclophilin 1, TIP41 (TIP41-like protein, EXP2 (Expressed protein 2, PTBP1 (Polypyrimidine tract-binding protein 1, EXP1 (Expressed protein 1, PP2A (Serine/threonine-protein phosphatase 2A, β-TUB (β-tubulin, α-TUB (α-tubulin, EF1-α (Elongation factor 1-α, UBC (Ubiquitin-conjugating enzyme, ACT (Actin and GAPDH (Glyceraldehyde 3-phosphate dehydrogenase were selected from the transcriptome datasets of L. aurea. And then, expressions of these genes were assessed by qRT-PCR in various tissues and the roots under different treatments. The expression stability of the 14 candidates was analyzed by three commonly used software programs (geNorm, NormFinder, and BestKeeper, and their results were further integrated into a comprehensive ranking based on the geometric mean. The results show the relatively stable genes for each subset as follows: (1 EXP1 and TIP41 for all samples; (2 UBC and EXP1 for NaCl stress; (3 PTBP1 and EXP1 for heat stress, polyethylene glycol (PEG stress and ABA treatment; (4 UBC and CYP2 for cold stress; (5 PTBP1 and PP2A for sodium nitroprusside (SNP treatment; (6 CYP1 and TIP41 for methyl jasmonate (MeJA treatment; and (7 EXP1 and TIP41 for various tissues. The reliability of these results was further enhanced through comparison between part qRT-PCR result and RNA sequencing (RNA

  17. Ranking: a closer look on globalisation methods for normalisation of gene expression arrays

    Science.gov (United States)

    Kroll, Torsten C.; Wölfl, Stefan

    2002-01-01

    Data from gene expression arrays are influenced by many experimental parameters that lead to variations not simply accessible by standard quantification methods. To compare measurements from gene expression array experiments, quantitative data are commonly normalised using reference genes or global normalisation methods based on mean or median values. These methods are based on the assumption that (i) selected reference genes are expressed at a standard level in all experiments or (ii) that mean or median signal of expression will give a quantitative reference for each individual experiment. We introduce here a new ranking diagram, with which we can show how the different normalisation methods compare, and how they are influenced by variations in measurements (noise) that occur in every experiment. Furthermore, we show that an upper trimmed mean provides a simple and robust method for normalisation of larger sets of experiments by comparative analysis. PMID:12034851

  18. Development of Molecular Marker Linked to Cf-10 Gene Using SSR and AFLP Method in Tomato

    Institute of Scientific and Technical Information of China (English)

    Li Ning; Jiang Jing-bin; Li Jing-fu; Xu Xiang-yang

    2012-01-01

    The leaf mould resistance gene Cf-10 on tomato confered resistant or immune to all prevalent physiological races of Cladosporium fulvum presented in three northeastern provinces of China in inoculation test. In order to better utilize Cf-10 gene in a marker-assisted selection program and to permit the pyramiding of one or several resistance genes in a cultivar, tightly linked SSR and AFLP markers were obtained by the bulked segregant analysis method. One SSR marker and three AFLP markers were identified linked to Cf-10 gene, with the distance of 9.73, 5.8, 8.5, and 10.6 cM, respectively. These markers will facilitate the selection of resistant tomato germplasm containing Cf-10 gene.

  19. Selection of reference genes for quantitative PCR studies in purified B cells from B cell chronic lymphocytic leukaemia patients

    OpenAIRE

    Valceckiene, Vilma; Kontenyte, Rima; Jakubauskas, Arturas; Griskevicius, Laimonas

    2010-01-01

    Abstract Clinical heterogeneity of B-cell chronic lymphocytic leukaemia (B-CLL) makes it necessary to identify potent prognostic indicators to predict individual clinical course and select risk-adapted therapy. During the last years numerous gene expression models have been suggested as prognostic factors of B-CLL. Today quantitative polymerase chain reaction (qPCR) is a preferred method for rapid quantification of gene expression and validation of microarray data. Reliability of q...

  20. Bhargava and Ishizuka's BI-Method: A Neglected Method for Variable Selection

    Science.gov (United States)

    Leung, Shing On; Sachs, John

    2005-01-01

    Quite often in data reduction, it is more meaningful and economical to select a subset of variables instead of reducing the dimensionality of the variable space with principal components analysis. The authors present a neglected method for variable selection called the BI-method (R. P. Bhargava & T. Ishizuka, 1981). It is a direct, simple method…

  1. Selection of Construction Methods: A Knowledge-Based Approach

    Directory of Open Access Journals (Sweden)

    Ximena Ferrada

    2013-01-01

    Full Text Available The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method’ selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods’ selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects.

  2. Gene Expression Network Reconstruction by LEP Method Using Microarray Data

    Directory of Open Access Journals (Sweden)

    Na You

    2012-01-01

    Full Text Available Gene expression network reconstruction using microarray data is widely studied aiming to investigate the behavior of a gene cluster simultaneously. Under the Gaussian assumption, the conditional dependence between genes in the network is fully described by the partial correlation coefficient matrix. Due to the high dimensionality and sparsity, we utilize the LEP method to estimate it in this paper. Compared to the existing methods, the LEP reaches the highest PPV with the sensitivity controlled at the satisfactory level. A set of gene expression data from the HapMap project is analyzed for illustration.

  3. Database and selection method for portable power sources

    Energy Technology Data Exchange (ETDEWEB)

    Fu, L.; Huber, J.E. [Department of Engineering, University of Cambridge, Trumpington St., Cambridge CB2 1PZ (United Kingdom); Lu, T.J. [Department of Engineering, University of Cambridge, Trumpington St., Cambridge CB2 1PZ (United Kingdom); School of Aerospace, Xian Jiaotong University, Xian 710049 (China)

    2005-08-01

    A method for selecting power sources including batteries, fuel cells and solar cells is developed. It is based on matching the physical and performance characteristics of power sources, such as weight, volume, capacity, voltage and cost, to the requirements of the given task. Physical and performance characteristics are collated from manufacturers' data and a database is built using advanced selection software. This allows the construction of performance maps in terms of voltage, maximum current, mass energy density, volume energy density and cost, giving a systematic comparison of different kinds of power sources. The use of the method as a preliminary design tool is demonstrated in a case study on the selection of batteries for mobile phones. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

  4. Selective Integration in the Material-Point Method

    DEFF Research Database (Denmark)

    Andersen, Lars; Andersen, Søren; Damkilde, Lars

    2009-01-01

    The paper deals with stress integration in the material-point method. In order to avoid parasitic shear in bending, a formulation is proposed, based on selective integration in the background grid that is used to solve the governing equations. The suggested integration scheme is compared...... to a traditional material-point-method computation in which the stresses are evaluated at the material points. The deformation of a cantilever beam is analysed, assuming elastic or elastoplastic material behaviour....

  5. Spectrophotometric validation of assay method for selected medicinal plant extracts

    OpenAIRE

    Matthew Arhewoh; Augustine O. Okhamafe

    2014-01-01

    Objective: To develop UV spectrophotometric assay validation methods for some selected medicinal plant extracts.Methods: Dried, powdered leaves of Annona muricata (AM) and Andrographis paniculata (AP) as well as seeds of Garcinia kola (GK) and Hunteria umbellata (HU) were separately subjected to maceration using distilled water. Different concentrations of the extracts were scanned spectrophotometrically to obtain wavelengths of maximum absorbance. The different extracts were then subjected t...

  6. Statistical methods for cosmological parameter selection and estimation

    CERN Document Server

    Liddle, Andrew R

    2009-01-01

    The estimation of cosmological parameters from precision observables is an important industry with crucial ramifications for particle physics. This article discusses the statistical methods presently used in cosmological data analysis, highlighting the main assumptions and uncertainties. The topics covered are parameter estimation, model selection, multi-model inference, and experimental design, all primarily from a Bayesian perspective.

  7. Measuring balance and model selection in propensity score methods

    NARCIS (Netherlands)

    Belitser, S.; Martens, Edwin P.; Pestman, Wiebe R.; Groenwold, Rolf H.H.; De Boer, Anthonius; Klungel, Olaf H.

    2011-01-01

    Background: Propensity score (PS) methods focus on balancing confounders between groups to estimate an unbiased treatment or exposure effect. However, there is lack of attention in actually measuring, reporting and using the information on balance, for instance for model selection. Objectives: To de

  8. SELECTION OF REFERENCE PLANE BY THE LEAST SQUARES FITTING METHODS

    Directory of Open Access Journals (Sweden)

    Przemysław Podulka

    2016-06-01

    For least squares polynomial fittings it was found that applied method for cylinder liners gave usually better robustness for scratches, valleys and dimples occurrence. For piston skirt surfaces better edge-filtering results were obtained. It was also recommended to analyse the Sk parameters for proper selection of reference plane in surface topography measurements.

  9. An objective method for High Dynamic Range source content selection

    DEFF Research Database (Denmark)

    Narwaria, Manish; Mantel, Claire; Da Silva, Matthieu Perreira

    2014-01-01

    component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content. In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more...

  10. Quantitative evaluation and selection of reference genes in mouse oocytes and embryos cultured in vivo and in vitro

    Directory of Open Access Journals (Sweden)

    Dinnyes Andras

    2007-03-01

    Full Text Available Abstract Background Real-time PCR is an efficient tool to measure transcripts and provide valuable quantitative information on gene expression of preimplantation stage embryos. Finding valid reference genes for normalization is essential to interpret the real-time PCR results accurately, and understand the biological dynamics during early development. The use of reference genes also known as housekeeping genes is the most widely applied approach. However, the different genes are not systematically compared, and as a result there is no uniformity between studies in selecting the reference gene. The goals of this study were to compare a wide selection of the most commonly used housekeeping genes in mouse oocytes and preimplantation stage embryos produced under different culture conditions, and select the best stable genes for normalization of gene expression data. Results Quantitative real time PCR method was used to evaluate 12 commonly used housekeeping genes (Actb, Gapdh, H2afz, Hprt, Ppia, Ubc, Eef1e1, Tubb4, Hist2h2aa1, Tbp, Bmp7, Polr2a in multiple individual embryos representing six different developmental stages. The results were analysed, and stable genes were selected using the geNorm software. The expression pattern was almost similar despite differences in the culture system; however, the transcript levels were affected by culture conditions. The genes have showed various stabilities, and have been ranked accordingly. Conclusion Compared to earlier studies with similar objectives, we used a unique approach in analysing larger number of genes, comparing embryo samples derived in vivo or in vitro, analysing the expression in the early and late maternal to zygote transition periods separately, and using multiple individual embryos. Based on detailed quantification, pattern analyses and using the geNorm application, we found Ppia, H2afz and Hprt1 genes to be the most stable across the different stages and culture conditions, while Actb

  11. A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

    Directory of Open Access Journals (Sweden)

    Ching Lee Koo

    2013-01-01

    Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  12. Determination of Selection Method in Genetic Algorithm for Land Suitability

    Directory of Open Access Journals (Sweden)

    Irfianti Asti Dwi

    2016-01-01

    Full Text Available Genetic Algoirthm is one alternative solution in the field of modeling optimization, automatic programming and machine learning. The purpose of the study was to compare some type of selection methods in Genetic Algorithm for land suitability. Contribution of this research applies the best method to develop region based horticultural commodities. This testing is done by comparing the three methods on the method of selection, the Roulette Wheel, Tournament Selection and Stochastic Universal Sampling. Parameters of the locations used in the test scenarios include Temperature = 27°C, Rainfall = 1200 mm, hummidity = 30%, Cluster fruit = 4, Crossover Probabiitiy (Pc = 0.6, Mutation Probabilty (Pm = 0.2 and Epoch = 10. The second test epoch incluides location parameters consist of Temperature = 30°C, Rainfall = 2000 mm, Humidity = 35%, Cluster fruit = 5, Crossover Probability (Pc = 0.7, Mutation Probability (Pm = 0.3 and Epoch 10. The conclusion of this study shows that the Roulette Wheel is the best method because it produces more stable and fitness value than the other two methods.

  13. The signal selection and processing method for polarization measurement radar

    Institute of Scientific and Technical Information of China (English)

    CHANG YuLiang; WANG XueSong; LI YongZhen; XIAO ShunPing

    2009-01-01

    Based on the ambiguity function, a novel signal processing method for the polarization measurement radar is developed. One advantage of this method is that the two orthogonal polarized signals do not have to be perpendicular to each other, which is required by traditional methods. The error due to the correlation of the two transmitting signals in the traditional method, can be reduced by this new approach. A concept called ambiguity function matrix (AFM) is introduced based on this method. AFM is a promising tool for the signal selection and design in the polarization scattering matrix measurement. The waveforms of the polarimetric radar are categorized and analyzed based on AFM in this paper. The signal processing flow of this method is explained. And the polarization scattering matrix measurement performance is testified by simulation. Furthermore, this signal processing method can be used in the inter-pulse interval measurement technique as well as in the instantaneous measurement technique.

  14. Selection on protein-coding genes of natural cyanobacterial populations

    NARCIS (Netherlands)

    Mes, T.H.M.; Doeleman, M.W.; Lodders, N.; Nübel, U.; Stal, L.J.

    2006-01-01

    We examined the distribution of synonymous and non-synonymous changes in 12 protein-coding genes of natural populations of cyanobacteria to infer changes in gene functionality. By comparing mutation distributions within and across species using the McDonald–Kreitman test, we found data sets to conta

  15. Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

    Science.gov (United States)

    Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

    2017-10-02

    Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

  16. Comparative GO: a web application for comparative gene ontology and gene ontology-based gene selection in bacteria.

    Directory of Open Access Journals (Sweden)

    Mario Fruzangohar

    Full Text Available The primary means of classifying new functions for genes and proteins relies on Gene Ontology (GO, which defines genes/proteins using a controlled vocabulary in terms of their Molecular Function, Biological Process and Cellular Component. The challenge is to present this information to researchers to compare and discover patterns in multiple datasets using visually comprehensible and user-friendly statistical reports. Importantly, while there are many GO resources available for eukaryotes, there are none suitable for simultaneous, graphical and statistical comparison between multiple datasets. In addition, none of them supports comprehensive resources for bacteria. By using Streptococcus pneumoniae as a model, we identified and collected GO resources including genes, proteins, taxonomy and GO relationships from NCBI, UniProt and GO organisations. Then, we designed database tables in PostgreSQL database server and developed a Java application to extract data from source files and loaded into database automatically. We developed a PHP web application based on Model-View-Control architecture, used a specific data structure as well as current and novel algorithms to estimate GO graphs parameters. We designed different navigation and visualization methods on the graphs and integrated these into graphical reports. This tool is particularly significant when comparing GO groups between multiple samples (including those of pathogenic bacteria from different sources simultaneously. Comparing GO protein distribution among up- or down-regulated genes from different samples can improve understanding of biological pathways, and mechanism(s of infection. It can also aid in the discovery of genes associated with specific function(s for investigation as a novel vaccine or therapeutic targets.http://turing.ersa.edu.au/BacteriaGO.

  17. A Brief Review of Computational Gene Prediction Methods

    Institute of Scientific and Technical Information of China (English)

    Zhuo Wang; Yazhu Chen; Yixue Li

    2004-01-01

    With the development of genome sequencing for many organisms, more and more raw sequences need to be annotated. Gene prediction by computational methods for finding the location of protein coding regions is one of the essential issues in bioinformatics. Two classes of methods are generally adopted: similarity based searches and ab initio prediction. Here, we review the development of gene prediction methods, summarize the measures for evaluating predictor quality, highlight open problems in this area, and discuss future research directions.

  18. Selective Amplification of the Genome Surrounding Key Placental Genes in Trophoblast Giant Cells.

    Science.gov (United States)

    Hannibal, Roberta L; Baker, Julie C

    2016-01-25

    While most cells maintain a diploid state, polyploid cells exist in many organisms and are particularly prevalent within the mammalian placenta [1], where they can generate more than 900 copies of the genome [2]. Polyploidy is thought to be an efficient method of increasing the content of the genome by avoiding the costly and slow process of cytokinesis [1, 3, 4]. Polyploidy can also affect gene regulation by amplifying a subset of genomic regions required for specific cellular function [1, 3, 4]. This mechanism is found in the fruit fly Drosophila melanogaster, where polyploid ovarian follicle cells amplify genomic regions containing chorion genes, which facilitate secretion of eggshell proteins [5]. Here, we report that genomic amplification also occurs in mammals at selective regions of the genome in parietal trophoblast giant cells (p-TGCs) of the mouse placenta. Using whole-genome sequencing (WGS) and digital droplet PCR (ddPCR) of mouse p-TGCs, we identified five amplified regions, each containing a gene family known to be involved in mammalian placentation: the prolactins (two clusters), serpins, cathepsins, and the natural killer (NK)/C-type lectin (CLEC) complex [6-12]. We report here the first description of amplification at selective genomic regions in mammals and present evidence that this is an important mode of genome regulation in placental TGCs.

  19. An expert system for selecting wart treatment method.

    Science.gov (United States)

    Khozeimeh, Fahime; Alizadehsani, Roohallah; Roshanzamir, Mohamad; Khosravi, Abbas; Layegh, Pouran; Nahavandi, Saeid

    2017-02-01

    As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. There are several treatment methods for this illness. However, none of them can heal all patients. Consequently, physicians are looking for more effective and customized treatments for each patient. They are endeavoring to discover which treatments have better impacts on a particular patient. The aim of this study is to identify the appropriate treatment for two common types of warts (plantar and common) and to predict the responses of two of the best methods (immunotherapy and cryotherapy) to the treatment. As an original work, the study was conducted on 180 patients, with plantar and common warts, who had referred to the dermatology clinic of Ghaem Hospital, Mashhad, Iran. In this study, 90 patients were treated by cryotherapy method with liquid nitrogen and 90 patients with immunotherapy method. The selection of the treatment method was made randomly. A fuzzy logic rule-based system was proposed and implemented to predict the responses to the treatment method. It was observed that the prediction accuracy of immunotherapy and cryotherapy methods was 83.33% and 80.7%, respectively. According to the results obtained, the benefits of this expert system are multifold: assisting physicians in selecting the best treatment method, saving time for patients, reducing the treatment cost, and improving the quality of treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

    Directory of Open Access Journals (Sweden)

    Cohn Zachary A

    2007-06-01

    Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

  1. 利用生物信息学方法挑选MCPH1基因标签单核苷酸多态性(tag-SNPs)位点%Bioinformatics methods for selecting the MCHPH1 gene tag single nucleotide polymorphisms(tag-SNPs)sites

    Institute of Scientific and Technical Information of China (English)

    刘跃亮; 曾照芳

    2011-01-01

    目的:为考察汉族人群MCPH1基因与原发性小头畸形病的关系,利用生物信息学方法挑选汉族人群中的MCPH1基因标签单核苷酸多态性(tag-SNPs)位点。方法:利用NCBI数据库,确定MCPHl基因研究范围:利用Hapmap数据库获取汉族人群的MCPHl基因SNPs数据;应用Haploview4.2对MCPH1基因进行连锁不平衡分析;在D′值95%可信区间内构建单倍域(haplotype block):根据单倍域内SNPs之间的r2值和LOD值,挑选标签SNP。结果:在汉族人群中,MCPH1全基因范围内共构建35个单倍域,挑选出122个标签SNPs,确定了各个单倍域内的代表单倍型。结论:汉族人群MCPH1基因的122个SNPs位点是较具代表性的标志性位点,可被选为标签SNPs,并作为汉族人群MCPHl基因与原发性小头畸形病的关联研究。%Objective:Han population for the study MCPH1 primary microcephaly genes and the relationship between disease,the use of bioinformatics methods for selecting the Han population MCPH1 gene tag single nucleotide polymorphisms(tag-SNPs) sites.Methods:Using NCBI databases,to determine the scope of genetic research MCPH1;use Hapmap database for the Han population MCPH1 gene SNPs data;application Haploview4.2 MCPH1 gene on linkage disequilibrium analysis;in the D'value of the 95% confidence interval constructed single-fold domain(haplotype block);based on the single-fold within the r2 values between SNPs and the LOD value,tag SNP selection.Results:In the Han population,MCPH 1 genome were constructed within the domain of 35 haplotypes,selected 122 tag SNPs,identified representatives of the various haplotypes within haplotype.Conclusion:MCPH1 gene in Han population of 122 SNPs loci are more representative of the landmark site,can be selected as tag SNPs,Han population MCPH1 favor of primary microcephaly genes and disease association studies.

  2. A new DEA-GAHP method for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Behrooz Ahadian

    2012-10-01

    Full Text Available Supplier selection is one of the most important decisions made in supply chain management. Supplier evaluation problem has been in the center of supply chain researcher’s attention in these years. Managers regard some of these studies and methods inappropriate due to simple, weight scoring methods that generally are based on subjective opinions and judgments of decision maker units involved in the supplier evaluation process yielding imprecise and even unreliable results. This paper seeks to propose a methodology to integrate data envelopment analysis (DEA and group analytical hierarchy process (GAHP for evaluating and selecting the most efficient supplier. We develop a methodology, which consists of 6 steps, one by one has been introduced in lecture and finally applicability of proposed method is indicated by assessing 12 suppliers in a numerical example.

  3. A robust and accurate method for feature selection and prioritization from multi-class OMICs data.

    Directory of Open Access Journals (Sweden)

    Vittorio Fortino

    Full Text Available Selecting relevant features is a common task in most OMICs data analysis, where the aim is to identify a small set of key features to be used as biomarkers. To this end, two alternative but equally valid methods are mainly available, namely the univariate (filter or the multivariate (wrapper approach. The stability of the selected lists of features is an often neglected but very important requirement. If the same features are selected in multiple independent iterations, they more likely are reliable biomarkers. In this study, we developed and evaluated the performance of a novel method for feature selection and prioritization, aiming at generating robust and stable sets of features with high predictive power. The proposed method uses the fuzzy logic for a first unbiased feature selection and a Random Forest built from conditional inference trees to prioritize the candidate discriminant features. Analyzing several multi-class gene expression microarray data sets, we demonstrate that our technique provides equal or better classification performance and a greater stability as compared to other Random Forest-based feature selection methods.

  4. A copula method for modeling directional dependence of genes

    Directory of Open Access Journals (Sweden)

    Park Changyi

    2008-05-01

    Full Text Available Abstract Background Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation. Results We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex by adopting a measure of directional dependence based on a copula function. We have compared

  5. Hyperspectral image classification based on NMF Features Selection Method

    Science.gov (United States)

    Abe, Bolanle T.; Jordaan, J. A.

    2013-12-01

    Hyperspectral instruments are capable of collecting hundreds of images corresponding to wavelength channels for the same area on the earth surface. Due to the huge number of features (bands) in hyperspectral imagery, land cover classification procedures are computationally expensive and pose a problem known as the curse of dimensionality. In addition, higher correlation among contiguous bands increases the redundancy within the bands. Hence, dimension reduction of hyperspectral data is very crucial so as to obtain good classification accuracy results. This paper presents a new feature selection technique. Non-negative Matrix Factorization (NMF) algorithm is proposed to obtain reduced relevant features in the input domain of each class label. This aimed to reduce classification error and dimensionality of classification challenges. Indiana pines of the Northwest Indiana dataset is used to evaluate the performance of the proposed method through experiments of features selection and classification. The Waikato Environment for Knowledge Analysis (WEKA) data mining framework is selected as a tool to implement the classification using Support Vector Machines and Neural Network. The selected features subsets are subjected to land cover classification to investigate the performance of the classifiers and how the features size affects classification accuracy. Results obtained shows that performances of the classifiers are significant. The study makes a positive contribution to the problems of hyperspectral imagery by exploring NMF, SVMs and NN to improve classification accuracy. The performances of the classifiers are valuable for decision maker to consider tradeoffs in method accuracy versus method complexity.

  6. Selection of an optimal treatment method for acute periodontitis disease.

    Science.gov (United States)

    Aliev, Rafik A; Aliyev, B F; Gardashova, Latafat A; Huseynov, Oleg H

    2012-04-01

    The present paper is devoted to selection of an optimal treatment method for acute periodontitis by using fuzzy Choquet integral-based approach. We consider application of different treatment methods depending on development stages and symptoms of the disease. The effectiveness of application of different treatment methods in each stage of the disease is linguistically evaluated by a dentist. The stages of the disease are also linguistically described by a dentist. Dentist's linguistic evaluations are represented by fuzzy sets. The total effectiveness of the each considered treatment method is calculated by using fuzzy Choquet integral with fuzzy number-valued integrand and fuzzy number-valued fuzzy measure. The most effective treatment method is determined by using fuzzy ranking method.

  7. Methods, apparatus and system for selective duplication of subtasks

    Energy Technology Data Exchange (ETDEWEB)

    Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

    2016-03-29

    A method for selective duplication of subtasks in a high-performance computing system includes: monitoring a health status of one or more nodes in a high-performance computing system, where one or more subtasks of a parallel task execute on the one or more nodes; identifying one or more nodes as having a likelihood of failure which exceeds a first prescribed threshold; selectively duplicating the one or more subtasks that execute on the one or more nodes having a likelihood of failure which exceeds the first prescribed threshold; and notifying a messaging library that one or more subtasks were duplicated.

  8. Pyrochemical and Dry Processing Methods Program. A selected bibliography

    Energy Technology Data Exchange (ETDEWEB)

    McDuffie, H.F.; Smith, D.H.; Owen, P.T.

    1979-03-01

    This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles.

  9. BRCA1-mediated repression of select X chromosome genes

    Directory of Open Access Journals (Sweden)

    Ropers H Hilger

    2004-09-01

    Full Text Available Abstract Recently BRCA1 has been implicated in the regulation of gene expression from the X chromosome. In this study the influence of BRCA1 on expression of X chromosome genes was investigated. Complementary DNA microarrays were used to compare the expression levels of X chromosome genes in 18 BRCA1-associated ovarian cancers to those of the 13 "BRCA1-like" and 14 "BRCA2-like" sporadic tumors (as defined by previously reported expression profiling. Significance was determined using parametric statistics with P

  10. 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.

  11. Computational disease gene identification : a concert of methods prioritizes type 2 diabetes and obesity candidate genes

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most

  12. Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most

  13. Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most li

  14. Computational disease gene identification : a concert of methods prioritizes type 2 diabetes and obesity candidate genes

    NARCIS (Netherlands)

    Tiffin, N.; Adie, E.; Turner, F.; Brunner, H.G.; Driel, M.A. van; Oti, M.O.; Lopez-Bigas, N.; Ouzounis, C.A.; Perez-Iratxeta, C.; Andrade-Navarro, M.A.; Adeyemo, A.; Patti, M.E.; Semple, C.A.; Hide, W.

    2006-01-01

    Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most li

  15. 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.

  16. Selection Signatures in Four Lignin Genes from Switchgrass Populations Divergently Selected for In Vitro Dry Matter Digestibility

    Science.gov (United States)

    Kaeppler, Shawn M.; Vogel, Kenneth P.; Casler, Michael D.

    2016-01-01

    Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four loci in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. This study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality. PMID:27893787

  17. Positive selection at reproductive ADAM genes with potential intercellular binding activity.

    Science.gov (United States)

    Glassey, Barb; Civetta, Alberto

    2004-05-01

    Many genes with a role in reproduction, including those implicated in fertilization and spermatogenesis, have been shown to evolve at a faster rate relative to genes associated with other functions and tissues. These survey studies usually group a wide variety of genes with different characteristics and evolutionary histories as reproductive genes based on their site of expression or function. We have examined the molecular evolution of the ADAM (a disintegrin and metalloprotease) gene family, a structurally and functionally diverse group of genes expressed in reproductive and somatic tissue to test whether a variety of protein characteristics such as phylogenetic clusters, tissue of expression, and proteolytic and adhesive function can group fast evolving ADAM genes. We found that all genes were evolving under purifying selection (d(N)/d(S) < 1), although reproductive ADAMs, including those implicated in fertilization and spermatogenesis, evolved at the fastest rate. Genes with a role in binding to cell receptors in endogenous tissue appear to be evolving under purifying selection, regardless of the tissue of expression. In contrast, positive selection of codon sites in the disintegrin/cysteine-rich adhesion domains was detected exclusively in ADAMs 2 and 32, two genes expressed in the testis with a potential role in sperm-egg adhesion. Positive selection was detected in the transmembrane/cytosolic tail region of ADAM genes expressed in a variety of tissues.

  18. An improved method for functional similarity analysis of genes based on Gene Ontology.

    Science.gov (United States)

    Tian, Zhen; Wang, Chunyu; Guo, Maozu; Liu, Xiaoyan; Teng, Zhixia

    2016-12-23

    Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional similarity methods have been proposed based on the semantic similarity of GO terms. However, these leading approaches may make errorprone judgments especially when they measure the specificity of GO terms as well as the IC of a term set. Therefore, how to estimate the gene functional similarity reliably is still a challenging problem. We propose WIS, an effective method to measure the gene functional similarity. First of all, WIS computes the IC of a term by employing its depth, the number of its ancestors as well as the topology of its descendants in the GO graph. Secondly, WIS calculates the IC of a term set by means of considering the weighted inherited semantics of terms. Finally, WIS estimates the gene functional similarity based on the IC overlap ratio of term sets. WIS is superior to some other representative measures on the experiments of functional classification of genes in a biological pathway, collaborative evaluation of GO-based semantic similarity measures, protein-protein interaction prediction and correlation with gene expression. Further analysis suggests that WIS takes fully into account the specificity of terms and the weighted inherited semantics of terms between GO terms. The proposed WIS method is an effective and reliable way to compare gene function. The web service of WIS is freely available at http://nclab.hit.edu.cn/WIS/ .

  19. Substrate-induced gene expression screening: a method for high-throughput screening of metagenome libraries.

    Science.gov (United States)

    Uchiyama, Taku; Miyazaki, Kentaro

    2010-01-01

    The SIGEX (substrate-induced gene expression) method is a novel approach for the screening of gene (genome) libraries. In addition to the commonly used function- and sequence-driven approaches to screening, SIGEX provides a third option; in SIGEX, positives are identified using a reporter gene, and the library is constructed using an "operon-trap" vector. This vector contains the reporter gene immediately downstream of the cloning site for the genomic insert so that the expression of the inserted gene(s) is coupled with that of the reporter gene. This system is especially suitable for screening catabolic genes that are induced in response to metabolically relevant compounds, such as substrates. If expression of the inserted gene(s) is activated in response to the addition of these compounds, then positive clones can be identified based on the reporter signal. The most effective selection is obtained by the use of a FACS (fluorescence-activated cell sorter) in conjunction with a FACS-compatible fluorescent reporter protein, such as GFP (green fluorescent protein). Activity-based screening of metagenomic libraries often suffers from low sensitivity and low throughput. In contrast, the high throughput, high sensitivity, and versatility of SIGEX make it a particularly suitable method for screening metagenomic libraries.

  20. Selective AR Modulators that Distinguish Proliferative from Differentiative Gene Promoters

    Science.gov (United States)

    2015-08-01

    dependent compound screen, aided by the University of Michigan Center for Chemical Genomics . Differential AR activation in transfected cells was assessed...WR, Parker JS, Lee MX, Kass EM, Spratt DE, Iaquinta PJ, Arora VK, Yen WF, Cai L, Zheng D, Carver BS, Chen Y, Watson PA, Shah NP, Fujisawa S, Goglia...for known genes and genome -wide by ChIP-seq. Results will strengthen our overall hypothesis that genes with similar function (i.e

  1. Balancing selection on immunity genes: review of the current literature and new analysis in Drosophila melanogaster.

    Science.gov (United States)

    Croze, Myriam; Živković, Daniel; Stephan, Wolfgang; Hutter, Stephan

    2016-08-01

    Balancing selection has been widely assumed to be an important evolutionary force, yet even today little is known about its abundance and its impact on the patterns of genetic diversity. Several studies have shown examples of balancing selection in humans, plants or parasites, and many genes under balancing selection are involved in immunity. It has been proposed that host-parasite coevolution is one of the main forces driving immune genes to evolve under balancing selection. In this paper, we review the literature on balancing selection on immunity genes in several organisms, including Drosophila. Furthermore, we performed a genome scan for balancing selection in an African population of Drosophila melanogaster using coalescent simulations of a demographic model with and without selection. We find very few genes under balancing selection and only one novel candidate gene related to immunity. Finally, we discuss the possible causes of the low number of genes under balancing selection. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

  2. Differential transcription profiles in Aedes aegypti detoxification genes after temephos selection.

    Science.gov (United States)

    Saavedra-Rodriguez, K; Strode, C; Flores, A E; Garcia-Luna, S; Reyes-Solis, G; Ranson, H; Hemingway, J; Black, W C

    2014-04-01

    The mosquito Aedes aegypti is the main vector of Dengue and Yellow Fever flaviviruses. The organophosphate insecticide temephos is a larvicide that is used globally to control Ae. aegypti populations; many of which have in turn evolved resistance. Target site alteration in the acetylcholine esterase of this species has not being identified. Instead, we tracked changes in transcription of metabolic detoxification genes using the Ae. aegypti 'Detox Chip' microarray during five generations of temephos selection. We selected for temephos resistance in three replicates in each of six collections, five from Mexico, and one from Peru. The response to selection was tracked in terms of lethal concentrations. Uniform upregulation was seen in the epsilon class glutathione-S-transferase (eGST) genes in strains from Mexico prior to laboratory selection, while eGSTs in the Iquitos Peru strain became upregulated after five generations of temephos selection. While expression of many carboxyl/cholinesterase esterase (CCE) genes increased with selection, no single esterase was consistently upregulated and this same pattern was noted in the cytochrome P450 monooxygenase (CYP) genes and in other genes involved in reduction or oxidation of xenobiotics. Bioassays using glutathione-S-transferase (GST), CCE and CYP inhibitors suggest that various CCEs instead of GSTs are the main metabolic mechanism conferring resistance to temephos. We show that temephos-selected strains show no cross resistance to permethrin and that genes associated with temephos selection are largely independent of those selected with permethrin in a previous study.

  3. Targeting of breast metastases using a viral gene vector with tumour-selective transcription.

    LENUS (Irish Health Repository)

    Rajendran, Simon

    2012-01-31

    BACKGROUND: Adeno-associated virus (AAV) vectors have significant potential as gene delivery vectors for cancer gene therapy. However, broad AAV2 tissue tropism results in nonspecific gene expression. MATERIALS AND METHODS: We investigated use of the C-X-C chemokine receptor type 4 (CXCR4) promoter to restrict AAV expression to tumour cells, in subcutaneous MCF-7 xenograft mouse models of breast cancer and in patient samples, using bioluminescent imaging and flow cytometric analysis. RESULTS: Higher transgene expression levels were observed in subcutaneous MCF-7 tumours relative to normal tissue (muscle) using the CXCR4 promoter, unlike a ubiquitously expressing Cytomegalovirus promoter construct, with preferential AAVCXCR4 expression in epithelial tumour and CXCR4-positive cells. Transgene expression following intravenously administered AAVCXCR4 in a model of liver metastasis was detected specifically in livers of tumour bearing mice. Ex vivo analysis using patient samples also demonstrated higher AAVCXCR4 expression in tumour compared with normal liver tissue. CONCLUSION: This study demonstrates for the first time, the potential for systemic administration of AAV2 vector for tumour-selective gene therapy.

  4. Genetic Diversity and Balancing Selection within the Human Phenylalanine Hydroxylase (PAH Gene Region in Iranian Population

    Directory of Open Access Journals (Sweden)

    J Mowla

    2012-04-01

    Full Text Available Background:Genetic diversity of three polymorphic markers in the phenylalanine hydroxylase(PAH gene region including PvuII(a, PAHSTR and MspI were investigated.Methods:Unrelated individuals (n=139 from the Iranian populations were genotyped using primers specific to PAH gene markers including PvuII(a,MspI and PAHSTR. The amplified products for PvuII(a,MspI were digested using the appropriate restriction enzymes and separated on 1.5% agarose. The PAHSTR alleles were identified using polyacrylamide gel electrophoresis followed by silver staining. The exact size of the STR alleles was determined by sequencing. The allele frequency and population status of the alleles were estimated using PHASE, FBAT and GENEPOP software.Results: The estimated degree of heterozygosity for PAHSTR, MspI and PvuII (a was 66%, 56% and 58%, respectively. The haplotype estimation analysis of the markers resulted in nine informative haplotypes with frequencies ≥5%.Moreover,the results obtained from Ewens-Watterson test for neutrality suggested that the markers were under balancing selection in the Iranian population.Conclusion:These findings suggested the presence of genetic diversity at these three markers in the PAH gene region. Therefore, the markers could be considered as functional markers for linkage analysis of the PAH gene mutations in the Iranian families with the PKU disease.

  5. Successful recovery of transgenic cowpea (Vigna unguiculata) using the 6-phosphomannose isomerase gene as the selectable marker.

    Science.gov (United States)

    Bakshi, Souvika; Saha, Bedabrata; Roy, Nand Kishor; Mishra, Sagarika; Panda, Sanjib Kumar; Sahoo, Lingaraj

    2012-06-01

    A new method for obtaining transgenic cowpea was developed using positive selection based on the Escherichia coli 6-phosphomannose isomerase gene as the selectable marker and mannose as the selective agent. Only transformed cells were capable of utilizing mannose as a carbon source. Cotyledonary node explants from 4-day-old in vitro-germinated seedlings of cultivar Pusa Komal were inoculated with Agrobacterium tumefaciens strain EHA105 carrying the vector pNOV2819. Regenerating transformed shoots were selected on medium supplemented with a combination of 20 g/l mannose and 5 g/l sucrose as carbon source. The transformed shoots were rooted on medium devoid of mannose. Transformation efficiency based on PCR analysis of individual putative transformed shoots was 3.6%. Southern blot analysis on five randomly chosen PCR-positive plants confirmed the integration of the pmi transgene. Qualitative reverse transcription (qRT-PCR) analysis demonstrated the expression of pmi in T₀ transgenic plants. Chlorophenol red (CPR) assays confirmed the activity of PMI in transgenic plants, and the gene was transmitted to progeny in a Mendelian fashion. The transformation method presented here for cowpea using mannose selection is efficient and reproducible, and could be used to introduce a desirable gene(s) into cowpea for biotic and abiotic stress tolerance.

  6. A systematic method for search term selection in systematic reviews.

    Science.gov (United States)

    Thompson, Jenna; Davis, Jacqueline; Mazerolle, Lorraine

    2014-06-01

    The wide variety of readily available electronic media grants anyone the freedom to retrieve published references from almost any area of research around the world. Despite this privilege, keeping up with primary research evidence is almost impossible because of the increase in professional publishing across disciplines. Systematic reviews are a solution to this problem as they aim to synthesize all current information on a particular topic and present a balanced and unbiased summary of the findings. They are fast becoming an important method of research across a number of fields, yet only a small number of guidelines exist on how to define and select terms for a systematic search. This article presents a replicable method for selecting terms in a systematic search using the semantic concept recognition software called leximancer (Leximancer, University of Queensland, Brisbane, Australia). We use this software to construct a set of terms from a corpus of literature pertaining to transborder interventions for drug control and discuss the applicability of this method to systematic reviews in general. This method aims to contribute a more 'systematic' approach for selecting terms in a manner that is entirely replicable for any user.

  7. Methods for the detection of specific bacteria and their genes in soil

    NARCIS (Netherlands)

    Elsas, van J.D.; Waalwijk, C.

    1991-01-01

    Methods for the introduction of specific genetic markers into soil bacteria and detection of these bacteria in soil are reviewed. Cuiturable cells may be detected and quantified by (selective) cultivation followed by gene probing. Non-culturable cells may be detected by immunofluorescence using

  8. Scarless Gene Tagging with One-Step Transformation and Two-Step Selection in Saccharomyces cerevisiae and Schizosaccharomyces pombe

    Science.gov (United States)

    Huh, Dann; Hallacli, Erinc; Lindquist, Susan

    2016-01-01

    Gene tagging with fluorescent proteins is commonly applied to investigate the localization and dynamics of proteins in their cellular environment. Ideally, a fluorescent tag is genetically inserted at the endogenous locus at the N- or C- terminus of the gene of interest without disrupting regulatory sequences including the 5’ and 3’ untranslated region (UTR) and without introducing any extraneous unwanted “scar” sequences, which may create unpredictable transcriptional or translational effects. We present a reliable, low-cost, and highly efficient method for the construction of such scarless C-terminal and N-terminal fusions with fluorescent proteins in yeast. The method relies on sequential positive and negative selection and uses an integration cassette with long flanking regions, which is assembled by two-step PCR, to increase the homologous recombination frequency. The method also enables scarless tagging of essential genes with no need for a complementing plasmid. To further ease high-throughput strain construction, we have computationally automated design of the primers, applied the primer design code to all open reading frames (ORFs) of the budding yeast Saccharomyces cerevisiae (S. cerevisiae) and the fission yeast Schizosaccharomyces pombe (S. pombe), and provide here the computed sequences. To illustrate the scarless N- and C-terminal gene tagging methods in S. cerevisiae, we tagged various genes including the E3 ubiquitin ligase RSP5, the proteasome subunit PRE1, and the eleven Rab GTPases with yeast codon-optimized mNeonGreen or mCherry; several of these represent essential genes. We also implemented the scarless C-terminal gene tagging method in the distantly related organism S. pombe using kanMX6 and HSV1tk as positive and negative selection markers, respectively, as well as ura4. The scarless gene tagging methods presented here are widely applicable to visualize and investigate the functional roles of proteins in living cells. PMID:27736907

  9. Adiponectin gene polymorphism is selectively associated with the concomitant presence of metabolic syndrome and essential hypertension.

    Directory of Open Access Journals (Sweden)

    Hsin-Bang Leu

    Full Text Available OBJECTIVE: Cardiovascular risk increases with the presence of both metabolic syndrome (MetS and hypertension (HTN. Although the adiponectin (ADIPOQ gene has been reported to be involved in MetS, its association with HTN remained undetermined. This study aimed to investigate the association of ADIPOQ gene with the phenotypes of HTN and MetS. METHODS: A total of 962 participants from 302 families from the Taiwan young-onset hypertension genetic study were enrolled. Plasma adiponectin were measured, and association analysis was conducted by using GEE regression-based method. Another study, of 1448 unrelated participants, was conducted to replicate the association between ADIPOQ gene and variable phenotypes of MetS with or without HTN. RESULTS: Among 962 subjects from family samples, the lowest plasma adiponectin value was observed in MetS with HTN component (9.3±0.47 µg/ml compared with hypertensives (13.4±0.74 µg /ml or MetS without HTN (11.9±0.60 µg/ml, P<0.05. The SNP rs1501299 (G276T in ADIPOQ gene was found associated with the presence of HTN in MetS (odds ratio for GG+GT vs. TT = 2.46; 95% CI: 1.14-5.3, p = 0.02, but not rs2241766 (T45G. No association of ADIPOQ gene with HTN alone or MetS without HTN was observed. The significant association of the SNP rs1501299 (G276T with the phenotype of presence of HTN in MetS was confirmed (odds ratio for GG+GT vs. TT = 2.15; 95% CI: 1.1-4.3 in the replication study. CONCLUSIONS: ADIPOQ genetic variants were selectively and specifically associated with the concomitant presence of MetS and HTN, suggesting potential genetic linkage between MetS and HTN.

  10. [Evaluation of using statistical methods in selected national medical journals].

    Science.gov (United States)

    Sych, Z

    1996-01-01

    The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as

  11. High diversity and no significant selection signal of human ADH1B gene in Tibet

    Directory of Open Access Journals (Sweden)

    Lu Yan

    2012-11-01

    Full Text Available Abstract Background ADH1B is one of the most studied human genes with many polymorphic sites. One of the single nucleotide polymorphism (SNP, rs1229984, coding for the Arg48His substitution, have been associated with many serious diseases including alcoholism and cancers of the digestive system. The derived allele, ADH1B*48His, reaches high frequency only in East Asia and Southwest Asia, and is highly associated with agriculture. Micro-evolutionary study has defined seven haplogroups for ADH1B based on seven SNPs encompassing the gene. Three of those haplogroups, H5, H6, and H7, contain the ADH1B*48His allele. H5 occurs in Southwest Asia and the other two are found in East Asia. H7 is derived from H6 by the derived allele of rs3811801. The H7 haplotype has been shown to have undergone significant positive selection in Han Chinese, Hmong, Koreans, Japanese, Khazak, Mongols, and so on. Methods In the present study, we tested whether Tibetans also showed evidence for selection by typing 23 SNPs in the region covering the ADH1B gene in 1,175 individuals from 12 Tibetan populations representing all districts of the Tibet Autonomous Region. Multiple statistics were estimated to examine the gene diversities and positive selection signals among the Tibetans and other populations in East Asia. Results The larger Tibetan populations (Qamdo, Lhasa, Nagqu, Nyingchi, Shannan, and Shigatse comprised mostly farmers, have around 12% of H7, and 2% of H6. The smaller populations, living on hunting or recently switched to farming, have lower H7 frequencies (Tingri 9%, Gongbo 8%, Monba and Sherpa 6%. Luoba (2% and Deng (0% have even lower frequencies. Long-range haplotype analyses revealed very weak signals of positive selection for H7 among Tibetans. Interestingly, the haplotype diversity of H7 is higher in Tibetans than in any other populations studied, indicating a longer diversification history for that haplogroup in Tibetans. Network analysis on the long

  12. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2015-01-01

    Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  13. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method.

    Science.gov (United States)

    Alguliyev, Rasim M; Aliguliyev, Ramiz M; Mahmudova, Rasmiyya S

    2015-01-01

    Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  14. Novel selection methods for DNA-encoded chemical libraries.

    Science.gov (United States)

    Chan, Alix I; McGregor, Lynn M; Liu, David R

    2015-06-01

    Driven by the need for new compounds to serve as biological probes and leads for therapeutic development and the growing accessibility of DNA technologies including high-throughput sequencing, many academic and industrial groups have begun to use DNA-encoded chemical libraries as a source of bioactive small molecules. In this review, we describe the technologies that have enabled the selection of compounds with desired activities from these libraries. These methods exploit the sensitivity of in vitro selection coupled with DNA amplification to overcome some of the limitations and costs associated with conventional screening methods. In addition, we highlight newer techniques with the potential to be applied to the high-throughput evaluation of DNA-encoded chemical libraries.

  15. ORDERED WEIGHTED AVERAGING AGGREGATION METHOD FOR PORTFOLIO SELECTION

    Institute of Scientific and Technical Information of China (English)

    LIU Shancun; QIU Wanhua

    2004-01-01

    Portfolio management is a typical decision making problem under incomplete,sometimes unknown, informationThis paper considers the portfolio selection problemsunder a general setting of uncertain states without probabilityThe investor's preferenceis based on his optimum degree about the nature, and his attitude can be described by anOrdered Weighted Averaging Aggregation functionWe construct the OWA portfolio selec-tion model, which is a nonlinear programming problemThe problem can be equivalentlytransformed into a mixed integer linear programmingA numerical example is given andthe solutions imply that the investor's strategies depend not only on his optimum degreebut also on his preference weight vectorThe general game-theoretical portfolio selectionmethod, max-min method and competitive ratio method are all the special settings of thismodel.

  16. Multiple ant colony algorithm method for selecting tag SNPs.

    Science.gov (United States)

    Liao, Bo; Li, Xiong; Zhu, Wen; Li, Renfa; Wang, Shulin

    2012-10-01

    The search for the association between complex disease and single nucleotide polymorphisms (SNPs) or haplotypes has recently received great attention. Finding a set of tag SNPs for haplotyping in a great number of samples is an important step to reduce cost for association study. Therefore, it is essential to select tag SNPs with more efficient algorithms. In this paper, we model problem of selection tag SNPs by MINIMUM TEST SET and use multiple ant colony algorithm (MACA) to search a smaller set of tag SNPs for haplotyping. The various experimental results on various datasets show that the running time of our method is less than GTagger and MLR. And MACA can find the most representative SNPs for haplotyping, so that MACA is more stable and the number of tag SNPs is also smaller than other evolutionary methods (like GTagger and NSGA-II). Our software is available upon request to the corresponding author.

  17. Using RNA-Seq data to select refence genes for normalizing gene expression in apple roots

    Science.gov (United States)

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for t...

  18. Selection of reference genes for gene expression studies related to intramuscular fat deposition in Capra hircus skeletal muscle.

    Science.gov (United States)

    Zhu, Wuzheng; Lin, Yaqiu; Liao, Honghai; Wang, Yong

    2015-01-01

    The identification of suitable reference genes is critical for obtaining reliable results from gene expression studies using quantitative real-time PCR (qPCR) because the expression of reference genes may vary considerably under different experimental conditions. In most cases, however, commonly used reference genes are employed in data normalization without proper validation, which may lead to incorrect data interpretation. Here, we aim to select a set of optimal reference genes for the accurate normalization of gene expression associated with intramuscular fat (IMF) deposition during development. In the present study, eight reference genes (PPIB, HMBS, RPLP0, B2M, YWHAZ, 18S, GAPDH and ACTB) were evaluated by three different algorithms (geNorm, NormFinder and BestKeeper) in two types of muscle tissues (longissimus dorsi muscle and biceps femoris muscle) across different developmental stages. All three algorithms gave similar results. PPIB and HMBS were identified as the most stable reference genes, while the commonly used reference genes 18S and GAPDH were the most variably expressed, with expression varying dramatically across different developmental stages. Furthermore, to reveal the crucial role of appropriate reference genes in obtaining a reliable result, analysis of PPARG expression was performed by normalization to the most and the least stable reference genes. The relative expression levels of PPARG normalized to the most stable reference genes greatly differed from those normalized to the least stable one. Therefore, evaluation of reference genes must be performed for a given experimental condition before the reference genes are used. PPIB and HMBS are the optimal reference genes for analysis of gene expression associated with IMF deposition in skeletal muscle during development.

  19. Genome-wide selection of superior reference genes for expression studies in Ganoderma lucidum.

    Science.gov (United States)

    Xu, Zhichao; Xu, Jiang; Ji, Aijia; Zhu, Yingjie; Zhang, Xin; Hu, Yuanlei; Song, Jingyuan; Chen, Shilin

    2015-12-15

    Quantitative real-time polymerase chain reaction (qRT-PCR) is widely used for the accurate analysis of gene expression. However, high homology among gene families might result in unsuitability of reference genes, which leads to the inaccuracy of qRT-PCR analysis. The release of the Ganoderma lucidum genome has triggered numerous studies to be done on the homology among gene families with the purpose of selecting reliable reference genes. Based on the G. lucdum genome and transcriptome database, 38 candidate reference genes including 28 novel genes were systematically selected and evaluated for qRT-PCR normalization. The result indicated that commonly used polyubiquitin (PUB), beta-actin (BAT), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were unsuitable reference genes because of the high sequence similarity and low primer specificity. According to the evaluation of RefFinder, cyclophilin 5 (CYP5) was ranked as the most stable reference gene for 27 tested samples under all experimental conditions and eighteen mycelial samples. Based on sequence analysis and expression analysis, our study suggested that gene characteristic, primer specificity of high homologous genes, allele-specificity expression of candidate genes and under-evaluation of reference genes influenced the accuracy and sensitivity of qRT-PCR analysis. This investigation not only revealed potential factors influencing the unsuitability of reference genes but also selected the superior reference genes from more candidate genes and testing samples than those used in the previous study. Furthermore, our study established a model for reference gene analysis by using the genomic sequence.

  20. Essay on Methods in Futures Studies and a Selective Bibliography

    DEFF Research Database (Denmark)

    Poulsen, Claus

    2005-01-01

    in futures studies must be open to critique to be accepted as a research activity. Premises, assumptions, methods and data have to be explicit as a critical discourse, cooperation, and eventual revision is to be carried out by egalitarian means, potentially accessible to all. Problems in this idealistic...... programme are (only) partly reduced by applying Causal Layered Analysis as an internal quality control. The following selective bibliography is focussed on these methodological issues...

  1. GeneWaltz--A new method for reducing the false positives of gene finding

    Directory of Open Access Journals (Sweden)

    Misawa Kazuharu

    2010-09-01

    Full Text Available Abstract Background Identifying protein-coding regions in genomic sequences is an essential step in genome analysis. It is well known that the proportion of false positives among genes predicted by current methods is high, especially when the exons are short. These false positives are problematic because they waste time and resources of experimental studies. Methods We developed GeneWaltz, a new filtering method that reduces the risk of false positives in gene finding. GeneWaltz utilizes a codon-to-codon substitution matrix that was constructed by comparing protein-coding regions from orthologous gene pairs between mouse and human genomes. Using this matrix, a scoring scheme was developed; it assigned higher scores to coding regions and lower scores to non-coding regions. The regions with high scores were considered candidate coding regions. One-dimensional Karlin-Altschul statistics was used to test the significance of the coding regions identified by GeneWaltz. Results The proportion of false positives among genes predicted by GENSCAN and Twinscan were high, especially when the exons were short. GeneWaltz significantly reduced the ratio of false positives to all positives predicted by GENSCAN and Twinscan, especially when the exons were short. Conclusions GeneWaltz will be helpful in experimental genomic studies. GeneWaltz binaries and the matrix are available online at http://en.sourceforge.jp/projects/genewaltz/.

  2. Benchmarking Transcriptome Quantification Methods for Duplicated Genes in Xenopus laevis.

    Science.gov (United States)

    Kwon, Taejoon

    2015-01-01

    Xenopus is an important model organism for the study of genome duplication in vertebrates. With the full genome sequence of diploid Xenopus tropicalis available, and that of allotetraploid X. laevis close to being finished, we will be able to expand our understanding of how duplicated genes have evolved. One of the key features in the study of the functional consequence of gene duplication is how their expression patterns vary across different conditions, and RNA-seq seems to have enough resolution to discriminate the expression of highly similar duplicated genes. However, most of the current RNA-seq analysis methods were not designed to study samples with duplicate genes such as in X. laevis. Here, various computational methods to quantify gene expression in RNA-seq data were evaluated, using 2 independent X. laevis egg RNA-seq datasets and 2 reference databases for duplicated genes. The fact that RNA-seq can measure expression levels of similar duplicated genes was confirmed, but long paired-end reads are more informative than short single-end reads to discriminate duplicated genes. Also, it was found that bowtie, one of the most popular mappers in RNA-seq analysis, reports significantly smaller numbers of unique hits according to a mapping quality score compared to other mappers tested (BWA, GSNAP, STAR). Calculated from unique hits based on a mapping quality score, both expression levels and the expression ratio of duplicated genes can be estimated consistently among biological replicates, demonstrating that this method can successfully discriminate the expression of each copy of a duplicated gene pair. This comprehensive evaluation will be a useful guideline for studying gene expression of organisms with genome duplication using RNA-seq in the future.

  3. BAGE genes generated by juxtacentromeric reshuffling in the Hominidae lineage are under selective pressure.

    Science.gov (United States)

    Ruault, Myriam; Ventura, Mario; Galtier, Nicolas; Brun, Marie-Elisabeth; Archidiacono, Nicoletta; Roizès, Gérard; De Sario, Albertina

    2003-04-01

    In this paper, we show that the BAGE (B melanoma antigen) gene family was generated by chromosome rearrangements that occurred during the evolution of hominoids. An 84-kb DNA fragment derived from the phylogenetic 7q36 region was duplicated in the juxtacentromeric region of either chromosome 13 or chromosome 21. The duplicated region contained a fragment of the MLL3 gene, which, after juxtacentromeric reshuffling, generated the ancestral BAGE gene. Then, this ancestral gene gave rise to several independent genes through successive rounds of inter- and intrachromosome duplications. Comparison of synonymous and nonsynonymous mutations in putative coding regions shows that BAGE genes, but not the BAGE gene fragments, are under selective pressure. Our data strongly suggest that BAGE proteins have a function and that juxtacentromeric regions, whose plasticity is now largely proved, are not a simple junkyard of gene fragments, but may be the birth site of novel genes.

  4. Encapsulated formulation of the Selective Frequency Damping method

    CERN Document Server

    Jordi, Bastien E; Sherwin, Spencer J

    2013-01-01

    We present an alternative "encapsulated" formulation of the Selective Frequency Damping method for finding unstable equilibria of dynamical systems, which is particularly useful when analysing the stability of fluid flows. The formulation makes use of splitting methods, which means that it can be wrapped around an existing time-stepping code as a "black box". The method is first applied to a scalar problem in order to analyse its stability and highlight the roles of the control coefficient $\\chi$ and the filter width $\\Delta$ in the convergence (or not) towards the steady-state. Then the steady-state of the incompressible flow past a two-dimensional cylinder at $Re=100$, obtained with a code which implements the spectral/hp element method, is presented.

  5. The selective dynamical downscaling method for extreme-wind atlases

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Badger, Jake; Hahmann, Andrea N.

    2012-01-01

    and (iii) post-processing. The post-processing generalizes the winds from the mesoscale modelling to standard conditions, i.e. 10-m height over a homogeneous surface with roughness length of 5 cm. The generalized winds are then used to calculate the 50-year wind using the annual maximum method for each......A selective dynamical downscaling method is developed to obtain extreme-wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling...... mesoscale grid point. The generalization of the mesoscale winds through the post-processing provides a framework for data validation and for applying further the mesoscale extreme winds at specific places using microscale modelling. The results are compared with measurements from two areas with different...

  6. Criteria and methods for indicator assessment and selection

    DEFF Research Database (Denmark)

    Gudmundsson, Henrik; Tennøy, Aud; Joumard, Robert

    2010-01-01

    indicators? How can several indicators be jointly considered? And how can indicators be used in planning and decision making? Firstly we provide definition of 'indicator of environmental sustainability in transport'. The functions, strengths and weaknesses of indicators as measurement tools, and as decision...... for indicators and assessments. As the decision making context influences the perceived and actual needs for indicators and methods, we also analysed the dimensions and context of decision making. We derived criteria and methods for the assessment and selection of indicators of environmental sustainability...... in transport, in terms of measurement, monitoring and management. The methods and the criteria are exemplified for seven chains of causality. Methods for a comprehensive joint consideration of environmentally sustainable indicators are analyzed and evaluated. They concerned aggregated or composite indicators...

  7. A fractured rock geophysical toolbox method selection tool

    Science.gov (United States)

    Day-Lewis, F. D.; Johnson, C.D.; Slater, L.D.; Robinson, J.L.; Williams, J.H.; Boyden, C.L.; Werkema, D.D.; Lane, J.W.

    2016-01-01

    Geophysical technologies have the potential to improve site characterization and monitoring in fractured rock, but the appropriate and effective application of geophysics at a particular site strongly depends on project goals (e.g., identifying discrete fractures) and site characteristics (e.g., lithology). No method works at every site or for every goal. New approaches are needed to identify a set of geophysical methods appropriate to specific project goals and site conditions while considering budget constraints. To this end, we present the Excel-based Fractured-Rock Geophysical Toolbox Method Selection Tool (FRGT-MST). We envision the FRGT-MST (1) equipping remediation professionals with a tool to understand what is likely to be realistic and cost-effective when contracting geophysical services, and (2) reducing applications of geophysics with unrealistic objectives or where methods are likely to fail.

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

    Science.gov (United States)

    Teng, Shaolei; Yang, Jack Y; Wang, Liangjiang

    2013-01-01

    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. 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. 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.

  9. Selection of housekeeping genes for gene expression studies in larvae from flatfish using real-time PCR

    Directory of Open Access Journals (Sweden)

    Reith Michael

    2008-03-01

    Full Text Available Abstract Background Flatfish metamorphosis involves major physiological and morphological changes. Due to its importance in aquaculture and as a model for developmental studies, some gene expression studies have focused on the understanding of this process using quantitative real-time PCR (qRT-PCR technique. Therefore, adequate reference genes for accurate normalization are required. Results The stability of 12 potential reference genes was examined during larval development in Senegalese sole (Solea senegalensis and Atlantic halibut (Hippoglossus hippoglossus to determine the most suitable genes for qRT-PCR analysis. Transcription levels of genes encoding β-Actin (ACTB, glyceraldehyde-3P-dehydrogenase (GAPDH, annexin A2 (ANXA2, glutathione S-transferase (GST, ornithine decarboxylase (ODC, hypoxanthine phosphoribosyltransferase (HPRT1, ubiquitin (UBQ, elongation factor 1 alpha (eEF1A1, 18S ribosomal RNA, and the ribosomal proteins S4 (RPS4 and L13a (RPL13a were quantitated. Two paralogous genes for ACTB were analyzed in each of both flatfish species. In addition, two paralogous genes for GAPDH were studied in Senegalese sole. RPL13a represented non-orthologous genes between both flatfish species. GeNorm and NormFinder analyses for expression stability revealed RPS4, UBQ and eEF1A1 as the most stable genes in Senegalese sole, Atlantic halibut and in a combined analysis. In all cases, paralogous genes exhibited differences in expression stability. Conclusion This work suggests RPS4, UBQ, and eEF1A1 genes as useful reference genes for accurate normalization in qRT-PCR studies in Senegalese sole and Atlantic halibut larvae. The congruent results between both species in spite of the drastic differences in larval development suggest that selected housekeeping genes (HKGs could be useful in other flatfish species. However, the finding of paralogous gene copies differentially expressed during development in some HKGs underscores the necessity to

  10. Change of positive selection pressure on HIV-1 envelope gene inferred by early and recent samples.

    Directory of Open Access Journals (Sweden)

    Izumi Yoshida

    Full Text Available HIV-1 infection has been on the rise in Japan recently, and the main transmission route has changed from blood transmission in the 1980s to homo- and/or hetero-sexual transmission in the 2000s. The lack of early viral samples with clinical information made it difficult to investigate the possible virological changes over time. In this study, we sequenced 142 full-length env genes collected from 16 Japanese subjects infected with HIV-1 in the 1980s and in the 2000s. We examined the diversity change in sequences and potential adaptive evolution of the virus to the host population. We used a codon-based likelihood method under the branch-site and clade models to detect positive selection operating on the virus. The clade model was extended to account for different positive selection pressures in different viral populations. The result showed that the selection pressure was weaker in the 2000s than in the 1980s, indicating that it might have become easier for the HIV to infect a new host and to develop into AIDS now than 20 years ago and that the HIV may be becoming more virulent in the Japanese population. The study provides useful information on the surveillance of HIV infection and highlights the utility of the extended clade models in analysis of virus populations which may be under different selection pressures.

  11. Quantitative DNA methylation analysis of selected genes in endometrial carcinogenesis

    Directory of Open Access Journals (Sweden)

    Ying-Chieh Chen

    2015-10-01

    Conclusion: Promoter methylation of ZNF177, COL14A1, HOXA9, DPYSL4, and TMEFF2 genes is a frequent epigenetic event in EC. Furthermore, the epigenetic hypermethylation of TMEFF2 may be a valuable marker for identifying undetected EC within endometrial hyperplasia.

  12. Diversification of the ant odorant receptor gene family and positive selection on candidate cuticular hydrocarbon receptors.

    Science.gov (United States)

    Engsontia, Patamarerk; Sangket, Unitsa; Robertson, Hugh M; Satasook, Chutamas

    2015-08-27

    Chemical communication plays important roles in the social behavior of ants making them one of the most successful groups of animals on earth. However, the molecular evolutionary process responsible for their chemosensory adaptation is still elusive. Recent advances in genomic studies have led to the identification of large odorant receptor (Or) gene repertoires from ant genomes providing fruitful materials for molecular evolution analysis. The aim of this study was to test the hypothesis that diversification of this gene family is involved in olfactory adaptation of each species. We annotated the Or genes from the genome sequences of two leaf-cutter ants, Acromyrmex echinatior and Atta cephalotes (385 and 376 putative functional genes, respectively). These were used, together with Or genes from Camponotus floridanus, Harpegnathos saltator, Pogonomyrmex barbatus, Linepithema humile, Cerapachys biroi, Solenopsis invicta and Apis mellifera, in molecular evolution analysis. Like the Or family in other insects, ant Or genes evolve by the birth-and-death model of gene family evolution. Large gene family expansions involving tandem gene duplications, and gene gains outnumbering losses, are observed. Codon analysis of genes in lineage-specific expansion clades revealed signatures of positive selection on the candidate cuticular hydrocarbon receptor genes (9-exon subfamily) of Cerapachys biroi, Camponotus floridanus, Acromyrmex echinatior and Atta cephalotes. Positively selected amino acid positions are primarily in transmembrane domains 3 and 6, which are hypothesized to contribute to the odor-binding pocket, presumably mediating changing ligand specificity. This study provides support for the hypothesis that some ant lineage-specific Or genes have evolved under positive selection. Newly duplicated genes particularly in the candidate cuticular hydrocarbon receptor clade that have evolved under positive selection may contribute to the highly sophisticated lineage

  13. GOParGenPy: a high throughput method to generate gene ontology data matrices.

    Science.gov (United States)

    Kumar, Ajay Anand; Holm, Liisa; Toronen, Petri

    2013-08-08

    Gene Ontology (GO) is a popular standard in the annotation of gene products and provides information related to genes across all species. The structure of GO is dynamic and is updated on a daily basis. However, the popular existing methods use outdated versions of GO. Moreover, these tools are slow to process large datasets consisting of more than 20,000 genes. We have developed GOParGenPy, a platform independent software tool to generate the binary data matrix showing the GO class membership, including parental classes, of a set of GO annotated genes. GOParGenPy is at least an order of magnitude faster than popular tools for Gene Ontology analysis and it can handle larger datasets than the existing tools. It can use any available version of the GO structure and allows the user to select the source of GO annotation. GO structure selection is critical for analysis, as we show that GO classes have rapid turnover between different GO structure releases. GOParGenPy is an easy to use software tool which can generate sparse or full binary matrices from GO annotated gene sets. The obtained binary matrix can then be used with any analysis environment and with any analysis methods.

  14. Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

    Energy Technology Data Exchange (ETDEWEB)

    Balabin, Roman M., E-mail: balabin@org.chem.ethz.ch [Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich (Switzerland); Smirnov, Sergey V. [Unimilk Joint Stock Co., 143421 Moscow Region (Russian Federation)

    2011-04-29

    During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm{sup -1}) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

  15. Appropriate model selection methods for nonstationary generalized extreme value models

    Science.gov (United States)

    Kim, Hanbeen; Kim, Sooyoung; Shin, Hongjoon; Heo, Jun-Haeng

    2017-04-01

    Several evidences of hydrologic data series being nonstationary in nature have been found to date. This has resulted in the conduct of many studies in the area of nonstationary frequency analysis. Nonstationary probability distribution models involve parameters that vary over time. Therefore, it is not a straightforward process to apply conventional goodness-of-fit tests to the selection of an appropriate nonstationary probability distribution model. Tests that are generally recommended for such a selection include the Akaike's information criterion (AIC), corrected Akaike's information criterion (AICc), Bayesian information criterion (BIC), and likelihood ratio test (LRT). In this study, the Monte Carlo simulation was performed to compare the performances of these four tests, with regard to nonstationary as well as stationary generalized extreme value (GEV) distributions. Proper model selection ratios and sample sizes were taken into account to evaluate the performances of all the four tests. The BIC demonstrated the best performance with regard to stationary GEV models. In case of nonstationary GEV models, the AIC proved to be better than the other three methods, when relatively small sample sizes were considered. With larger sample sizes, the AIC, BIC, and LRT presented the best performances for GEV models which have nonstationary location and/or scale parameters, respectively. Simulation results were then evaluated by applying all four tests to annual maximum rainfall data of selected sites, as observed by the Korea Meteorological Administration.

  16. GAP1, a novel selection and counter-selection marker for multiple gene disruptions in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Regenberg, Birgitte; Hansen, J.

    2000-01-01

    We report on the use of a new homologous marker for use in multiple gene deletions in S, cerevisiae, the general amino acid permease gene (GAP1), A GAP1 strain can utilize L-citrulline as the sole nitrogen source but cannot grow in the presence of the toxic amino acid D-histidine, L-citrulline as......We report on the use of a new homologous marker for use in multiple gene deletions in S, cerevisiae, the general amino acid permease gene (GAP1), A GAP1 strain can utilize L-citrulline as the sole nitrogen source but cannot grow in the presence of the toxic amino acid D-histidine, L......-citrulline as well as D-histidine uptake is mediated solely by the general amino acid permease, and a gap1 strain is therefore able to grow in the presence of D-histidine but cannot utilize L-citrulline, Gene disruption is effected by transforming a gap1 strain with a gene cassette generated by PCR, containing GAP1...... the GAP1 gene. This is caused by recombination between two Salmonella typuimurium hisG direct repeats embracing GAP1, and will result in a sub-population of gap1 cells. Such cells are selected on a medium containing D-histidine, and may subsequently be used for a second gene disruption. Hence, multiple...

  17. Mammalian NPC1 genes may undergo positive selection and human polymorphisms associate with type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Al-Daghri Nasser M

    2012-11-01

    Full Text Available Abstract Background The NPC1 gene encodes a protein involved in intracellular lipid trafficking; its second endosomal loop (loop 2 is a receptor for filoviruses. A polymorphism (His215Arg in NPC1 was associated with obesity in Europeans. Adaptations to diet and pathogens represented powerful selective forces; thus, we analyzed the evolutionary history of the gene and exploited this information for the identification of variants/residues of functional importance in human disease. Methods We performed phylogenetic analysis, population genetic tests, and genotype-phenotype analysis in a population from Saudi Arabia. Results Maximum-likelihood ratio tests indicated the action of positive selection on loop 2 and identified three residues as selection targets; these were confirmed by an independent random effects likelihood (REL analysis. No selection signature was detected in present-day human populations, but analysis of nonsynonymous polymorphisms showed that a variant (Ile642Met, rs1788799 in the sterol sensing domain affects a highly conserved position. This variant and the previously described His215Arg polymorphism were tested for association with obesity and type 2 diabetes (T2D in a cohort from Saudi Arabia. Whereas no association with obesity was detected, 642Met allele was found to predispose to T2D. A significant interaction was noted with sex (P = 0.041, and stratification on the basis of gender indicated that the association is driven by men (P = 0.0021, OR = 1.5. Notably, two NPC1 haplotypes were also associated with T2D in men (rs1805081-rs1788799, His-Met: P = 0.0012, OR = 1.54; His-Ile: P = 0.0004, OR = 0.63. Conclusions Our data indicate a sex-specific effect of NPC1 variants on T2D risk and describe putative binding sites for filoviruses entry.

  18. A novel genomic selection method combining GBLUP and LASSO.

    Science.gov (United States)

    Li, Hengde; Wang, Jingwei; Bao, Zhenmin

    2015-06-01

    Genetic prediction of quantitative traits is a critical task in plant and animal breeding. Genomic selection is an accurate and efficient method of estimating genetic merits by using high-density genome-wide single nucleotide polymorphisms (SNP). In the framework of linear mixed models, we extended genomic best linear unbiased prediction (GBLUP) by including additional quantitative trait locus (QTL) information that was extracted from high-throughput SNPs by using least absolute shrinkage selection operator (LASSO). GBLUP was combined with three LASSO methods-standard LASSO (SLGBLUP), adaptive LASSO (ALGBLUP), and elastic net (ENGBLUP)-that were used for detecting QTLs, and these QTLs were fitted as fixed effects; the remaining SNPs were fitted using a realized genetic relationship matrix. Simulations performed under distinct scenarios revealed that (1) the prediction accuracy of SLGBLUP was the lowest; (2) the prediction accuracies of ALGBLUP and ENGBLUP were equivalent to or higher than that of GBLUP, except under scenarios in which the number of QTLs was large; and (3) the persistence of prediction accuracy over generations was strongest in the case of ENGBLUP. Building on the favorable computational characteristics of GBLUP, ENGBLUP enables robust modeling and efficient computation to be performed for genomic selection.

  19. Selected Tools and Methods from Quality Management Field

    Directory of Open Access Journals (Sweden)

    Kateřina BRODECKÁ

    2009-06-01

    Full Text Available Following paper describes selected tools and methods from Quality management field and their practical applications on defined examples. Solved examples were elaborated in the form of electronic support. This in detail elaborated electronic support provides students opportunity to thoroughly practice specific issues, help them to prepare for exams and consequently will lead to education improvement. Especially students of combined study form will appreciate this support. The paper specifies project objectives, subjects that will be covered by mentioned support, target groups, structure and the way of elaboration of electronic exercise book in view. The emphasis is not only on manual solution of selected examples that may help students to understand the principles and relationships, but also on solving and results interpreting of selected examples using software support. Statistic software Statgraphics Plus v 5.0 is used while working support, because it is free to use for all students of the faculty. Exemplary example from the subject Basic Statistical Methods of Quality Management is also part of this paper.

  20. Identification of positive selection in disease response genes within members of the Poaceae.

    Science.gov (United States)

    Rech, Gabriel E; Vargas, Walter A; Sukno, Serenella A; Thon, Michael R

    2012-12-01

    Millions of years of coevolution between plants and pathogens can leave footprints on their genomes and genes involved on this interaction are expected to show patterns of positive selection in which novel, beneficial alleles are rapidly fixed within the population. Using information about upregulated genes in maize during Colletotrichum graminicola infection and resources available in the Phytozome database, we looked for evidence of positive selection in the Poaceae lineage, acting on protein coding sequences related with plant defense. We found six genes with evidence of positive selection and another eight with sites showing episodic selection. Some of them have already been described as evolving under positive selection, but others are reported here for the first time including genes encoding isocitrate lyase, dehydrogenases, a multidrug transporter, a protein containing a putative leucine-rich repeat and other proteins with unknown functions. Mapping positively selected residues onto the predicted 3-D structure of proteins showed that most of them are located on the surface, where proteins are in contact with other molecules. We present here a set of Poaceae genes that are likely to be involved in plant defense mechanisms and have evidence of positive selection. These genes are excellent candidates for future functional validation.

  1. Mutant acetolactate synthase (ALS) gene as a selectable marker for Agrobacterium-mediated transformation of soybean

    Institute of Scientific and Technical Information of China (English)

    Chen Shiyun; Zhang Yong

    2006-01-01

    Soybean is one of the crops most difficult to be manipulated in vitro. Although several soybean transformation systems with different selectable marker genes have been reported, e.g. antibiotic (kanamycin or hygromycin) resistant genes and herbicide ( glufosinate, glyphosate) resistant selectable marker genes, all the selectable markers used were from bacteria origin. To find suitable selectable marker gene from plant origin for soybean transformation, a mutant acetolactate synthase (ALS) gene from Arabidopsis thaliana was tested for Agrobacterium-mediated soybean embryo axis transformation with the herbicide Arsenal as the selective agent. Transgenic soybean plants were obtained after the herbicide selection and the To transgenic lines showed resistance to the herbicide at a concentration of 100 g/ha. ALS enzyme assay of To transgenic line also showed higher activity compared to the wild type control plant.PCR analysis of the T1 transgenic lines confirmed the integration and segregation of the transgene. Taken together, our results showed that the mutant ALS gene is a suitable selectable marker for soybean transformation.

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

    Directory of Open Access Journals (Sweden)

    Chris Cheadle

    2007-01-01

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

  3. Relationship of Source Selection Methods to Contract Outcomes: An Analysis of Air Force Source Selection

    Science.gov (United States)

    2015-12-01

    LIST OF REFERENCES Albano, J. D. (2013). The contract management body of knowledge : A comparison of contracting competencies (Master’s thesis). Naval...Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY...improvement initiative, our research focuses on the contract management process, with special emphasis on the source selection methods of tradeoff and

  4. Polycistronic strategy for cyanobacterial expression vector construction: Co-transcription of a human gene and a selective marker gene

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yukun; SHI Dingji; ZHAO Feifei; YU Meimin; RU Binggen

    2005-01-01

    A polycistronic expression vector, pKGA-NTF1, was constructed for the cyanobacterium. Within this vector, the spectinomycin/streptomycin resistance gene (aadA) facilitated the selection of transformants when co-transcribed with favorite genes. A natural glnA gene was selected as the platform to introduce the plasmid into a neutral site of the Synechococcus sp. PCC 7002 chromosome. Function of the vector was demonstrated by the insertion of a modified human Trefoil factor 3 gene (NTF1 ) to upstream of the aadA gene and by the analyses of the transformed strains. Antibiotics resistance assays showed that the dicistronic expression cassette conferred high spectinomycin resistance to both the E. coli cells and the Synechococcus cells. PCR analysis and Western-blot analysis were carried out to confirm the integration and expression of the NTF1 gene, respectively. Through simple molecular manipulations, the artificial polycistronic structure described here can be conveniently used to express other favorable genes or operons in cyanobacteria, and to study the cyanobacterial gene expression as well.

  5. Selective Landscapes in newt Immune Genes Inferred from Patterns of Nucleotide Variation.

    Science.gov (United States)

    Fijarczyk, Anna; Dudek, Katarzyna; Babik, Wieslaw

    2016-12-31

    Host-pathogen interactions may result in either directional selection or in pressure for the maintenance of polymorphism at the molecular level. Hence signatures of both positive and balancing selection are expected in immune genes. Because both overall selective pressure and specific targets may differ between species, large-scale population genomic studies are useful in detecting functionally important immune genes and comparing selective landscapes between taxa. Such studies are of particular interest in amphibians, a group threatened worldwide by emerging infectious diseases. Here, we present an analysis of polymorphism and divergence of 634 immune genes in two lineages of Lissotriton newts: L. montandoni and L. vulgaris graecus Variation in newt immune genes has been shaped predominantly by widespread purifying selection and strong evolutionary constraint, implying long-term importance of these genes for functioning of the immune system. The two evolutionary lineages differ in the overall strength of purifying selection which can partially be explained by demographic history but may also signal differences in long-term pathogen pressure. The prevalent constraint notwithstanding, 23 putative targets of positive selection and 11 putative targets of balancing selection were identified. The latter were detected by composite tests involving the demographic model and further validated in independent population samples. Putative targets of balancing selection encode proteins which may interact closely with pathogens but include also regulators of immune response. The identified candidates will be useful for testing whether genes affected by balancing selection are more prone to interspecific introgression than other genes in the genome. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  6. Detection of selective antibacterial peptides by the Polarity Profile method.

    Science.gov (United States)

    Polanco, Carlos; Buhse, Thomas; Samaniego, José Lino; Castañón-González, Jorge Alberto

    2013-01-01

    Antimicrobial peptides occupy a prominent place in the production of pharmaceuticals, because of their effective contribution to the protection of the immune system against almost all types of pathogens. These peptides are thoroughly studied by computational methods designed to shed light on their main functions. In this paper, we propose a computational approach, named the Polarity Profile method that represents an improvement to the former Polarity Index method. The Polarity Profile method is very effective in detecting the subgroup of antibacterial peptides called selective cationic amphipathic antibacterial peptides (SCAAP) that show high toxicity towards bacterial membranes and exhibit almost zero toxicity towards mammalian cells. Our study was restricted to the peptides listed in the antimicrobial peptides database (APD2) of December 19, 2012. Performance of the Polarity Profile method is demonstrated through a comparison to the former Polarity Index method by using the same sets of peptides. The efficiency of the Polarity Profile method exceeds 85% taking into account the false positive and/or false negative peptides.

  7. Unfolding the mystery of alternative splicing through a unique method of in vivo selection.

    Science.gov (United States)

    Singh, Ravindra N

    2007-05-01

    Alternative splicing of pre-messenger RNA (pre-mRNA) is a fundamental mechanism of gene regulation in higher eukaryotes. In addition to creating protein diversity, alternative splicing provides the safest mode of gene evolution. Of late, more and more forms of alternatively spliced transcripts (mRNAs) are being discovered for key genes. Some of the alternatively spliced transcripts are also associated with major human diseases. This has created a sense of urgency to find the methods by which regulation of alternative splicing of specific exons could be best understood. Here I review a powerful in vivo selection method that uses a combinatorial library of partially random sequences. Several advantages of this method include in vivo analysis of large sequences, identification of unique sequence motifs, determination of relative strength of splice sites and identification of long-distance interactions including role of RNA structures. This unique method could be applied to identify tissue-specific cis-elements. Similarly, the method is suitable to find cis-elements that become active in response to specific treatments of cells. Considering this unbiased method uses in vivo conditions, it has potential to identify critical regulatory elements as therapeutic targets for a growing number of splicing-associated diseases.

  8. Immune clonal selection optimization method with combining mutation strategies

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination mutation operator of Gaussian and Cauchy mutation is presented in this paper, and a novel clonal selection optimization method based on clonal selection principle is proposed also. The simulation results show the combining mutation strategy can obtain the same performance as the best of pure strategies or even better in some cases.

  9. Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca

    OpenAIRE

    2013-01-01

    Real-time quantitative PCR is a powerful technique for the investigation of comparative gene expression, but its accuracy and reliability depend on the reference genes used as internal standards. Only genes that show a high level of expression stability are suitable for use as reference genes, and these must be identified on a case-by-case basis. Erythroxylum coca produces and accumulates high amounts of the pharmacologically active tropane alkaloid cocaine (especially in the leaves), and is ...

  10. Validated spectrofluorimetric method for determination of selected aminoglycosides

    Science.gov (United States)

    Omar, Mahmoud A.; Ahmed, Hytham M.; Hammad, Mohamed A.; Derayea, Sayed M.

    2015-01-01

    New, sensitive, and selective spectrofluorimetric method was developed for determination of three aminoglycoside drugs in different dosage forms, namely; neomycin sulfate (NEO), tobramycin (TOB) and kanamycin sulfate (KAN). The method is based on Hantzsch condensation reaction between the primary amino group of aminoglycosides with acetylacetone and formaldehyde in pH 2.7 yielding highly yellow fluorescent derivatives measured emission (471 nm) and excitation (410 nm) wavelengths. The fluorescence intensity was directly proportional to the concentration over the range 10-60, 40-100 and 5-50 ng/mL for NEO, TOB and KAN respectively. The proposed method was applied successfully for determination of these drugs in their pharmaceutical dosage forms.

  11. Assessing and selecting gene expression signals based upon the quality of the measured dynamics

    Directory of Open Access Journals (Sweden)

    Androulakis Ioannis P

    2009-02-01

    Full Text Available Abstract Background One of the challenges with modeling the temporal progression of biological signals is dealing with the effect of noise and the limited number of replicates at each time point. Given the rising interest in utilizing predictive mathematical models to describe the biological response of an organism or analysis such as clustering and gene ontology enrichment, it is important to determine whether the dynamic progression of the data has been accurately captured despite the limited number of replicates, such that one can have confidence that the results of the analysis are capturing important salient dynamic features. Results By pre-selecting genes based upon quality before the identification of differential expression via algorithm such as EDGE, it was found that the percentage of statistically enriched ontologies (p Conclusion We have developed an algorithm that quantifies the quality of temporal biological signal rather than whether the signal illustrates a significant change over the experimental time course. Because the use of these temporal signals, whether it is in mathematical modeling or clustering, focuses upon the entire time series, it is necessary to develop a method to quantify and select for signals which conform to this ideal. By doing this, we have demonstrated a marked and consistent improvement in the results of a clustering exercise over multiple experiments, microarray platforms, and experimental designs.

  12. Antimicrobial Peptide-PNA Conjugates Selectively Targeting Bacterial Genes

    Science.gov (United States)

    2013-07-22

    change, (Good, 2000). In the case of MRSA, RNA polymerase σ⁷⁷ (encoded by gene rpoD) is a conserved prokaryotic factor essential for transcription...silencing technology to bacteria is the inefficient entry of PNAs into the targeted cell due to restrictions imposed by the bacterial membrane . Peptide...AMP and (RW)3, a linear hexameric peptide, both designed in our lab, interact with wall polymers and cause penetration of the cell membrane at sub

  13. Classification of Cancer Gene Selection Using Random Forest and Neural Network Based Ensemble Classifier

    Directory of Open Access Journals (Sweden)

    Jogendra Kushwah

    2013-06-01

    Full Text Available The free radical gene classification of cancerdiseasesis challenging job in biomedical dataengineering. The improving of classification of geneselection of cancer diseases various classifier areused, but the classification of classifier are notvalidate. So ensemble classifier is used for cancergene classification using neural network classifierwith random forest tree. The random forest tree isensembling technique of classifier in this techniquethe number of classifier ensemble of their leaf nodeof class of classifier. In this paper we combinedneuralnetwork with random forest ensembleclassifier for classification of cancer gene selectionfor diagnose analysis of cancer diseases.Theproposed method is different from most of themethods of ensemble classifier, which follow aninput output paradigm ofneural network, where themembers of the ensemble are selected from a set ofneural network classifier. the number of classifiersis determined during the rising procedure of theforest. Furthermore, the proposed method producesan ensemble not only correct, but also assorted,ensuring the two important properties that shouldcharacterize an ensemble classifier. For empiricalevaluation of our proposed method we used UCIcancer diseases data set for classification. Ourexperimental result shows that betterresult incompression of random forest tree classification

  14. Tetracycline resistance genes persist in soil amended with cattle feces independently from chlortetracycline selection pressure

    NARCIS (Netherlands)

    Kyselkova, Martina; Kotrbova, Lucie; Bhumibhamon, Gamonsiri; Chronakova, Alica; Jirout, Jiri; Vrchotova, Nadezda; Schmitt, Heike; Elhottova, Dana

    2015-01-01

    Antibiotic residues and antibiotic resistance genes originating from animal waste represent environmental pollutants with possible human health consequences. In this study, we addressed the question whether chlortetracycline (CTC) residues in soils can act as selective pressure enhancing the persist

  15. Selection of reference genes for qPCR in hairy root cultures of peanut

    Directory of Open Access Journals (Sweden)

    Medrano Giuliana

    2011-10-01

    Full Text Available Abstract Background Hairy root cultures produced via Agrobacterium rhizogenes-mediated transformation have emerged as practical biological models to elucidate the biosynthesis of specialized metabolites. To effectively understand the expression patterns of the genes involved in the metabolic pathways of these compounds, reference genes need to be systematically validated under specific experimental conditions as established by the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines. In the present report we describe the first validation of reference genes for RT-qPCR in hairy root cultures of peanut which produce stilbenoids upon elicitor treatments. Results A total of 21 candidate reference genes were evaluated. Nineteen genes were selected based on previous qPCR studies in plants and two were from the T-DNAs transferred from A. rhizogenes. Nucleotide sequences of peanut candidate genes were obtained using their homologous sequences in Arabidopsis. To identify the suitable primers, calibration curves were obtained for each candidate reference gene. After data analysis, 12 candidate genes meeting standard efficiency criteria were selected. The expression stability of these genes was analyzed using geNorm and NormFinder algorithms and a ranking was established based on expression stability of the genes. Candidate reference gene expression was shown to have less variation in methyl jasmonate (MeJA treated root cultures than those treated with sodium acetate (NaOAc. Conclusions This work constitutes the first effort to validate reference genes for RT-qPCR in hairy roots. While these genes were selected under conditions of NaOAc and MeJA treatment, we anticipate these genes to provide good targets for reference genes for hairy roots under a variety of stress conditions. The lead reference genes were a gene encoding for a TATA box binding protein (TBP2 and a gene encoding a ribosomal protein (RPL8C. A

  16. Genomic consequences of selection on self-incompatibility genes

    DEFF Research Database (Denmark)

    Schierup, Mikkel Heide; Vekemans, Xavier

    2008-01-01

    Frequency-dependent selection at plant self-incompatibility systems is inherent and well understood theoretically. A self-incompatibility locus leads to a strong peak of diversity in the genome, to a unique distribution of diversity across the species and possibly to increased introgression between...

  17. SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles.

    Science.gov (United States)

    Li, Xiaobo; Peng, Sihua; Chen, Jian; Lü, Bingjian; Zhang, Honghe; Lai, Maode

    2012-03-09

    Although metastasis is the principal cause of death cause for colorectal cancer (CRC) patients, the molecular mechanisms underlying CRC metastasis are still not fully understood. In an attempt to identify metastasis-related genes in CRC, we obtained gene expression profiles of 55 early stage primary CRCs, 56 late stage primary CRCs, and 34 metastatic CRCs from the expression project in Oncology (http://www.intgen.org/expo/). We developed a novel gene selection algorithm (SVM-T-RFE), which extends support vector machine recursive feature elimination (SVM-RFE) algorithm by incorporating T-statistic. We achieved highest classification accuracy (100%) with smaller gene subsets (10 and 6, respectively), when classifying between early and late stage primary CRCs, as well as between metastatic CRCs and late stage primary CRCs. We also compared the performance of SVM-T-RFE and SVM-RFE gene selection algorithms on another large-scale CRC dataset and the five public microarray datasets. SVM-T-RFE bestowed SVM-RFE algorithm in identifying more differentially expressed genes, and achieving highest prediction accuracy using equal or smaller number of selected genes. A fraction of selected genes have been reported to be associated with CRC development or metastasis.

  18. Gene targeting in the red alga Cyanidioschyzon merolae: single- and multi-copy insertion using authentic and chimeric selection markers.

    Science.gov (United States)

    Fujiwara, Takayuki; Ohnuma, Mio; Yoshida, Masaki; Kuroiwa, Tsuneyoshi; Hirano, Tatsuya

    2013-01-01

    The unicellular red alga Cyanidioschyzon merolae is an emerging model organism for studying organelle division and inheritance: the cell is composed of an extremely simple set of organelles (one nucleus, one mitochondrion and one chloroplast), and their genomes are completely sequenced. Although a fruitful set of cytological and biochemical methods have now been developed, gene targeting techniques remain to be fully established in this organism. Thus far, only a single selection marker, URA Cm-Gs , has been available that complements the uracil-auxotrophic mutant M4. URA Cm-Gs , a chimeric URA5.3 gene of C. merolae and the related alga Galdieria sulphuraria, was originally designed to avoid gene conversion of the mutated URA5.3 allele in the parental strain M4. Although an early example of targeted gene disruption by homologous recombination was reported using this marker, the genome structure of the resultant transformants had never been fully characterized. In the current study, we showed that the use of the chimeric URA Cm-Gs selection marker caused multicopy insertion at high frequencies, accompanied by undesired recombination events at the targeted loci. The copy number of the inserted fragments was variable among the transformants, resulting in high yet uneven levels of transgene expression. In striking contrast, when the authentic URA5.3 gene (URA Cm-Cm ) was used as a selection marker, efficient single-copy insertion was observed at the targeted locus. Thus, we have successfully established a highly reliable and reproducible method for gene targeting in C. merolae. Our method will be applicable to a number of genetic manipulations in this organism, including targeted gene disruption, replacement and tagging.

  19. Transgenic gene knock-outs: functional genomics and therapeutic target selection.

    Science.gov (United States)

    Harris, S; Foord, S M

    2000-11-01

    The completion of the first draft of the human genome presents both a tremendous opportunity and enormous challenge to the pharmaceutical industry since the whole community, with few exceptions, will soon have access to the same pool of candidate gene sequences from which to select future therapeutic targets. The commercial imperative to select and pursue therapeutically relevant genes from within the overall content of the genome will be particularly intense for those gene families that currently represent the chemically tractable or 'drugable' gene targets. As a consequence the emphasis within exploratory research has shifted towards the evaluation and adoption of technology platforms that can add additional value to the gene selection process, either through functional studies or direct/indirect measures of disease alignment e.g., genetics, differential gene expression, proteomics, tissue distribution, comparative species data etc. The selection of biological targets for the development of potential new medicines relies, in part, on the quality of the in vivo biological data that correlates a particular molecular target with the underlying pathophysiology of a disease. Within the pharmaceutical industry, studies employing transgenic animals and, in particular, animals with specific gene deletions are playing an increasingly important role in the therapeutic target gene selection, drug candidate selection and product development phases of the overall drug discovery process. The potential of phenotypic information from gene knock-outs to contribute to a high-throughput target selection/validation strategy has hitherto been limited by the resources required to rapidly generate and characterise a large number of knock-out transgenics in a timely fashion. The offerings of several companies that provide an opportunity to overcome these hurdles, albeit at a cost, are assessed with respect to the strategic business needs of the pharmaceutical industry.

  20. Selection of reliable reference genes in Caenorhabditis elegans for analysis of nanotoxicity.

    Directory of Open Access Journals (Sweden)

    Yanqiong Zhang

    Full Text Available Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs, the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR. The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1 to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 µg/mL using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans.

  1. Investigation of the molecular relationship between breast cancer and obesity by candidate gene prioritization methods

    Directory of Open Access Journals (Sweden)

    Saba Garshasbi

    2015-10-01

    Full Text Available Background: Cancer and obesity are two major public health concerns. More than 12 million cases of cancer are reported annually. Many reports confirmed obesity as a risk factor for cancer. The molecular relationship between obesity and breast cancer has not been clear yet. The purpose of this study was to investigate priorities of effective genes in the molecular relationship between obesity and breast cancer. Methods: In this study, computer simulation method was used for prioritizing the genes that involved in the molecular links between obesity and breast cancer in laboratory of systems biology and bioinformatics (LBB, Tehran University, Tehran, Iran, from March to July 2014. In this study, ENDEAVOUR software was used for prioritizing the genes and integrating multiple data sources was used for data analysis. Training genes were selected from effective genes in obesity and/or breast cancer. Two groups of candidate genes were selected. The first group was included the existential genes in 5 common region chromosomes (between obesity and breast cancer and the second group was included the results of genes microarray data analysis of research Creighton, et al (In 2012 on patients with breast cancer. The microarray data were analyzed with GER2 software (R online software on GEO website. Finally, both training and candidate genes were entered in ENDEAVOUR software package. Results: The candidate genes were prioritized to four style and five genes in ten of the first priorities were repeated twice. In other word, the outcome of prioritizing of 72 genes (Product of microarray data analysis and genes of 5 common chromosome regions (Between obesity and breast cancer showed, 5 genes (TNFRSF10B, F2, IGFALS, NTRK3 and HSP90B1 were the priorities in the molecular connection between obesity and breast cancer. Conclusion: There are some common genes between breast cancer and obesity. So, molecular relationship is confirmed. In this study the possible effect

  2. DEVELOPMENT OF IMAGE SELECTION METHOD USING GRAPH CUTS

    Directory of Open Access Journals (Sweden)

    T. Fuse

    2016-06-01

    Full Text Available 3D models have been widely used by spread of many available free-software. Additionally, enormous images can be easily acquired, and images are utilized for creating the 3D models recently. The creation of 3D models by using huge amount of images, however, takes a lot of time and effort, and then efficiency for 3D measurement are required. In the efficient strategy, the accuracy of the measurement is also required. This paper develops an image selection method based on network design that means surveying network construction. The proposed method uses image connectivity graph. The image connectivity graph consists of nodes and edges. The nodes correspond to images to be used. The edges connected between nodes represent image relationships with costs as accuracies of orientation elements. For the efficiency, the image connectivity graph should be constructed with smaller number of edges. Once the image connectivity graph is built, the image selection problem is regarded as combinatorial optimization problem and the graph cuts technique can be applied. In the process of 3D reconstruction, low quality images and similar images are also extracted and removed. Through the experiments, the significance of the proposed method is confirmed. It implies potential to efficient and accurate 3D measurement.

  3. Development of Image Selection Method Using Graph Cuts

    Science.gov (United States)

    Fuse, T.; Harada, R.

    2016-06-01

    3D models have been widely used by spread of many available free-software. Additionally, enormous images can be easily acquired, and images are utilized for creating the 3D models recently. The creation of 3D models by using huge amount of images, however, takes a lot of time and effort, and then efficiency for 3D measurement are required. In the efficient strategy, the accuracy of the measurement is also required. This paper develops an image selection method based on network design that means surveying network construction. The proposed method uses image connectivity graph. The image connectivity graph consists of nodes and edges. The nodes correspond to images to be used. The edges connected between nodes represent image relationships with costs as accuracies of orientation elements. For the efficiency, the image connectivity graph should be constructed with smaller number of edges. Once the image connectivity graph is built, the image selection problem is regarded as combinatorial optimization problem and the graph cuts technique can be applied. In the process of 3D reconstruction, low quality images and similar images are also extracted and removed. Through the experiments, the significance of the proposed method is confirmed. It implies potential to efficient and accurate 3D measurement.

  4. Effective gene-viral therapy for telomerase-positive cancers by selective replicative-competent adenovirus combining with endostatin gene

    Institute of Scientific and Technical Information of China (English)

    Zhang Q; Liu C; Jiang M; Fang G; Liu X; Wu M; Qian Q; Nie M; Sham J; Su C; Xue H; Chua D; Wang W; Cui Z; Liu Y

    2005-01-01

    Gene-viral therapy, which uses replication-selective transgene-expressing viruses to manage tumors, can exploit the virtues of gene therapy and virotherapy and overcome the limitations of conventional gene therapy. Using a human telomerase reverse transcriptase-targeted replicative adenovirus as an antiangiogenic gene transfer vector to target new angiogenesis and making use of its unrestrained proliferation are completely new concepts in tumor management. CNHK300-mE is a selective replication transgene-expressing adenovirus constructed to carry mouse endostatin gene therapeutically. Infection with CNHK300-mE was associated with selective replication of the adenovirus and production of mouse endostatin in telomerase-positive cancer cells. Endostatin secreted from a human gastric cell line, SGC-7901, infected with CNHK300-mE was significantly higher than that infected with nonreplicative adenovirus Ad-mE in vitro (800±94.7 ng/ml versus 132.9±9.9 ng/ml) and in vivo (610±42 ng/ml versus 126 +/- 13 ng/ml). Embryonic chorioallantoic membrane assay showed that the mouse endostatin secreted by CNHK300-mE inhibited angiogenesis efficiently and also induced distortion of pre-existing vasculature. CNHK300-mE exhibited a superior suppression of xenografts in nude mice compared with CNHK300 and Ad-mE. In summary, we provided a more efficient gene-viral therapy strategy by combining oncolysis with antiangiogenesis.

  5. Positive selection in the adhesion domain of Mus sperm Adam genes through gene duplications and function-driven gene complex formations.

    Science.gov (United States)

    Grayson, Phil; Civetta, Alberto

    2013-09-30

    Sperm and testes-expressed Adam genes have been shown to undergo bouts of positive selection in mammals. Despite the pervasiveness of positive selection signals, it is unclear what has driven such selective bouts. The fact that only sperm surface Adam genes show signals of positive selection within their adhesion domain has led to speculation that selection might be driven by species-specific adaptations to fertilization or sperm competition. Alternatively, duplications and neofunctionalization of Adam sperm surface genes, particularly as it is now understood in rodents, might have contributed to an acceleration of evolutionary rates and possibly adaptive diversification. Here we sequenced and conducted tests of selection within the adhesion domain of sixteen known sperm-surface Adam genes among five species of the Mus genus. We find evidence of positive selection associated with all six Adam genes known to interact to form functional complexes on Mus sperm. A subset of these complex-forming sperm genes also displayed accelerated branch evolution with Adam5 evolving under positive selection. In contrast to our previous findings in primates, selective bouts within Mus sperm Adams showed no associations to proxies of sperm competition. Expanded phylogenetic analysis including sequence data from other placental mammals allowed us to uncover ancient and recent episodes of adaptive evolution. The prevailing signals of rapid divergence and positive selection detected within the adhesion domain of interacting sperm Adams is driven by duplications and potential neofunctionalizations that are in some cases ancient (Adams 2, 3 and 5) or more recent (Adams 1b, 4b and 6).

  6. Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.).

    Science.gov (United States)

    Mariot, Roberta Fogliatto; de Oliveira, Luisa Abruzzi; Voorhuijzen, Marleen M; Staats, Martijn; Hutten, Ronald C B; Van Dijk, Jeroen P; Kok, Esther; Frazzon, Jeverson

    2015-01-01

    Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

  7. Selection of Reference Genes for Transcriptional Analysis of Edible Tubers of Potato (Solanum tuberosum L.)

    Science.gov (United States)

    Voorhuijzen, Marleen M.; Staats, Martijn; Hutten, Ronald C. B.; Van Dijk, Jeroen P.; Kok, Esther; Frazzon, Jeverson

    2015-01-01

    Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples. PMID:25830330

  8. ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

    Directory of Open Access Journals (Sweden)

    Brett A McKinney

    Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to

  9. ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

    Science.gov (United States)

    McKinney, Brett A; White, Bill C; Grill, Diane E; Li, Peter W; Kennedy, Richard B; Poland, Gregory A; Oberg, Ann L

    2013-01-01

    Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main

  10. Genome-wide analysis of positively selected genes in seasonal and non-seasonal breeding species.

    Directory of Open Access Journals (Sweden)

    Yuhuan Meng

    Full Text Available Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.

  11. Rough sets selected methods and applications in management and engineering

    CERN Document Server

    Peters, Georg; lzak, Dominik

    2012-01-01

    Rough Set Theory, introduced by Pawlak in the early 1980s, has become an important part of soft computing within the last 25 years. However, much of the focus has been on the theoretical understanding of Rough Sets, with a survey of Rough Sets and their applications within business and industry much desired. Rough Sets: Selected Methods and Applications in Management and Engineering provides context to Rough Set theory, with each chapter exploring a real-world application of Rough Sets. Rough Sets is relevant to managers striving to improve their businesses, industry researchers looking to imp

  12. Selection of renewable energy project using Multicriteria Method

    Directory of Open Access Journals (Sweden)

    DADDA Afaf1 , OUHBI Brahim1

    2015-10-01

    Full Text Available Nowadays, many investors are interesting on implementing new renewable energy project around the world. The success of the decision making process regarding the selection of this projects, depends a lot on the effectiveness of the feasibility stage. During last decades, it is observed that many researches had used the Multicriteria Decision Making Methods to assist decision makers. Therefore, this paper proposes a comparative study of a three decision making process, applied in different countries. This study compares the related process in different levels. A new process is also proposed to validate a local renewable energy project

  13. ANMM4CBR: a case-based reasoning method for gene expression data classification

    Directory of Open Access Journals (Sweden)

    Li Shao

    2010-01-01

    Full Text Available Abstract Background Accurate classification of microarray data is critical for successful clinical diagnosis and treatment. The "curse of dimensionality" problem and noise in the data, however, undermines the performance of many algorithms. Method In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data. Results The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM and k nearest neighbor (kNN, especially when the data contains a high level of noise. Availability The source code is attached as an additional file of this paper.

  14. Genetic transformation of apple (Malus x domestica) without use of a selectable marker gene

    Science.gov (United States)

    Selectable marker genes are widely used for the efficient transformation of crop plants. In most cases, antibiotic or herbicide resistance marker genes are preferred, because they tend to be most efficient. Due mainly to consumer and grower concerns, considerable effort is being put into developin...

  15. Use of the alr gene as a food-grade selection marker in lactic acid bacteria

    NARCIS (Netherlands)

    Bron, P.A.; Benchimol, M.G.; Lambert, J.; Palumbo, E.; Deghorain, M.; Delcour, J.; Vos, de W.M.; Kleerebezem, M.; Hols, P.

    2002-01-01

    Both Lactococcus lactis and Lactobacillus plantarum contain a single alr gene, encoding an alanine racemase (EC 5.1.1.1), which catalyzes the interconversion of D-alanine and L-alanine. The alr genes of these lactic acid bacteria were investigated for their application as food-grade selection marker

  16. Natural selection on protein-coding genes in the human genome

    DEFF Research Database (Denmark)

    Bustamente, Carlos D.; Fledel-Alon, Adi; Williamson, Scott

    2005-01-01

    Comparisons of DNA polymorphism within species to divergence between species enables the discovery of molecular adaptation in evolutionarily constrained genes as well as the differentiation of weak from strong purifying selection 1, 2, 3, 4 . The extent to which weak negative and positive darwini......, show an excess of rapidly evolving genes, whereas others, such as cytoskeletal proteins, show an excess of genes with extensive amino acid polymorphism within humans and yet little amino acid divergence between humans and chimpanzees....

  17. Reliable Selection and Holistic Stability Evaluation of Reference Genes for Rice Under 22 Different Experimental Conditions.

    Science.gov (United States)

    Wang, Zhaohai; Wang, Ya; Yang, Jing; Hu, Keke; An, Baoguang; Deng, Xiaolong; Li, Yangsheng

    2016-07-01

    Stable and uniform expression of reference genes across samples plays a key role in accurate normalization of gene expression by reverse-transcription quantitative polymerase chain reaction (RT-qPCR). For rice study, there is still a lack of validation and recommendation of appropriate reference genes with high stability depending on experimental conditions. Eleven candidate reference genes potentially owning high stability were evaluated by geNorm and NormFinder for their expression stability in 22 various experimental conditions. Best combinations of multiple reference genes were recommended depending on experimental conditions, and the holistic stability of reference genes was also evaluated. Reference genes would become more variable and thus needed to be critically selected in experimental groups of tissues, heat, 6-benzylamino purine, and drought, but they were comparatively stable under cold, wound, and ultraviolet-B stresses. Triosephosphate isomerase (TI), profilin-2 (Profilin-2), ubiquitin-conjugating enzyme E2 (UBC), endothelial differentiation factor (Edf), and ADP-ribosylation factor (ARF) were stable in most of our experimental conditions. No universal reference gene showed good stability in all experimental conditions. To get accurate expression result, suitable combination of multiple reference genes for a specific experimental condition would be a better choice. This study provided an application guideline to select stable reference genes for rice gene expression study.

  18. "Every Gene Is Everywhere but the Environment Selects": Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis.

    Science.gov (United States)

    Fondi, Marco; Karkman, Antti; Tamminen, Manu V; Bosi, Emanuele; Virta, Marko; Fani, Renato; Alm, Eric; McInerney, James O

    2016-05-13

    The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as "everything is everywhere but the environment selects." While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge.

  19. Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies.

    Science.gov (United States)

    Cheng, Changde; Kirkpatrick, Mark

    2016-09-01

    Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive "Twin Peaks" pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.

  20. Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies.

    Directory of Open Access Journals (Sweden)

    Changde Cheng

    2016-09-01

    Full Text Available Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive "Twin Peaks" pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.

  1. Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca.

    Science.gov (United States)

    Docimo, Teresa; Schmidt, Gregor W; Luck, Katrin; Delaney, Sven K; D'Auria, John C

    2013-01-01

    Real-time quantitative PCR is a powerful technique for the investigation of comparative gene expression, but its accuracy and reliability depend on the reference genes used as internal standards. Only genes that show a high level of expression stability are suitable for use as reference genes, and these must be identified on a case-by-case basis. Erythroxylum coca produces and accumulates high amounts of the pharmacologically active tropane alkaloid cocaine (especially in the leaves), and is an emerging model for the investigation of tropane alkaloid biosynthesis. The identification of stable internal reference genes for this species is important for its development as a model species, and would enable comparative analysis of candidate biosynthetic genes in the different tissues of the coca plant. In this study, we evaluated the expression stability of nine candidate reference genes in E. coca ( Ec6409, Ec10131, Ec11142, Actin, APT2, EF1α, TPB1, Pex4, Pp2aa3). The expression of these genes was measured in seven tissues (flowers, stems, roots and four developmental leaf stages) and the stability of expression was assessed using three algorithms (geNorm, NormFinder and BestKeeper). From our results we conclude that Ec10131 and TPB1 are the most appropriate internal reference genes in leaves (where the majority of cocaine is produced), while Ec10131 and Ec6409 are the most suitable internal reference genes across all of the tissues tested.

  2. Accuracy of multi-trait genomic selection using different methods

    Directory of Open Access Journals (Sweden)

    Veerkamp Roel F

    2011-07-01

    Full Text Available Abstract Background Genomic selection has become a very important tool in animal genetics and is rapidly emerging in plant genetics. It holds the promise to be particularly beneficial to select for traits that are difficult or expensive to measure, such as traits that are measured in one environment and selected for in another environment. The objective of this paper was to develop three models that would permit multi-trait genomic selection by combining scarcely recorded traits with genetically correlated indicator traits, and to compare their performance to single-trait models, using simulated datasets. Methods Three (SNP Single Nucleotide Polymorphism based models were used. Model G and BCπ0 assumed that contributed (covariances of all SNP are equal. Model BSSVS sampled SNP effects from a distribution with large (or small effects to model SNP that are (or not associated with a quantitative trait locus. For reasons of comparison, model A including pedigree but not SNP information was fitted as well. Results In terms of accuracies for animals without phenotypes, the models generally ranked as follows: BSSVS > BCπ0 > G > > A. Using multi-trait SNP-based models, the accuracy for juvenile animals without any phenotypes increased up to 0.10. For animals with phenotypes on an indicator trait only, accuracy increased up to 0.03 and 0.14, for genetic correlations with the evaluated trait of 0.25 and 0.75, respectively. Conclusions When the indicator trait had a genetic correlation lower than 0.5 with the trait of interest in our simulated data, the accuracy was higher if genotypes rather than phenotypes were obtained for the indicator trait. However, when genetic correlations were higher than 0.5, using an indicator trait led to higher accuracies for selection candidates. For different combinations of traits, the level of genetic correlation below which genotyping selection candidates is more effective than obtaining phenotypes for an indicator

  3. Selective Gene Transfer to the Retina Using Intravitreal Ultrasound Irradiation

    Directory of Open Access Journals (Sweden)

    Shozo Sonoda

    2012-01-01

    Full Text Available This paper aims to evaluate the efficacy of intravitreal ultrasound (US irradiation for green fluorescent protein (GFP plasmid transfer into the rabbit retina using a miniature US transducer. Intravitreal US irradiation was performed by a slight modification of the transconjunctival sutureless vitrectomy system utilizing a small probe. After vitrectomy, the US probe was inserted through a scleral incision. A mixture of GFP plasmid (50 μL and bubble liposomes (BLs; 50 μL was injected into the vitreous cavity, and US was generated to the retina using a SonoPore 4000. The control group was not exposed to US. After 72 h, the gene-transfer efficiency was quantified by counting the number of GFP-positive cells. The retinas that received plasmid, BL, and US showed a significant increase in the number (average ± SEM of GFP-positive cells (32±4.9; n=7; P<0.01 . No GFP-positive cells were observed in the control eyes (n=7. Intravitreal retinal US irradiation can transfer the GFP plasmid into the retina without causing any apparent damage. This procedure could be used to transfer genes and drugs directly to the retina and therefore has potential therapeutic value.

  4. Duration and speed of speech events: A selection of methods

    Directory of Open Access Journals (Sweden)

    Gibbon Dafydd

    2015-07-01

    Full Text Available The study of speech timing, i.e. the duration and speed or tempo of speech events, has increased in importance over the past twenty years, in particular in connection with increased demands for accuracy, intelligibility and naturalness in speech technology, with applications in language teaching and testing, and with the study of speech timing patterns in language typology. H owever, the methods used in such studies are very diverse, and so far there is no accessible overview of these methods. Since the field is too broad for us to provide an exhaustive account, we have made two choices: first, to provide a framework of paradigmatic (classificatory, syntagmatic (compositional and functional (discourse-oriented dimensions for duration analysis; and second, to provide worked examples of a selection of methods associated primarily with these three dimensions. Some of the methods which are covered are established state-of-the-art approaches (e.g. the paradigmatic Classification and Regression Trees, CART , analysis, others are discussed in a critical light (e.g. so-called ‘rhythm metrics’. A set of syntagmatic approaches applies to the tokenisation and tree parsing of duration hierarchies, based on speech annotations, and a functional approach describes duration distributions with sociolinguistic variables. Several of the methods are supported by a new web-based software tool for analysing annotated speech data, the Time Group Analyser.

  5. "Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

    Science.gov (United States)

    Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

    2008-02-01

    The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed

  6. Proposed optimal LSP selection method in MPLS networks

    CERN Document Server

    Kuribayashi, Shin-ichi

    2012-01-01

    Multi-Protocol Label Switching (MPLS) had been deployed by many data networking service providers, including the next-generation mobile backhaul networks, because of its undeniable potential in terms of virtual private network (VPN) management, traffic engineering, etc. In MPLS networks, IP packets are transmitted along a Label Switched Path (LSP) established between edge nodes. To improve the efficiency of resource use in MPLS networks, it is essential to utilize the LSPs efficiently. This paper proposes a method of selecting the optimal LSP pair from among multiple LSP pairs which are established between the same pair of edge nodes, on the assumption that both the upward and downward LSPs are established as a pair (both-way operation). It is supposed that both upward and downward bandwidths are allocated simultaneously in the selected LSP pair for each service request. It is demonstrated by simulation evaluations that the proposal method could reduce the total amount of the bandwidth required by up to 15% c...

  7. A Successive Selection Method for finite element model updating

    Science.gov (United States)

    Gou, Baiyong; Zhang, Weijie; Lu, Qiuhai; Wang, Bo

    2016-03-01

    Finite Element (FE) model can be updated effectively and efficiently by using the Response Surface Method (RSM). However, it often involves performance trade-offs such as high computational cost for better accuracy or loss of efficiency for lots of design parameter updates. This paper proposes a Successive Selection Method (SSM), which is based on the linear Response Surface (RS) function and orthogonal design. SSM rewrites the linear RS function into a number of linear equations to adjust the Design of Experiment (DOE) after every FE calculation. SSM aims to interpret the implicit information provided by the FE analysis, to locate the Design of Experiment (DOE) points more quickly and accurately, and thereby to alleviate the computational burden. This paper introduces the SSM and its application, describes the solution steps of point selection for DOE in detail, and analyzes SSM's high efficiency and accuracy in the FE model updating. A numerical example of a simply supported beam and a practical example of a vehicle brake disc show that the SSM can provide higher speed and precision in FE model updating for engineering problems than traditional RSM.

  8. Reference gene selection for gene expression analysis of oocytes collected from dairy cattle and buffaloes during winter and summer.

    Directory of Open Access Journals (Sweden)

    Carolina Habermann Macabelli

    Full Text Available Oocytes from dairy cattle and buffaloes have severely compromised developmental competence during summer. While analysis of gene expression is a powerful technique for understanding the factors affecting developmental hindrance in oocytes, analysis by real-time reverse transcription PCR (RT-PCR relies on the correct normalization by reference genes showing stable expression. Furthermore, several studies have found that genes commonly used as reference standards do not behave as expected depending on cell type and experimental design. Hence, it is recommended to evaluate expression stability of candidate reference genes for a specific experimental condition before employing them as internal controls. In acknowledgment of the importance of seasonal effects on oocyte gene expression, the aim of this study was to evaluate the stability of expression levels of ten well-known reference genes (ACTB, GAPDH, GUSB, HIST1H2AG, HPRT1, PPIA, RPL15, SDHA, TBP and YWHAZ using oocytes collected from different categories of dairy cattle and buffaloes during winter and summer. A normalization factor was provided for cattle (RPL15, PPIA and GUSB and buffaloes (YWHAZ, GUSB and GAPDH based on the expression of the three most stable reference genes in each species. Normalization of non-reference target genes by these reference genes was shown to be considerably different from normalization by less stable reference genes, further highlighting the need for careful selection of internal controls. Therefore, due to the high variability of reference genes among experimental groups, we conclude that data normalized by internal controls can be misleading and should be compared to not normalized data or to data normalized by an external control in order to better interpret the biological relevance of gene expression analysis.

  9. Reference Gene Selection for Gene Expression Analysis of Oocytes Collected from Dairy Cattle and Buffaloes during Winter and Summer

    Science.gov (United States)

    Gimenes, Lindsay Unno; de Carvalho, Nelcio Antonio Tonizza; Soares, Júlia Gleyci; Ayres, Henderson; Ferraz, Márcio Leão; Watanabe, Yeda Fumie; Watanabe, Osnir Yoshime; Sangalli, Juliano Rodrigues; Smith, Lawrence Charles; Baruselli, Pietro Sampaio; Meirelles, Flávio Vieira; Chiaratti, Marcos Roberto

    2014-01-01

    Oocytes from dairy cattle and buffaloes have severely compromised developmental competence during summer. While analysis of gene expression is a powerful technique for understanding the factors affecting developmental hindrance in oocytes, analysis by real-time reverse transcription PCR (RT-PCR) relies on the correct normalization by reference genes showing stable expression. Furthermore, several studies have found that genes commonly used as reference standards do not behave as expected depending on cell type and experimental design. Hence, it is recommended to evaluate expression stability of candidate reference genes for a specific experimental condition before employing them as internal controls. In acknowledgment of the importance of seasonal effects on oocyte gene expression, the aim of this study was to evaluate the stability of expression levels of ten well-known reference genes (ACTB, GAPDH, GUSB, HIST1H2AG, HPRT1, PPIA, RPL15, SDHA, TBP and YWHAZ) using oocytes collected from different categories of dairy cattle and buffaloes during winter and summer. A normalization factor was provided for cattle (RPL15, PPIA and GUSB) and buffaloes (YWHAZ, GUSB and GAPDH) based on the expression of the three most stable reference genes in each species. Normalization of non-reference target genes by these reference genes was shown to be considerably different from normalization by less stable reference genes, further highlighting the need for careful selection of internal controls. Therefore, due to the high variability of reference genes among experimental groups, we conclude that data normalized by internal controls can be misleading and should be compared to not normalized data or to data normalized by an external control in order to better interpret the biological relevance of gene expression analysis. PMID:24676354

  10. Sparse Inverse Covariance Selection via Alternating Linearization Methods

    CERN Document Server

    Scheinberg, Katya; Goldfarb, Donald

    2010-01-01

    Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse covariance matrix of the Gaussian distribution, one can learn the structure of the graph by estimating a sparse inverse covariance matrix from sample data, by solving a convex maximum likelihood problem with an $\\ell_1$-regularization term. In this paper, we propose a first-order method based on an alternating linearization technique that exploits the problem's special structure; in particular, the subproblems solved in each iteration have closed-form solutions. Moreover, our algorithm obtains an $\\epsilon$-optimal solution in $O(1/\\epsilon)$ iterations. Numerical experiments on both synthetic and real data from gene association networks show that a practical version of this algorithm outperforms other competitive algorithms.

  11. ANMM4CBR: a case-based reasoning method for gene expression data classification.

    Science.gov (United States)

    Yao, Bangpeng; Li, Shao

    2010-01-06

    Accurate classification of microarray data is critical for successful clinical diagnosis and treatment. The "curse of dimensionality" problem and noise in the data, however, undermines the performance of many algorithms. In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR) method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR) method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data. The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM) and k nearest neighbor (kNN), especially when the data contains a high level of noise. The source code is attached as an additional file of this paper.

  12. Use of Heat Stress Responsive Gene Expression Levels for Early Selection of Heat Tolerant Cabbage (Brassica oleracea L.

    Directory of Open Access Journals (Sweden)

    Jun Cheul Ahn

    2013-06-01

    Full Text Available Cabbage is a relatively robust vegetable at low temperatures. However, at high temperatures, cabbage has disadvantages, such as reduced disease tolerance and lower yields. Thus, selection of heat-tolerant cabbage is an important goal in cabbage breeding. Easier or faster selection of superior varieties of cabbage, which are tolerant to heat and disease and have improved taste and quality, can be achieved with molecular and biological methods. We compared heat-responsive gene expression between a heat-tolerant cabbage line (HTCL, “HO”, and a heat-sensitive cabbage line (HSCL, “JK”, by Genechip assay. Expression levels of specific heat stress-related genes were increased in response to high-temperature stress, according to Genechip assays. We performed quantitative RT-PCR (qRT-PCR to compare expression levels of these heat stress-related genes in four HTCLs and four HSCLs. Transcript levels for heat shock protein BoHsp70 and transcription factor BoGRAS (SCL13 were more strongly expressed only in all HTCLs compared to all HSCLs, showing much lower level expressions at the young plant stage under heat stress (HS. Thus, we suggest that expression levels of these genes may be early selection markers for HTCLs in cabbage breeding. In addition, several genes that are involved in the secondary metabolite pathway were differentially regulated in HTCL and HSCL exposed to heat stress.

  13. A PCA-based method for ancestral informative markers selection in structured populations

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Identification of population structure can help trace population histories and identify disease genes. Structured association (SA) is a commonly used approach for population structure identification and association mapping. A major issue with SA is that its performance greatly depends on the informa-tiveness and the numbers of ancestral informative markers (AIMs). Present major AIM selection meth-ods mostly require prior individual ancestry information, which is usually not available or uncertain in practice. To address this potential weakness, we herein develop a novel approach for AIM selection based on principle component analysis (PCA), which does not require prior ancestry information of study subjects. Our simulation and real genetic data analysis results suggest that, with equivalent AIMs, PCA-based selected AIMs can significantly increase the accuracy of inferred individual ancestries compared with traditionally randomly selected AIMs. Our method can easily be applied to whole genome data to select a set of highly informative AIMs in population structure, which can then be used to identify potential population structure and correct possible statistical biases caused by population stratification.

  14. A PCA-based method for ancestral informative markers selection in structured populations

    Institute of Scientific and Technical Information of China (English)

    ZHANG Feng; ZHANG Lei; DENG Hong-Wen

    2009-01-01

    Identification of population structure can help trace population histories and identify disease genes.Structured association (SA) is a commonly used approach for population structure identification and association mapping. A major issue with SA is that its performance greatly depends on the informativeness and the numbers of ancestral informative markers (AIMs). Present major AIM selection methods mostly require prior individual ancestry information, which is usually not available or uncertain in practice. To address this potential weakness, we herein develop a novel approach for AIM selection based on principle component analysis (PCA), which does not require prior ancestry information of study subjects. Our simulation and real genetic data analysis results suggest that, with equivalent AIMs,PCA-based selected AIMs can significantly increase the accuracy of inferred individual ancestries compared with traditionally randomly selected AIMs. Our method can easily be applied to whole genome data to select a set of highly informative AIMs in population structure, which can then be used to identify potential population structure and correct possible statistical biases caused by population stratification.

  15. A visual method for direct selection of high-producing Pichia pastoris clones

    Directory of Open Access Journals (Sweden)

    Liu Sheng

    2011-03-01

    Full Text Available Abstract Background The methylotrophic yeast, Pichia pastoris, offers the possibility to generate a high amount of recombinant proteins in a fast and easy way to use expression system. Being a single-celled microorganism, P. pastoris is easy to manipulate and grows rapidly on inexpensive media at high cell densities. A simple and direct method for the selection of high-producing clones can dramatically enhance the whole production process along with significant decrease in production costs. Results A visual method for rapid selection of high-producing clones based on mannanase reporter system was developed. The study explained that it was possible to use mannanase activity as a measure of the expression level of the protein of interest. High-producing target protein clones were directly selected based on the size of hydrolysis holes in the selected plate. As an example, the target gene (9elp-hal18 was expressed and purified in Pichia pastoris using this technology. Conclusions A novel methodology is proposed for obtaining the high-producing clones of proteins of interest, based on the mannanase reporter system. This system may be adapted to other microorganisms, such as Saccharomyces cerevisiae for the selection of clones.

  16. Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

    Directory of Open Access Journals (Sweden)

    Ye Zhi-Qiang

    2011-08-01

    Full Text Available Abstract Background Differential coexpression analysis (DCEA is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links. Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

  17. Gene expression analysis for the identification of selection and local adaptation in fishes

    DEFF Research Database (Denmark)

    Larsen, Peter Foged; Schulte, P.M.; Eg Nielsen, Einar

    2011-01-01

    In recent years, variation in gene expression has been recognized as an important component of environmental adaptation in multiple model species, including a few fish species. There is, however, still little known about the genetic basis of adaptation in gene expression resulting from variation...... in the aquatic environment (e.g. temperature, salinity and oxygen) and the physiological effect and costs of such differences in gene expression. This review presents and discusses progress and pitfalls of applying gene expression analyses to fishes and suggests simple frameworks to get started with gene...... expression analysis. It is emphasized that well-planned gene expression studies can serve as an important tool for the identification of selection in local populations of fishes, even for non-traditional model species where limited genomic information is available. Recent studies focusing on gene expression...

  18. The roles of gene duplication, gene conversion and positive selection in rodent Esp and Mup pheromone gene families with comparison to the Abp family.

    Science.gov (United States)

    Karn, Robert C; Laukaitis, Christina M

    2012-01-01

    Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus. We studied the evolutionary histories of the Mup and Esp genes and compared them with what is known about the Abp genes. Apparently gene conversion has played little if any role in the expansion of the mouse Class A and Class B Mup genes and pseudogenes, and the rat Mups. By contrast, we found evidence of extensive gene conversion in many Esp genes although not in all of them. Our studies of selection identified at least two amino acid sites in β-sheets as having evolved under positive selection in the mouse Class A and Class B MUPs and in rat MUPs. We show that selection may have acted on the ESPs by determining K(a)/K(s) for Exon 3 sequences with and without the converted sequence segment. While it appears that purifying selection acted on the ESP signal peptides, the secreted portions of the ESPs probably have undergone much more rapid evolution. When the inner gene converted fragment sequences were removed, eleven Esp paralogs were present in two or more pairs with K(a)/K(s) >1.0 and thus we propose that positive selection is detectable by this means in at least some mouse Esp paralogs. We compare and contrast the evolutionary histories of all three mouse pheromone gene families in light of their proposed functions in mouse communication.

  19. Strength and tempo of selection revealed in viral gene genealogies.

    Science.gov (United States)

    Bedford, Trevor; Cobey, Sarah; Pascual, Mercedes

    2011-07-25

    RNA viruses evolve extremely quickly, allowing them to rapidly adapt to new environmental conditions. Viral pathogens, such as influenza virus, exploit this capacity for evolutionary change to persist within the human population despite substantial immune pressure. Understanding the process of adaptation in these viral systems is essential to our efforts to combat infectious disease. Through analysis of simulated populations and sequence data from influenza A (H3N2) and measles virus, we show how phylogenetic and population genetic techniques can be used to assess the strength and temporal pattern of adaptive evolution. The action of natural selection affects the shape of the genealogical tree connecting members of an evolving population, causing deviations from the neutral expectation. The magnitude and distribution of these deviations lends insight into the historical pattern of evolution and adaptation in the viral population. We quantify the degree of ongoing adaptation in influenza and measles virus through comparison of census population size and effective population size inferred from genealogical patterns, finding a 60-fold greater deviation in influenza than in measles. We also examine the tempo of adaptation in influenza, finding evidence for both continuous and episodic change. Our results have important consequences for understanding the epidemiological and evolutionary dynamics of the influenza virus. Additionally, these general techniques may prove useful to assess the strength and pattern of adaptive evolution in a variety of evolving systems. They are especially powerful when assessing selection in fast-evolving populations, where temporal patterns become highly visible.

  20. Strength and tempo of selection revealed in viral gene genealogies

    Directory of Open Access Journals (Sweden)

    Cobey Sarah

    2011-07-01

    Full Text Available Abstract Background RNA viruses evolve extremely quickly, allowing them to rapidly adapt to new environmental conditions. Viral pathogens, such as influenza virus, exploit this capacity for evolutionary change to persist within the human population despite substantial immune pressure. Understanding the process of adaptation in these viral systems is essential to our efforts to combat infectious disease. Results Through analysis of simulated populations and sequence data from influenza A (H3N2 and measles virus, we show how phylogenetic and population genetic techniques can be used to assess the strength and temporal pattern of adaptive evolution. The action of natural selection affects the shape of the genealogical tree connecting members of an evolving population, causing deviations from the neutral expectation. The magnitude and distribution of these deviations lends insight into the historical pattern of evolution and adaptation in the viral population. We quantify the degree of ongoing adaptation in influenza and measles virus through comparison of census population size and effective population size inferred from genealogical patterns, finding a 60-fold greater deviation in influenza than in measles. We also examine the tempo of adaptation in influenza, finding evidence for both continuous and episodic change. Conclusions Our results have important consequences for understanding the epidemiological and evolutionary dynamics of the influenza virus. Additionally, these general techniques may prove useful to assess the strength and pattern of adaptive evolution in a variety of evolving systems. They are especially powerful when assessing selection in fast-evolving populations, where temporal patterns become highly visible.

  1. SELECTING A MANAGEMENT SYSTEM HOSPITAL BY A METHOD MULTICRITERIA

    Directory of Open Access Journals (Sweden)

    Vitorino, Sidney L.

    2016-12-01

    Full Text Available The objective of this report is to assess how the multi-criteria method Analytic Hierarchy Process [HP] can help a hospital complex to choose a more suitable management system, known as Enterprise Resource Planning (ERP. The choice coated is very complex due to the novelty of the process of choosing and conflicts generated between areas that did not have a single view of organizational needs, generating a lot of pressure in the department responsible for implementing systems. To assist in this process, he was hired an expert consultant in decision-making and AHP, which in its role of facilitator, contributed to the criteria for system selection were defined, and the choice to occur within a consensual process. We used the study of a single case, based on two indepth interviews with the consultant and the project manager, and documents generated by the advisory and the tool that supported the method. The results of this analysis showed that the method could effectively collaborate in the system acquisition process, but knowledge of the problems of employees and senior management support, it was not used in new decisions of the organization. We conclude that this method contributed to the consensus in the procurement process, team commitment and engagement of those involved.

  2. Development of an optimal velocity selection method with velocity obstacle

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Geuk; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)

    2015-08-15

    The Velocity obstacle (VO) method is one of the most well-known methods for local path planning, allowing consideration of dynamic obstacles and unexpected obstacles. Typical VO methods separate a velocity map into a collision area and a collision-free area. A robot can avoid collisions by selecting its velocity from within the collision-free area. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method for choosing optimal velocity components using the concept of pass-time and vertical clearance is proposed for the efficient movement of a robot. The pass-time is the time required for a robot to pass by an obstacle. By generating a latticized available velocity map for a robot, each velocity component can be evaluated using a cost function that considers the pass-time and other aspects. From the output of the cost function, even a velocity component that will cause a collision in the future can be chosen as a final velocity if the pass-time is sufficiently long enough.

  3. Transcriptional Activation of Inflammatory Genes: Mechanistic Insight into Selectivity and Diversity.

    Science.gov (United States)

    Ahmed, Afsar U; Williams, Bryan R G; Hannigan, Gregory E

    2015-11-11

    Acute inflammation, an integral part of host defence and immunity, is a highly conserved cellular response to pathogens and other harmful stimuli. An inflammatory stimulation triggers transcriptional activation of selective pro-inflammatory genes that carry out specific functions such as anti-microbial activity or tissue healing. Based on the nature of inflammatory stimuli, an extensive exploitation of selective transcriptional activations of pro-inflammatory genes is performed by the host to ensure a defined inflammatory response. Inflammatory signal transductions are initiated by the recognition of inflammatory stimuli by transmembrane receptors, followed by the transmission of the signals to the nucleus for differential gene activations. The differential transcriptional activation of pro-inflammatory genes is precisely controlled by the selective binding of transcription factors to the promoters of these genes. Among a number of transcription factors identified to date, NF-κB still remains the most prominent and studied factor for its diverse range of selective transcriptional activities. Differential transcriptional activities of NF-κB are dictated by post-translational modifications, specificities in dimer formation, and variability in activation kinetics. Apart from the differential functions of transcription factors, the transcriptional activation of selective pro-inflammatory genes is also governed by chromatin structures, epigenetic markers, and other regulators as the field is continuously expanding.

  4. Positive selection in AvrP4 avirulence gene homologues across the genus Melampsora.

    Science.gov (United States)

    Van der Merwe, Marlien M; Kinnear, Mark W; Barrett, Luke G; Dodds, Peter N; Ericson, Lars; Thrall, Peter H; Burdon, Jeremy J

    2009-08-22

    Pathogen genes involved in interactions with their plant hosts are expected to evolve under positive Darwinian selection or balancing selection. In this study a single copy avirulence gene, AvrP4, in the plant pathogen Melampsora lini, was used to investigate the evolution of such a gene across species. Partial translation elongation factor 1-alpha sequences were obtained to establish phylogenetic relationships among the Melampsora species. We amplified AvrP4 homologues from species pathogenic on hosts from different plant families and orders, across the inferred phylogeny. Translations of the AvrP4 sequences revealed a predicted signal peptide and towards the C-terminus of the protein, six identically spaced cysteines were identified in all sequences. Maximum likelihood analysis of synonymous versus non-synonymous substitution rates indicated that positive selection played a role in the evolution of the gene during the diversification of the genus. Fourteen codons under significant positive selection reside in the C-terminal 28 amino acid region, suggesting that this region interacts with host molecules in most sequenced accessions. Selection pressures on the gene may be either due to the pathogenicity or avirulence function of the gene or both.

  5. Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods

    Directory of Open Access Journals (Sweden)

    Naseer Aisha

    2011-05-01

    Full Text Available Abstract Background There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data. Results The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

  6. Automatic segmentation of brain images: selection of region extraction methods

    Science.gov (United States)

    Gong, Leiguang; Kulikowski, Casimir A.; Mezrich, Reuben S.

    1991-07-01

    In automatically analyzing brain structures from a MR image, the choice of low level region extraction methods depends on the characteristics of both the target object and the surrounding anatomical structures in the image. The authors have experimented with local thresholding, global thresholding, and other techniques, using various types of MR images for extracting the major brian landmarks and different types of lesions. This paper describes specifically a local- binary thresholding method and a new global-multiple thresholding technique developed for MR image segmentation and analysis. The initial testing results on their segmentation performance are presented, followed by a comparative analysis of the two methods and their ability to extract different types of normal and abnormal brain structures -- the brain matter itself, tumors, regions of edema surrounding lesions, multiple sclerosis lesions, and the ventricles of the brain. The analysis and experimental results show that the global multiple thresholding techniques are more than adequate for extracting regions that correspond to the major brian structures, while local binary thresholding is helpful for more accurate delineation of small lesions such as those produced by MS, and for the precise refinement of lesion boundaries. The detection of other landmarks, such as the interhemispheric fissure, may require other techniques, such as line-fitting. These experiments have led to the formulation of a set of generic computer-based rules for selecting the appropriate segmentation packages for particular types of problems, based on which further development of an innovative knowledge- based, goal directed biomedical image analysis framework is being made. The system will carry out the selection automatically for a given specific analysis task.

  7. A method for selecting cis-acting regulatory sequences that respond to small molecule effectors

    Directory of Open Access Journals (Sweden)

    Allas Ülar

    2010-08-01

    Full Text Available Abstract Background Several cis-acting regulatory sequences functioning at the level of mRNA or nascent peptide and specifically influencing transcription or translation have been described. These regulatory elements often respond to specific chemicals. Results We have developed a method that allows us to select cis-acting regulatory sequences that respond to diverse chemicals. The method is based on the β-lactamase gene containing a random sequence inserted into the beginning of the ORF. Several rounds of selection are used to isolate sequences that suppress β-lactamase expression in response to the compound under study. We have isolated sequences that respond to erythromycin, troleandomycin, chloramphenicol, meta-toluate and homoserine lactone. By introducing synonymous and non-synonymous mutations we have shown that at least in the case of erythromycin the sequences act at the peptide level. We have also tested the cross-activities of the constructs and found that in most cases the sequences respond most strongly to the compound on which they were isolated. Conclusions Several selected peptides showed ligand-specific changes in amino acid frequencies, but no consensus motif could be identified. This is consistent with previous observations on natural cis-acting peptides, showing that it is often impossible to demonstrate a consensus. Applying the currently developed method on a larger scale, by selecting and comparing an extended set of sequences, might allow the sequence rules underlying the activity of cis-acting regulatory peptides to be identified.

  8. Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.

    Science.gov (United States)

    Evans, Ciaran; Hardin, Johanna; Stoebel, Daniel M

    2017-02-27

    RNA-Seq is a widely used method for studying the behavior of genes under different biological conditions. An essential step in an RNA-Seq study is normalization, in which raw data are adjusted to account for factors that prevent direct comparison of expression measures. Errors in normalization can have a significant impact on downstream analysis, such as inflated false positives in differential expression analysis. An underemphasized feature of normalization is the assumptions on which the methods rely and how the validity of these assumptions can have a substantial impact on the performance of the methods. In this article, we explain how assumptions provide the link between raw RNA-Seq read counts and meaningful measures of gene expression. We examine normalization methods from the perspective of their assumptions, as an understanding of methodological assumptions is necessary for choosing methods appropriate for the data at hand. Furthermore, we discuss why normalization methods perform poorly when their assumptions are violated and how this causes problems in subsequent analysis. To analyze a biological experiment, researchers must select a normalization method with assumptions that are met and that produces a meaningful measure of expression for the given experiment.

  9. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures

    Science.gov (United States)

    Zhang, Hang; Xie, Ziyang; Yang, Yuwen; Zhao, Yizhen

    2017-01-01

    Microarray analysis of gene expression is often used to diagnose different types of disease. Many studies report remarkable achievements in nervous system disease. Clinical diagnosis of schizophrenia (SCZ) still depends on doctors' experience, which is unreliable and needs to be more objective and quantified. To solve this problem, we collected whole blood gene expression data from four studies, including 152 individuals with schizophrenia (SCZ) and 138 normal controls in different regions. The correlation-based feature selection (CFS, one of the machine learning methods) algorithm was applied in this study, and 103 significantly differentially expressed genes between patients and controls, called “feature genes,” were selected; then, a model for SCZ diagnosis was built. The samples were subdivided into 10 groups, and cross-validation showed that the model we constructed achieved nearly 100% classification accuracy. Mathematical evaluation of the datasets before and after data processing proved the effectiveness of our algorithm. Feature genes were enriched in Parkinson's disease, oxidative phosphorylation, and TGF-beta signaling pathways, which were previously reported to be associated with SCZ. These results suggest that the analysis of gene expression in whole blood by our model could be a useful tool for diagnosing SCZ. PMID:28280741

  10. Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR

    Directory of Open Access Journals (Sweden)

    Longjian Niu

    2015-06-01

    Full Text Available Real-time quantitative PCR (RT-qPCR is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis, a promising oilseed crop known for its polyunsaturated fatty acid (PUFA-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt, BestKeeper, geNorm, and NormFinder were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE, actin (ACT and phospholipase A22 (PLA were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13, cyclophilin (CYC and elongation factor-1alpha (EF1α were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi.

  11. Selection for the compactness of highly expressed genes in Gallus gallus

    Directory of Open Access Journals (Sweden)

    Zhou Ming

    2010-05-01

    Full Text Available Abstract Background Coding sequence (CDS length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure. Results Based on different technologies, we gathered expression data for nuclear protein coding, single-splicing genes from Gallus gallus genome and compared them with gene parameters. We found that gene size, CDS length, first intron length, average intron length, and total intron length are negatively correlated with expression level and expression breadth significantly. The tissue specificity is positively correlated with the first intron length but negatively correlated with the average intron length, and not correlated with the CDS length and protein domain numbers. Comparison analyses showed that ubiquitously expressed genes and narrowly expressed genes with the similar expression levels do not differ in compactness. Our data provided evidence that the genomic design model can not, at least in part, explain our observations. We grouped all somatic-tissue-specific genes

  12. Selection for the G4 DNA motif at the 5' end of human genes.

    Science.gov (United States)

    Eddy, Johanna; Maizels, Nancy

    2009-04-01

    Formation of G4 DNA may occur in the course of replication and transcription, and contribute to genomic instability. We have quantitated abundance of G4 motifs and potential for G4 DNA formation of the nontemplate strand of 5' exons and introns of transcripts of human genes. We find that, for all human genes, G4 motifs are enriched in 5' regions of transcripts relative to downstream regions; and in 5' regulatory regions relative to coding regions. Notably, although tumor suppressor genes are depleted and proto-oncogenes enriched in G4 motifs, abundance of G4 motifs in the 5' regions of transcripts of genes in these categories does not differ. These results support the hypothesis that G4 motifs are under selection in the human genome. They further show that for tumor suppressor genes and proto-oncogenes, independent selection determines potential for G4 DNA formation of 5' regulatory regions of transcripts and downstream coding regions.

  13. A graphic method for identification of novel glioma related genes.

    Science.gov (United States)

    Gao, Yu-Fei; Shu, Yang; Yang, Lei; He, Yi-Chun; Li, Li-Peng; Huang, GuaHua; Li, Hai-Peng; Jiang, Yang

    2014-01-01

    Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.

  14. A Graphic Method for Identification of Novel Glioma Related Genes

    Directory of Open Access Journals (Sweden)

    Yu-Fei Gao

    2014-01-01

    Full Text Available Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.

  15. Progress and limits of PrP gene selection policy.

    Science.gov (United States)

    Dawson, Michael; Moore, Richard C; Bishop, Stephen C

    2008-01-01

    Classical scrapie has proved to be a notoriously difficult disease to control due to a poor understanding of its natural history. The recognition of disease risk linkage to PrP genotype has offered the prospect of a disease control strategy, viz. genotyping and selective breeding, novel to veterinary medicine when first considered in the 1990s. The UK Spongiform Encephalopathy Advisory Committee recommended the exploitation of this approach in a voluntary, national programme to control classical scrapie and protect the public against food-borne exposure to bovine spongiform encephalopathy, should the national flock have been exposed via contaminated feed. The National Scrapie Plan for Great Britain was launched in 2001 and uptake has been widespread throughout the purebreeding sector of the sheep industry, with membership peaking at over 12 000 flocks in 2006. A total of 700 000 rams from 90 breeds have been genotyped. A comparison of ram lambs born in 2002 with those in 2006 shows evident changes in PrP genotype frequencies which are predicted to be associated with a reduction in disease risk. Various concerns have been raised regarding possible unintended consequences of widespread selection on PrP genotype, including impacts on other performance traits and possible effects on inbreeding and genetic diversity. To date, these concerns appear to be unfounded, as no consistent associations have been found with performance traits, nor are there likely to be any detectable impacts on inbreeding in mainstream breeds. Currently, semen banks have been implemented in Great Britain to store samples from animals of all common PrP genotypes, should these genotypes be required in the future. Various strategies to minimise future disease risks are discussed in the paper.

  16. Patterns of Positive Selection of the Myogenic Regulatory Factor Gene Family in Vertebrates

    Science.gov (United States)

    Zhao, Xiao; Yu, Qi; Huang, Ling; Liu, Qing-Xin

    2014-01-01

    The functional divergence of transcriptional factors is critical in the evolution of transcriptional regulation. However, the mechanism of functional divergence among these factors remains unclear. Here, we performed an evolutionary analysis for positive selection in members of the myogenic regulatory factor (MRF) gene family of vertebrates. We selected 153 complete vertebrate MRF nucleotide sequences from our analyses, which revealed substantial evidence of positive selection. Here, we show that sites under positive selection were more frequently detected and identified from the genes encoding the myogenic differentiation factors (MyoG and Myf6) than the genes encoding myogenic determination factors (Myf5 and MyoD). Additionally, the functional divergence within the myogenic determination factors or differentiation factors was also under positive selection pressure. The positive selection sites were more frequently detected from MyoG and MyoD than Myf6 and Myf5, respectively. Amino acid residues under positive selection were identified mainly in their transcription activation domains and on the surface of protein three-dimensional structures. These data suggest that the functional gain and divergence of myogenic regulatory factors were driven by distinct positive selection of their transcription activation domains, whereas the function of the DNA binding domains was conserved in evolution. Our study evaluated the mechanism of functional divergence of the transcriptional regulation factors within a family, whereby the functions of their transcription activation domains diverged under positive selection during evolution. PMID:24651579

  17. Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

    Science.gov (United States)

    Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

    2011-05-19

    There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

  18. Transferring Translucent Endosperm Mutant Gene Wx-mq and Rice Stripe Disease Resistance Gene Stv-bi by Marker-Assisted Selection in Rice (Oryza sativa)

    Institute of Scientific and Technical Information of China (English)

    YAO Shu; CHEN Tao; ZHANG Ya-dong; ZHU Zhen; ZHAO Ling; ZHAO Qing-yong; ZHOU Li-hui; WANG Cai-lin

    2011-01-01

    A high-yielding japonica rice variety,Wuyunjing 7,bred in Jiangsu Province,China as a female parent was crossed with a Japanese rice variety Kantou 194,which carries a rice stripe disease resistance gene Stv-b1 and a translucent endosperm mutant gene Wx-mq.From F2 generations,a sequence characterized amplified region (SCAR) marker tightly linked with Stv-b1 and a cleaved amplified polymorphic sequence (CAPS) marker for Wx-mq were used for marker-assisted selection.Finally,a new japonica rice line,Ning 9108,with excellent agronomic traits was obtained by multi-generational selection on stripe disease resistance and endosperm appearance.The utilization of the markers from genes related to rice quality and disease resistance was helpful not only for establishing a marker-assisted selection system of high-quality and disease resistance for rice but also for providing important intermediate materials and rapid selection method for good quality,disease resistance and high yield in rice breeding.

  19. Multitemporal spectroscopy for crop stress detection using band selection methods

    Science.gov (United States)

    Mewes, Thorsten; Franke, Jonas; Menz, Gunter

    2008-08-01

    A fast and precise sensor-based identification of pathogen infestations in wheat stands is essential for the implementation of site-specific fungicide applications. Several works have shown possibilities and limitations for the detection of plant stress using spectral sensor data. Hyperspectral data provide the opportunity to collect spectral reflectance in contiguous bands over a broad range of the electromagnetic spectrum. Individual phenomena like the light absorption of leaf pigments can be examined in detail. The precise knowledge of stress-dependent shifting in certain spectral wavelengths provides great advantages in detecting fungal infections. This study focuses on band selection techniques for hyperspectral data to identify relevant and redundant information in spectra regarding a detection of plant stress caused by pathogens. In a laboratory experiment, five 1 sqm boxes with wheat were multitemporarily measured by a ASD Fieldspec® 3 FR spectroradiometer. Two stands were inoculated with Blumeria graminis - the pathogen causing powdery mildew - and one stand was used to simulate the effect of water deficiency. Two stands were kept healthy as control stands. Daily measurements of the spectral reflectance were taken over a 14-day period. Three ASD Pro Lamps were used to illuminate the plots with constant light. By applying band selection techniques, the three types of different wheat vitality could be accurately differentiated at certain stages. Hyperspectral data can provide precise information about pathogen infestations. The reduction of the spectral dimension of sensor data by means of band selection procedures is an appropriate method to speed up the data supply for precision agriculture.

  20. Nature and intensity of selection pressure on CRISPR-associated genes.

    Science.gov (United States)

    Takeuchi, Nobuto; Wolf, Yuri I; Makarova, Kira S; Koonin, Eugene V

    2012-03-01

    The recently discovered CRISPR-Cas adaptive immune system is present in almost all archaea and many bacteria. It consists of cassettes of CRISPR repeats that incorporate spacers homologous to fragments of viral or plasmid genomes that are employed as guide RNAs in the immune response, along with numerous CRISPR-associated (cas) genes that encode proteins possessing diverse, only partially characterized activities required for the action of the system. Here, we investigate the evolution of the cas genes and show that they evolve under purifying selection that is typically much weaker than the median strength of purifying selection affecting genes in the respective genomes. The exceptions are the cas1 and cas2 genes that typically evolve at levels of purifying selection close to the genomic median. Thus, although these genes are implicated in the acquisition of spacers from alien genomes, they do not appear to be directly involved in an arms race between bacterial and archaeal hosts and infectious agents. These genes might possess functions distinct from and additional to their role in the CRISPR-Cas-mediated immune response. Taken together with evidence of the frequent horizontal transfer of cas genes reported previously and with the wide-spread microscale recombination within these genes detected in this work, these findings reveal the highly dynamic evolution of cas genes. This conclusion is in line with the involvement of CRISPR-Cas in antiviral immunity that is likely to entail a coevolutionary arms race with rapidly evolving viruses. However, we failed to detect evidence of strong positive selection in any of the cas genes.

  1. A method for multiplex gene synthesis employing error correction based on expression.

    Directory of Open Access Journals (Sweden)

    Timothy H-C Hsiau

    Full Text Available Our ability to engineer organisms with new biosynthetic pathways and genetic circuits is limited by the availability of protein characterization data and the cost of synthetic DNA. With new tools for reading and writing DNA, there are opportunities for scalable assays that more efficiently and cost effectively mine for biochemical protein characteristics. To that end, we have developed the Multiplex Library Synthesis and Expression Correction (MuLSEC method for rapid assembly, error correction, and expression characterization of many genes as a pooled library. This methodology enables gene synthesis from microarray-synthesized oligonucleotide pools with a one-pot technique, eliminating the need for robotic liquid handling. Post assembly, the gene library is subjected to an ampicillin based quality control selection, which serves as both an error correction step and a selection for proteins that are properly expressed and folded in E. coli. Next generation sequencing of post selection DNA enables quantitative analysis of gene expression characteristics. We demonstrate the feasibility of this approach by building and testing over 90 genes for empirical evidence of soluble expression. This technique reduces the problem of part characterization to multiplex oligonucleotide synthesis and deep sequencing, two technologies under extensive development with projected cost reduction.

  2. A method for multiplex gene synthesis employing error correction based on expression.

    Science.gov (United States)

    Hsiau, Timothy H-C; Sukovich, David; Elms, Phillip; Prince, Robin N; Strittmatter, Tobias; Stritmatter, Tobias; Ruan, Paul; Curry, Bo; Anderson, Paige; Sampson, Jeff; Anderson, J Christopher

    2015-01-01

    Our ability to engineer organisms with new biosynthetic pathways and genetic circuits is limited by the availability of protein characterization data and the cost of synthetic DNA. With new tools for reading and writing DNA, there are opportunities for scalable assays that more efficiently and cost effectively mine for biochemical protein characteristics. To that end, we have developed the Multiplex Library Synthesis and Expression Correction (MuLSEC) method for rapid assembly, error correction, and expression characterization of many genes as a pooled library. This methodology enables gene synthesis from microarray-synthesized oligonucleotide pools with a one-pot technique, eliminating the need for robotic liquid handling. Post assembly, the gene library is subjected to an ampicillin based quality control selection, which serves as both an error correction step and a selection for proteins that are properly expressed and folded in E. coli. Next generation sequencing of post selection DNA enables quantitative analysis of gene expression characteristics. We demonstrate the feasibility of this approach by building and testing over 90 genes for empirical evidence of soluble expression. This technique reduces the problem of part characterization to multiplex oligonucleotide synthesis and deep sequencing, two technologies under extensive development with projected cost reduction.

  3. Identification of learning and memory genes in canine; promoter investigation and determining the selective pressure.

    Science.gov (United States)

    Seifi Moroudi, Reihane; Masoudi, Ali Akbar; Vaez Torshizi, Rasoul; Zandi, Mohammad

    2014-12-01

    One of the important behaviors of dogs is trainability which is affected by learning and memory genes. These kinds of the genes have not yet been identified in dogs. In the current research, these genes were found in animal models by mining the biological data and scientific literatures. The proteins of these genes were obtained from the UniProt database in dogs and humans. Not all homologous proteins perform similar functions, thus comparison of these proteins was studied in terms of protein families, domains, biological processes, molecular functions, and cellular location of metabolic pathways in Interpro, KEGG, Quick Go and Psort databases. The results showed that some of these proteins have the same performance in the rat or mouse, dog, and human. It is anticipated that the protein of these genes may be effective in learning and memory in dogs. Then, the expression pattern of the recognized genes was investigated in the dog hippocampus using the existing information in the GEO profile. The results showed that BDNF, TAC1 and CCK genes are expressed in the dog hippocampus, therefore, these genes could be strong candidates associated with learning and memory in dogs. Subsequently, due to the importance of the promoter regions in gene function, this region was investigated in the above genes. Analysis of the promoter indicated that the HNF-4 site of BDNF gene and the transcription start site of CCK gene is exposed to methylation. Phylogenetic analysis of protein sequences of these genes showed high similarity in each of these three genes among the studied species. The dN/dS ratio for BDNF, TAC1 and CCK genes indicates a purifying selection during the evolution of the genes.

  4. Selection of disposal contractor by multi criteria decision making methods

    Directory of Open Access Journals (Sweden)

    Cenker Korkmazer

    2016-08-01

    Full Text Available Hazardous waste is substance that threaten people and environment in case of improper storage, disposal and transport due to its concentration, physical and chemical properties. Companies producing hazardous waste as a result of several activities mostly do not have any own disposal facilities. In addition, they do not pay attention enough to determine the right contractor as a disposal facility. On the other hand, there are various qualitative and quantitative criteria affecting the selection of the contractor and conflicting with each other. The aim of the performed study is to assist one of these companies producing hazardous waste in the selection of the best contractor that eliminates hazardous waste economic and harmless way. In the study, contractor weights in percentage is calculated by using Analytic Network Process (ANP as one of the multi-criteria decision making (MCDM methods and widely used in the literature which considers both qualitative and quantitative criteria. In the next step, by the help of the mathematical model, contractors that will be given which type of hazardous waste are identified. This integrated approach can be used as a guide for similar firms.

  5. Material Design, Selection, and Manufacturing Methods for System Sustainment

    Energy Technology Data Exchange (ETDEWEB)

    David Sowder, Jim Lula, Curtis Marshall

    2010-02-18

    This paper describes a material selection and validation process proven to be successful for manufacturing high-reliability long-life product. The National Secure Manufacturing Center business unit of the Kansas City Plant (herein called KCP) designs and manufactures complex electrical and mechanical components used in extreme environments. The material manufacturing heritage is founded in the systems design to manufacturing practices that support the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA). Material Engineers at KCP work with the systems designers to recommend materials, develop test methods, perform analytical analysis of test data, define cradle to grave needs, present final selection and fielding. The KCP material engineers typically will maintain cost control by utilizing commercial products when possible, but have the resources and to develop and produce unique formulations as necessary. This approach is currently being used to mature technologies to manufacture materials with improved characteristics using nano-composite filler materials that will enhance system design and production. For some products the engineers plan and carry out science-based life-cycle material surveillance processes. Recent examples of the approach include refurbished manufacturing of the high voltage power supplies for cockpit displays in operational aircraft; dry film lubricant application to improve bearing life for guided munitions gyroscope gimbals, ceramic substrate design for electrical circuit manufacturing, and tailored polymeric materials for various systems. The following examples show evidence of KCP concurrent design-to-manufacturing techniques used to achieve system solutions that satisfy or exceed demanding requirements.

  6. Efficient Cluster Head Selection Methods for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jong-Shin Chen

    2010-08-01

    Full Text Available The past few years have witnessed increased in the potential use of wireless sensor network (WSN such as disaster management, combat field reconnaissance, border protection and security surveillance. Sensors in these applications are expected to be remotely deployed in large numbers and to operate autonomously in unattended environments. Since a WSN is composed of nodes with nonreplenishable energy resource, elongating the network lifetime is the main concern. To support scalability, nodes are often grouped into disjoint clusters. Each cluster would have a leader, often referred as cluster head (CH. A CH is responsible for not only the general request but also assisting the general nodes to route the sensed data to the target nodes. The power-consumption of a CH is higher then of a general (non-CH node. Therefore, the CH selection will affect the lifetime of a WSN. However, the application scenario contexts of WSNs that determine the definitions of lifetime will impact to achieve the objective of elongating lifetime. In this study, we classify the lifetime into different types and give the corresponding CH selection method to achieve the life-time extension objective. Simulation results demonstrate our study can enlarge the life-time for different requests of the sensor networks.

  7. Detecting short spatial scale local adaptation and epistatic selection in climate-related candidate genes in European beech (Fagus sylvatica) populations.

    Science.gov (United States)

    Csilléry, Katalin; Lalagüe, Hadrien; Vendramin, Giovanni G; González-Martínez, Santiago C; Fady, Bruno; Oddou-Muratorio, Sylvie

    2014-10-01

    Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. FST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an FST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.

  8. A Lightweight Structure Redesign Method Based on Selective Laser Melting

    Directory of Open Access Journals (Sweden)

    Li Tang

    2016-11-01

    Full Text Available The purpose of this paper is to present a new design method of lightweight parts fabricated by selective laser melting (SLM based on the “Skin-Frame” and to explore the influence of fabrication defects on SLM parts with different sizes. Some standard lattice parts were designed according to the Chinese GB/T 1452-2005 standard and manufactured by SLM. Then these samples were tested in an MTS Insight 30 compression testing machine to study the trends of the yield process with different structure sizes. A set of standard cylinder samples were also designed according to the Chinese GB/T 228-2010 standard. These samples, which were made of iron-nickel alloy (IN718, were also processed by SLM, and then tested in the universal material testing machine INSTRON 1346 to obtain their tensile strength. Furthermore, a lightweight redesigned method was researched. Then some common parts such as a stopper and connecting plate were redesigned using this method. These redesigned parts were fabricated and some application tests have already been performed. The compression testing results show that when the minimum structure size is larger than 1.5 mm, the mechanical characteristics will hardly be affected by process defects. The cylinder parts were fractured by the universal material testing machine at about 1069.6 MPa. These redesigned parts worked well in application tests, with both the weight and fabrication time of these parts reduced more than 20%.

  9. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  10. Method for producing a selectively permeable separation module

    Science.gov (United States)

    Stone, Mark L.; Orme, Christopher J.; Peterson, Eric S.

    2000-03-14

    A method and apparatus is provided for casting a polymeric membrane on the inside surface of porous tubes to provide a permeate filter system capable of withstanding hostile operating conditions and having excellent selectivity capabilities. Any polymer in solution, by either solvent means or melt processing means, is capable of being used in the present invention to form a thin polymer membrane having uniform thickness on the inside surface of a porous tube. Multiple tubes configured as a tubular module can also be coated with the polymer solution. By positioning the longitudinal axis of the tubes in a substantially horizontal position and rotating the tube about the longitudinal axis, the polymer solution coats the inside surface of the porous tubes without substantially infiltrating the pores of the porous tubes, thereby providing a permeate filter system having enhanced separation capabilities.

  11. [Selectivity rank regionalization of Paeonia lactiflora based on fuzzy method].

    Science.gov (United States)

    Lv, Jinrong; Guo, Lanping; Huang, Luqi; Liang, Liuke; Sun, Yuzhang; Zhang, Xiaobo; Han, Xiaoli; Zhang, Hongjun

    2009-04-01

    For optimal adaptive cultivation region selection, we used ecology factors characterized Duolun region as model area to carry out the adaptive habitat division of Paeonia lactiflora. Similar priority comparison of ecology factors.in 91 cities were calculated by Fuzzy methods, then, distance of the ecology factors were transferred to spacial model by geography information system (,GIS) and modified by soil utilization map of China. The results showed that P. lactiflora were mainly distributed in the Daxing'an Mountain, Changbaishan and qinling range which were divided into six grades of suitable regions belonging to three geographical distributed units. The most similar areas to Duolun were Huade, Xilinhaote, Suolun and Zhangbei. P. lactiflora's distribution and quality are relevant with longitude and latitude, and temperature and rainfall.

  12. Selective spin transport through a quantum heterostructure: Transfer matrix method

    Science.gov (United States)

    Dey, Moumita; Maiti, Santanu K.

    2016-09-01

    In the present work, we propose that a one-dimensional quantum heterostructure composed of magnetic and non-magnetic (NM) atomic sites can be utilized as a spin filter for a wide range of applied bias voltage. A simple tight-binding framework is given to describe the conducting junction where the heterostructure is coupled to two semi-infinite one-dimensional NM electrodes. Based on transfer matrix method, all the calculations are performed numerically which describe two-terminal spin-dependent transmission probability along with junction current through the wire. Our detailed analysis may provide fundamental aspects of selective spin transport phenomena in one-dimensional heterostructures at nanoscale level.

  13. Evaluation and selection of candidate reference genes for normalization of quantitative RT-PCR in Withania somnifera (L. Dunal.

    Directory of Open Access Journals (Sweden)

    Varinder Singh

    Full Text Available Quantitative real-time PCR (qRT-PCR is now globally used for accurate analysis of transcripts levels in plants. For reliable quantification of transcripts, identification of the best reference genes is a prerequisite in qRT-PCR analysis. Recently, Withania somnifera has attracted lot of attention due to its immense therapeutic potential. At present, biotechnological intervention for the improvement of this plant is being seriously pursued. In this background, it is important to have comprehensive studies on finding suitable reference genes for this high valued medicinal plant. In the present study, 11 candidate genes were evaluated for their expression stability under biotic (fungal disease, abiotic (wounding, salt, drought, heat and cold stresses, in different plant tissues and in response to various plant growth regulators (methyl jasmonate, salicylic acid, abscisic acid. The data as analyzed by various software packages (geNorm, NormFinder, Bestkeeper and ΔCt method suggested that cyclophilin (CYP is a most stable gene under wounding, heat, methyl jasmonate, different tissues and all stress conditions. T-SAND was found to be a best reference gene for salt and salicylic acid (SA treated samples, while 26S ribosomal RNA (26S, ubiquitin (UBQ and beta-tubulin (TUB were the most stably expressed genes under drought, biotic and cold treatment respectively. For abscisic acid (ABA treated samples 18S-rRNA was found to stably expressed gene. Finally, the relative expression level of the three genes involved in the withanolide biosynthetic pathway was detected to validate the selection of reliable reference genes. The present work will significantly contribute to gene analysis studies in W. somnifera and facilitate in improving the quality of gene expression data in this plant as well as and other related plant species.

  14. Selection and assessment of reference genes for quantitative PCR normalization in migratory locust Locusta migratoria (Orthoptera: Acrididae).

    Science.gov (United States)

    Yang, Qingpo; Li, Zhen; Cao, Jinjun; Zhang, Songdou; Zhang, Huaijiang; Wu, Xiaoyun; Zhang, Qingwen; Liu, Xiaoxia

    2014-01-01

    Locusta migratoria is a classic hemimetamorphosis insect and has caused widespread economic damage to crops as a migratory pest. Researches on the expression pattern of functional genes in L. migratoria have drawn focus in recent years, especially with the release of genome information. Real-time quantitative PCR is the most reproducible and sensitive approach for detecting transcript expression levels of target genes, but optimal internal standards are key factors for its accuracy and reliability. Therefore, it's necessary to provide a systematic stability assessment of internal control for well-performed tests of target gene expression profile. In this study, twelve candidate genes (Ach, Act, Cht2, EF1α, RPL32, Hsp70, Tub, RP49, SDH, GAPDH, 18S, and His) were analyzed with four statistical methods: the delta Ct approach, geNorm, Bestkeeper and NormFinder. The results from these analyses aimed to choose the best suitable reference gene across different experimental situations for gene profile study in L. migratoria. The result demonstrated that for different developmental stages, EF1α, Hsp70 and RPL32 exhibited the most stable expression status for all samples; EF1α and RPL32 were selected as the best reference genes for studies involving embryo and larvae stages, while SDH and RP49 were identified for adult stage. The best-ranked reference genes across different tissues are RPL32, Hsp70 and RP49. For abiotic treatments, the most appropriate genes we identified were as follows: Act and SDH for larvae subjected to different insecticides; RPL32 and Ach for larvae exposed to different temperature treatments; and Act and Ach for larvae suffering from starvation. The present report should facilitate future researches on gene expression in L. migratoria with accessibly optimal reference genes under different experimental contexts.

  15. Selection and assessment of reference genes for quantitative PCR normalization in migratory locust Locusta migratoria (Orthoptera: Acrididae.

    Directory of Open Access Journals (Sweden)

    Qingpo Yang

    Full Text Available Locusta migratoria is a classic hemimetamorphosis insect and has caused widespread economic damage to crops as a migratory pest. Researches on the expression pattern of functional genes in L. migratoria have drawn focus in recent years, especially with the release of genome information. Real-time quantitative PCR is the most reproducible and sensitive approach for detecting transcript expression levels of target genes, but optimal internal standards are key factors for its accuracy and reliability. Therefore, it's necessary to provide a systematic stability assessment of internal control for well-performed tests of target gene expression profile. In this study, twelve candidate genes (Ach, Act, Cht2, EF1α, RPL32, Hsp70, Tub, RP49, SDH, GAPDH, 18S, and His were analyzed with four statistical methods: the delta Ct approach, geNorm, Bestkeeper and NormFinder. The results from these analyses aimed to choose the best suitable reference gene across different experimental situations for gene profile study in L. migratoria. The result demonstrated that for different developmental stages, EF1α, Hsp70 and RPL32 exhibited the most stable expression status for all samples; EF1α and RPL32 were selected as the best reference genes for studies involving embryo and larvae stages, while SDH and RP49 were identified for adult stage. The best-ranked reference genes across different tissues are RPL32, Hsp70 and RP49. For abiotic treatments, the most appropriate genes we identified were as follows: Act and SDH for larvae subjected to different insecticides; RPL32 and Ach for larvae exposed to different temperature treatments; and Act and Ach for larvae suffering from starvation. The present report should facilitate future researches on gene expression in L. migratoria with accessibly optimal reference genes under different experimental contexts.

  16. Evaluation and selection of candidate reference genes for normalization of quantitative RT-PCR in Withania somnifera (L.) Dunal.

    Science.gov (United States)

    Singh, Varinder; Kaul, Sunil C; Wadhwa, Renu; Pati, Pratap Kumar

    2015-01-01

    Quantitative real-time PCR (qRT-PCR) is now globally used for accurate analysis of transcripts levels in plants. For reliable quantification of transcripts, identification of the best reference genes is a prerequisite in qRT-PCR analysis. Recently, Withania somnifera has attracted lot of attention due to its immense therapeutic potential. At present, biotechnological intervention for the improvement of this plant is being seriously pursued. In this background, it is important to have comprehensive studies on finding suitable reference genes for this high valued medicinal plant. In the present study, 11 candidate genes were evaluated for their expression stability under biotic (fungal disease), abiotic (wounding, salt, drought, heat and cold) stresses, in different plant tissues and in response to various plant growth regulators (methyl jasmonate, salicylic acid, abscisic acid). The data as analyzed by various software packages (geNorm, NormFinder, Bestkeeper and ΔCt method) suggested that cyclophilin (CYP) is a most stable gene under wounding, heat, methyl jasmonate, different tissues and all stress conditions. T-SAND was found to be a best reference gene for salt and salicylic acid (SA) treated samples, while 26S ribosomal RNA (26S), ubiquitin (UBQ) and beta-tubulin (TUB) were the most stably expressed genes under drought, biotic and cold treatment respectively. For abscisic acid (ABA) treated samples 18S-rRNA was found to stably expressed gene. Finally, the relative expression level of the three genes involved in the withanolide biosynthetic pathway was detected to validate the selection of reliable reference genes. The present work will significantly contribute to gene analysis studies in W. somnifera and facilitate in improving the quality of gene expression data in this plant as well as and other related plant species.

  17. Detecting positive darwinian selection in brain-expressed genes during human evolution

    Institute of Scientific and Technical Information of China (English)

    QI XueBin; Alice A. LIN; Luca L. CAVALLI-SFORZA; WANG Jun; SU Bing; YANG Su; ZHENG HongKun; WANG YinQiu; LIAO ChengHong; LIU Ying; CHEN XiaoHua; SHI Hong; YU XiaoJing

    2007-01-01

    To understand the genetic basis that underlies the phenotypic divergence between human and nonhuman primates, we screened a total of 7176 protein-coding genes expressed in the human brain and compared them with the chimpanzee orthologs to identify genes that show evidence of rapid evolution in the human lineage. Our results showed that the nonsynonymous/synonymous substitution (Ka/Ks) ratio for genes expressed in the brain of human and chimpanzee is 0.3854, suggesting that the brain-expressed genes are under functional constraint. The X-linked human brain-expressed genes evolved more rapidly than autosomal ones. We further dissected the molecular evolutionary patterns of 34 candidate genes by sequencing representative primate species to identify lineage-specific adaptive evolution. Fifteen out of the 34 candidate genes showed evidence of positive Darwinian selection in human and/or chimpanzee lineages. These genes are predicted to play diverse functional roles in embryonic development, spermatogenesis and male fertility, signal transduction, sensory nociception, and neural function. This study together with others demonstrated the usefulness and power of phylogenetic comparison of multiple closely related species in detecting lineage-specific adaptive evolution, and the identification of the positively selected brain-expressed genes may add new knowledge to the understanding of molecular mechanism of human origin.

  18. Degranulation of rat cerebellum induces selective variations in gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Eliyahu, D.; Soreq, H.

    1982-02-01

    Selective variations in the composition of poly(A)-containing mRNA were found to be induced in the rat cerebellum by X-irradiation. mRNA populations prepared from normal and X-irradiated rat cerebella at different stages of their development displayed equal efficiencies when translated in vitro in reticulocyte lysates. Specific differences were revealed, however, when the labeled translation products of both mRNA preparations were subjected to two-dimensional gel electrophoresis followed by fluorography of the dried gels. Of more than 100 polypeptide products, several showed marked intensity differences, indicating changes in the abundance of their directing mRNA species. These differences appear both in developing and in mature cerebellar mRNA, and the extent of modification in mRNA is much higher than the consequent changes in the composition of proteins in the irradiated cerebellum. The degranulation-induced modifications in levels of specific cerebellar mRNA species can be used to identify proteins whose biosynthesis depends on the presence of interneurons.

  19. Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

    Directory of Open Access Journals (Sweden)

    Alok Arun

    Full Text Available Real-time quantitative reverse transcription PCR (qRT-PCR is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae, two developmental stages (pupal and adult and two sexes (male and female, all of which were subjected to two food treatments (food stress and control feeding ad libitum. The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the

  20. Generation of recombinant Orf virus using an enhanced green fluorescent protein reporter gene as a selectable marker

    Directory of Open Access Journals (Sweden)

    Ning Zhangyong

    2011-12-01

    Full Text Available Abstract Background Reporter genes are often used as a selectable marker for generation of recombinant viruses in order to investigate the mechanism of pathogenesis and to obtain candidate vaccine viruses. Routine selection of the recombinant parapoxvirus is time-consuming and labor intensive. Therefore, developing a novel method for selection is critical. Results In this study, we developed a rapid method to generate recombinant Orf viruses (ORFV based on the enhanced green fluorescent protein (EGFP reporter gene as a selectable marker. The coding sequence of EGFP gene was amplified from pEGFP-N1 vector and subcloned into the pZIPPY-neo/gus plasmid under the control of the early-late vaccinia virus (VACV VV7.5 promoter and flanked by two multiple cloning sites (MCS to generate a novel transfer vector pSPV-EGFP. Using the pSPV-EGFP, two recombination cassettes pSPV-113LF-EGFP-113RF and pSPV-116LF-EGFP-116RF were constructed by cloning the flanking regions of the ORFV113 and ORFV116 and inserted into two MCS flanking the EGFP gene. Using this novel system, two single gene deletion mutants OV-IA82Δ113 and OV-IA82Δ116 were successfully generated. Conclusions This approach shortens the time needed to generate recombinant ORFVs (rORFVs. Thus, the pSPV-EGFP vector provides a direct, fast, and convenient way to manipulate the recombinant viruses, indicating that it is highly suited for its designed purpose.

  1. Selection of Suitable Reference Genes for Quantitative Real-time PCR in Sapium sebiferum

    Directory of Open Access Journals (Sweden)

    Xue Chen

    2017-05-01

    Full Text Available Chinese tallow (Sapium sebiferum L. is a promising landscape and bioenergy plant. Measuring gene expression by quantitative real-time polymerase chain reaction (qRT-PCR can provide valuable information on gene function. Stably expressed reference genes for normalization are a prerequisite for ensuring the accuracy of the target gene expression level among different samples. However, the reference genes in Chinese tallow have not been systematically validated. In this study, 12 candidate reference genes (18S, GAPDH, UBQ, RPS15, SAND, TIP41, 60S, ACT7, PDF2, APT, TBP, and TUB were investigated with qRT-PCR in 18 samples, including those from different tissues, from plants treated with sucrose and cold stresses. The data were calculated with four common algorithms, geNorm, BestKeeper, NormFinder, and the delta cycle threshold (ΔCt. TIP41 and GAPDH were the most stable for the tissue-specific experiment, GAPDH and 60S for cold treatment, and GAPDH and UBQ for sucrose stresses, while the least stable genes were 60S, TIP41, and 18S respectively. The comprehensive results showed APT, GAPDH, and UBQ to be the top-ranked stable genes across all the samples. The stability of 60S was the lowest during all experiments. These selected reference genes were further validated by comparing the expression profiles of the chalcone synthase gene in Chinese tallow in different samples. The results will help to improve the accuracy of gene expression studies in Chinese tallow.

  2. Allelic Polymorphism, Gene Duplication and Balancing Selection of MHC Class IIB Genes in the Omei Treefrog (Rhacophorus omeimontis)

    Institute of Scientific and Technical Information of China (English)

    Li HUANG; Mian ZHAO; Zhenhua LUO; Hua WU

    2016-01-01

    The worldwide declines in amphibian populations have largely been caused by infectious fungi and bacteria. Given that vertebrate immunity against these extracellular pathogens is primarily functioned by the major histocompatibility complex (MHC) class II molecules, the characterization and the evolution of amphibian MHC class II genes have attracted increasing attention. The polymorphism of MHC class II genes was found to be correlated with susceptibility to fungal pathogens in many amphibian species, suggesting the importance of studies on MHC class II genes for amphibians. However, such studies on MHC class II gene evolution have rarely been conducted on amphibians in China. In this study, we chose Omei treefrog (Rhacophorus omeimontis), which lived moist environments easy for breeding bacteria, to study the polymorphism of its MHC class II genes and the underlying evolutionary mechanisms. We amplified the entire MHC class IIB exon 2 sequence in the R. omeimontis using newly designed primers. We detected 102 putative alleles in 146 individuals. The number of alleles per individual ranged from one to seven, indicating that there are at least four loci containing MHC class IIB genes in R. omeimontis. The allelic polymorphism estimated from the 102 alleles in R. omeimontis was not high compared to that estimated in other anuran species. No significant gene recombination was detected in the 102 MHC class IIB exon 2 sequences. In contrast, both gene duplication and balancing selection greatly contributed to the variability in MHC class IIB exon 2 sequences of R. omeimontis. This study lays the groundwork for the future researches to comprehensively analyze the evolution of amphibian MHC genes and to assess the role of MHC gene polymorphisms in resistance against extracellular pathogens for amphibians in China.

  3. 'Obesity' is healthy for cetaceans? Evidence from pervasive positive selection in genes related to triacylglycerol metabolism.

    Science.gov (United States)

    Wang, Zhengfei; Chen, Zhuo; Xu, Shixia; Ren, Wenhua; Zhou, Kaiya; Yang, Guang

    2015-09-18

    Cetaceans are a group of secondarily adapted marine mammals with an enigmatic history of transition from terrestrial to fully aquatic habitat and subsequent adaptive radiation in waters around the world. Numerous physiological and morphological cetacean characteristics have been acquired in response to this drastic habitat transition; for example, the thickened blubber is one of the most striking changes that increases their buoyancy, supports locomotion, and provides thermal insulation. However, the genetic basis underlying the blubber thickening in cetaceans remains poorly explored. Here, 88 candidate genes associated with triacylglycerol metabolism were investigated in representative cetaceans and other mammals to test whether the thickened blubber matched adaptive evolution of triacylglycerol metabolism-related genes. Positive selection was detected in 41 of the 88 candidate genes, and functional characterization of these genes indicated that these are involved mainly in triacylglycerol synthesis and lipolysis processes. In addition, some essential regulatory genes underwent significant positive selection in cetacean-specific lineages, whereas no selection signal was detected in the counterpart terrestrial mammals. The extensive occurrence of positive selection in triacylglycerol metabolism-related genes is suggestive of their essential role in secondary adaptation to an aquatic life, and further implying that 'obesity' might be an indicator of good health for cetaceans.

  4. Identification of polymorphisms and balancing selection in the male infertility candidate gene, ornithine decarboxylase antizyme 3

    Directory of Open Access Journals (Sweden)

    Atkins John F

    2006-03-01

    Full Text Available Abstract Background The antizyme family is a group of small proteins that play a role in cell growth and division by regulating the biosynthesis of polyamines (putrescine, spermidine, spermine. Antizymes regulate polyamine levels primarily through binding ornithine decarboxylase (ODC, an enzyme key to polyamine production, and targeting ODC for destruction by the 26S proteosome. Ornithine decarboxylase antizyme 3 (OAZ3 is a testis-specific antizyme paralog and the only antizyme expressed in the mid to late stages of spermatogenesis. Methods To see if mutations in the OAZ3 gene are responsible for some cases of male infertility, we sequenced and evaluated the genomic DNA of 192 infertile men, 48 men of known paternity, and 34 African aborigines from the Mbuti tribe in the Democratic Republic of the Congo. The coding sequence of OAZ3 was further screened for polymorphisms by SSCP analysis in the infertile group and an additional 250 general population controls. Identified polymorphisms in the OAZ3 gene were further subjected to a haplotype analysis using PHASE 2.02 and Arlequin 2.0 software programs. Results A total of 23 polymorphisms were identified in the promoter, exons or intronic regions of OAZ3. The majority of these fell within a region of less than two kilobases. Two of the polymorphisms, -239 A/G in the promoter and 4280 C/T, a missense polymorphism in exon 5, may show evidence of association with male infertility. Haplotype analysis identified 15 different haplotypes, which can be separated into two divergent clusters. Conclusion Mutations in the OAZ3 gene are not a common cause of male infertility. However, the presence of the two divergent haplotypes at high frequencies in all three of our subsamples (infertile, control, African suggests that they have been maintained in the genome by balancing selection, which was supported by a test of Tajima's D statistic. Evidence for natural selection in this region implies that these haplotypes

  5. Complex signatures of locus-specific selective pressures and gene conversion on Human Growth Hormone/Chorionic Somatomammotropin genes.

    Science.gov (United States)

    Sedman, Laura; Padhukasahasram, Badri; Kelgo, Piret; Laan, Maris

    2008-10-01

    Reduced birth weight and slow neonatal growth are risks correlated with the development of common diseases in adulthood. The Human Growth Hormone/Chorionic Somatomammotropin (hGH/CSH) gene cluster (48 kb) at 17q22-24, consisting of one pituitary-expressed postnatal (GH1) and four placental genes (GH2, CSH1, CSH2, and CSHL1) may contribute to common variation in intrauterine and infant growth, and also to the regulation of feto-maternal and adult glucose metabolism. In contrast to GH1, there are limited genetic data on the hGH/CSH genes expressed in utero. We report the first survey of sequence variation encompassing all five hGH/CSH genes. Resequencing identified 113 SNPs/indels (ss86217675-ss86217787 in dbSNP) including 66 novel variants, and revealed remarkable differences in diversity patterns among the homologous duplicated genes as well as between the study populations of European (Estonians), Asian (Han Chinese), and African (Mandenkalu) ancestries. A dominant feature of the hGH/CSH region is hyperactive gene conversion, with the rate exceeding tens to hundreds of times the rate of reciprocal crossing-over and resulting in near absence of linkage disequilibrium. The initiation of gene conversion seems to be uniformly distributed because the data do not predict any recombination hotspots. Signatures of different selective constraints acting on each gene indicate functional specification of the hGH/CSH genes. Most strikingly, the GH2 coding for placental growth hormone shows strong intercontinental diversification (F(ST)=0.41-0.91; p<10(-6)) indicative of balancing selection, whereas the flanking CSH1 exhibits low population differentiation (F(ST)=0.03-0.09), low diversity (non-Africans, pi=8-9 x 10(-5); Africans, pi=8.2 x 10(-4)), and one dominant haplotype worldwide, consistent with purifying selection. The results imply that the success of an association study targeted to duplicated genes may be enhanced by prior resequencing of the study population in order

  6. Selection of Reference Genes for Gene Expression Studies related to lung injury in a preterm lamb model.

    Science.gov (United States)

    Pereira-Fantini, Prue M; Rajapaksa, Anushi E; Oakley, Regina; Tingay, David G

    2016-05-23

    Preterm newborns often require invasive support, however even brief periods of supported ventilation applied inappropriately to the lung can cause injury. Real-time quantitative reverse transcriptase-PCR (qPCR) has been extensively employed in studies of ventilation-induced lung injury with the reference gene 18S ribosomal RNA (18S RNA) most commonly employed as the internal control reference gene. Whilst the results of these studies depend on the stability of the reference gene employed, the use of 18S RNA has not been validated. In this study the expression profile of five candidate reference genes (18S RNA, ACTB, GAPDH, TOP1 and RPS29) in two geographical locations, was evaluated by dedicated algorithms, including geNorm, Normfinder, Bestkeeper and ΔCt method and the overall stability of these candidate genes determined (RefFinder). Secondary studies examined the influence of reference gene choice on the relative expression of two well-validated lung injury markers; EGR1 and IL1B. In the setting of the preterm lamb model of lung injury, RPS29 reference gene expression was influenced by tissue location; however we determined that individual ventilation strategies influence reference gene stability. Whilst 18S RNA is the most commonly employed reference gene in preterm lamb lung studies, our results suggest that GAPDH is a more suitable candidate.

  7. Selection of reliable reference genes for gene expression studies in Clonostachys rosea 67-1 under sclerotial induction.

    Science.gov (United States)

    Sun, Zhan-Bin; Li, Shi-Dong; Sun, Man-Hong

    2015-07-01

    Reference genes are important to precisely quantify gene expression by real-time PCR. In order to identify stable and reliable expressed genes in mycoparasite Clonostachys rosea in different modes of nutrition, seven commonly used housekeeping genes, 18S rRNA, actin, β-tubulin, elongation factor 1, ubiquitin, ubiquitin-conjugating enzyme and glyceraldehyde-3-phosphate dehydrogenase, from the effective biocontrol isolate C. rosea 67-1 were tested for their expression under sclerotial induction and during vegetative growth on PDA medium. Analysis by three software programs showed that differences existed among the candidates. Elongation factor 1 was most stable; the M value in geNorm, SD value in Bestkeeper and stability value in Normfinder analysis were 0.405, 0.450 and 0.442, respectively, indicating that the gene elongation factor 1 could be used to normalize gene expression in C. rosea in both vegetative growth and parasitic process. By using elongation factor 1, the expression of a serine protease gene, sep, in different conditions was assessed, which was consistent with the transcriptomic data. This research provides an effective method to quantitate expression changes of target genes in C. rosea, and will assist in further investigation of parasitism-related genes of this fungus.

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

    Science.gov (United States)

    Barman, Shohag; Kwon, Yung-Keun

    2017-01-01

    Background Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately. Results In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI) method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods. Conclusions Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network. PMID:28178334

  9. Self-assembled pentablock copolymers for selective and sustained gene delivery

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Bingqi [Iowa State Univ., Ames, IA (United States)

    2011-05-15

    The poly(diethylaminoethyl methacrylate) (PDEAEM) - Pluronic F127 - PDEAEM pentablock copolymer (PB) gene delivery vector system has been found to possess an inherent selectivity in transfecting cancer cells over non-cancer cells in vitro, without attaching any targeting ligands. In order to understand the mechanism of this selective transfection, three possible intracellular barriers to transfection were investigated in both cancer and non-cancer cells. We concluded that escape from the endocytic pathway served as the primary intracellular barrier for PB-mediated transfection. Most likely, PB vectors were entrapped and rendered non-functional in acidic lysosomes of non-cancer cells, but survived in less acidic lysosomes of cancer cells. The work highlights the importance of identifying intracellular barriers for different gene delivery systems and provides a new paradigm for designing targeting vectors based on intracellular differences between cell types, rather than through the use of targeting ligands. The PB vector was further developed to simultaneously deliver anticancer drugs and genes, which showed a synergistic effect demonstrated by significantly enhanced gene expression in vitro. Due to the thermosensitive gelation behavior, the PB vector packaging both drug and gene was also investigated for its in vitro sustained release properties by using polyethylene glycol diacrylate as a barrier gel to mimic the tumor matrix in vivo. Overall, this work resulted in the development of a gene delivery vector for sustained and selective gene delivery to tumor cells for cancer therapy.

  10. Self-assembled pentablock copolymers for selective and sustained gene delivery

    Science.gov (United States)

    Zhang, Bingqi

    The poly(diethylaminoethyl methacrylate) (PDEAEM) - Pluronic F127 - PDEAEM pentablock copolymer (PB) gene delivery vector system has been found to possess an inherent selectivity in transfecting cancer cells over non-cancer cells in vitro, without attaching any targeting ligands. In order to understand the mechanism of this selective transfection, three possible intracellular barriers to transfection were investigated in both cancer and non-cancer cells. We concluded that escape from the endocytic pathway served as the primary intracellular barrier for PB-mediated transfection. Most likely, PB vectors were entrapped and rendered non-functional in acidic lysosomes of non-cancer cells, but survived in less acidic lysosomes of cancer cells. The work highlights the importance of identifying intracellular barriers for different gene delivery systems and provides a new paradigm for designing targeting vectors based on intracellular differences between cell types, rather than through the use of targeting ligands. The PB vector was further developed to simultaneously deliver anticancer drugs and genes, which showed a synergistic effect demonstrated by significantly enhanced gene expression in vitro. Due to the thermosensitive gelation behavior, the PB vector packaging both drug and gene was also investigated for its in vitro sustained release properties by using polyethylene glycol diacrylate as a barrier gel to mimic the tumor matrix in vivo . Overall, this work resulted in the development of a gene delivery vector for sustained and selective gene delivery to tumor cells for cancer therapy.

  11. Selection of SNP subsets for association studies in candidate genes: comparison of the power of different strategies to detect single disease susceptibility locus effects

    Directory of Open Access Journals (Sweden)

    Deleuze Jean-Francois

    2006-04-01

    Full Text Available Abstract Background The recent advances in genotyping and molecular techniques have greatly increased the knowledge of the human genome structure. Millions of polymorphisms are reported and freely available in public databases. As a result, there is now a need to identify among all these data, the relevant markers for genetic association studies. Recently, several methods have been published to select subsets of markers, usually Single Nucleotide Polymorphisms (SNPs, that best represent genetic polymorphisms in the studied candidate gene or region. Results In this paper, we compared four of these selection methods, two based on haplotype information and two based on pairwise linkage disequilibrium (LD. The methods were applied to the genotype data on twenty genes with different patterns of LD and different numbers of SNPs. A measure of the efficiency of the different methods to select SNPs was obtained by comparing, for each gene and under several single disease susceptibility models, the power to detect an association that will be achieved with the selected SNP subsets. Conclusion None of the four selection methods stands out systematically from the others. Methods based on pairwise LD information turn out to be the most interesting methods in a context of association study in candidate gene. In a context where the number of SNPs to be tested in a given region needs to be more limited, as in large-scale studies or wide genome scans, one of the two methods based on haplotype information, would be more suitable.

  12. Tracing evolutionary relicts of positive selection on eight malaria-related immune genes in mammals.

    Science.gov (United States)

    Huang, Bing-Hong; Liao, Pei-Chun

    2015-07-01

    Plasmodium-induced malaria widely infects primates and other mammals. Multiple past studies have revealed that positive selection could be the main evolutionary force triggering the genetic diversity of anti-malaria resistance-associated genes in human or primates. However, researchers focused most of their attention on the infra-generic and intra-specific genome evolution rather than analyzing the complete evolutionary history of mammals. Here we extend previous research by testing the evolutionary link of natural selection on eight candidate genes associated with malaria resistance in mammals. Three of the eight genes were detected to be affected by recombination, including TNF-α, iNOS and DARC. Positive selection was detected in the rest five immunogenes multiple times in different ancestral lineages of extant species throughout the mammalian evolution. Signals of positive selection were exposed in four malaria-related immunogenes in primates: CCL2, IL-10, HO1 and CD36. However, selection signals of G6PD have only been detected in non-primate eutherians. Significantly higher evolutionary rates and more radical amino acid replacement were also detected in primate CD36, suggesting its functional divergence from other eutherians. Prevalent positive selection throughout the evolutionary trajectory of mammalian malaria-related genes supports the arms race evolutionary hypothesis of host genetic response of mammalian immunogenes to infectious pathogens.

  13. Application of Delphi method in site selection of desalination plants

    Directory of Open Access Journals (Sweden)

    M. Sepehr

    2017-12-01

    Full Text Available Given the reduced freshwater supplies across the world, seawater desalination is one of the appropriate methods available for producing freshwater. Selecting an optimal location is crucial in the installation of these plants owing to the environmental problems they cause. The present study was conducted to identify optimal locations for installing desalination Plants in the coastal areas of southern Iran (Hormozgan Province with application of Delphi method. To implement this technique and identify, screen and prioritize effective criteria and sub-criteria, ten experts were surveyed through questionnaires and eight criteria and 18 sub-criteria were identified. All these sub-criteria were evaluated and classified in ArcGIS into five classes as input layers. The maps were then integrated based on the modulation importance coefficient and the identified priorities using a linear Delphi model and the final map was reclassified into five categories. Environmentally sensitive areas and seawater quality were respectively the criterion and sub-criterion that received the highest importance. After combining the layers and obtaining the final map, 63 locations were identified for installing desalination plants in the coastal areas on the Persian Gulf and Oman Sea in Hormozgan Province.  At the end, 27 locations were high important and had optimal environmental conditions for establishing desalination plants. Of the 27 locations, six were located in the coastal area of the Oman Sea, one in the coastal area of the Strait of Hormuz and 20 others in the coastal area of the Persian Gulf.

  14. Spectrophotometric validation of assay method for selected medicinal plant extracts

    Directory of Open Access Journals (Sweden)

    Matthew Arhewoh

    2014-09-01

    Full Text Available Objective: To develop UV spectrophotometric assay validation methods for some selected medicinal plant extracts.Methods: Dried, powdered leaves of Annona muricata (AM and Andrographis paniculata (AP as well as seeds of Garcinia kola (GK and Hunteria umbellata (HU were separately subjected to maceration using distilled water. Different concentrations of the extracts were scanned spectrophotometrically to obtain wavelengths of maximum absorbance. The different extracts were then subjected to validation studies following international guidelines at the respective wavelengths obtained.Results: The results showed linearity at peak wavelengths of maximum absorbance of 292, 280, 274 and 230 nm for GK, HU, AM and AP, respectively. The calibration curves for the different concentrations of the extract gave R2 values ranging from 0.9831 for AM to 0.9996 for AP the inter-day and intra-day precision study showed that the relative standard deviation (% was ≤ 10% for all the extracts.Conclusion: The aqueous extracts and isolates of these plants can be assayed and monitored using these wavelengths.

  15. Exercise induced stress in horses: Selection of the most stable reference genes for quantitative RT-PCR normalization

    Directory of Open Access Journals (Sweden)

    Silvestrelli Maurizio

    2008-05-01

    Full Text Available Abstract Background Adequate stress response is a critical factor during athlete horses' training and is central to our capacity to obtain better performances while safeguarding animal welfare. In order to investigate the molecular mechanisms underlying this process, several studies have been conducted that take advantage of microarray and quantitative real-time PCR (qRT-PCR technologies to analyse the expression of candidate genes involved in the cellular stress response. Appropriate application of qRT-PCR, however, requires the use of reference genes whose level of expression is not affected by the test, by general physiological conditions or by inter-individual variability. Results The expression of nine potential reference genes was evaluated in lymphocytes of ten endurance horses during strenuous exercise. These genes were tested by qRT-PCR and ranked according to the stability of their expression using three different methods (implemented in geNorm, NormFinder and BestKeeper. Succinate dehydrogenase complex subunit A (SDHA and hypoxanthine phosphoribosyltransferase (HPRT always ranked as the two most stably expressed genes. On the other hand, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, transferrin receptor (TFRC and ribosomal protein L32 (RPL32 were constantly classified as the less reliable controls. Conclusion This study underlines the importance of a careful selection of reference genes for qRT-PCR studies of exercise induced stress in horses. Our results, based on different algorithms and analytical procedures, clearly indicate SDHA and HPRT as the most stable reference genes of our pool.

  16. Selection of internal control genes for real-time quantitative PCR in ovary and uterus of sows across pregnancy.

    Directory of Open Access Journals (Sweden)

    María Martínez-Giner

    Full Text Available BACKGROUND: Reproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages. RESULTS: The gene expression stability of ten potential reference genes was studied by three different methods (geNorm, NormFinder and BestKeeper in ovary and uterus collected at five different physiological time points (heat, and 15, 30, 45 and 60 days of pregnancy. Although final ranking differed, the three algorithms gave very similar results. Thus, the most stable genes across time were TBP and UBC in uterus and TBP and HPRT1 in ovary, while HMBS and ACTB showed the less stable expression in uterus and ovary, respectively. When studied as a systematic effect, the reproductive stage did not significantly affect the expression of the candidate reference genes except at 30d and 60d of pregnancy, when a general drop in expression was observed in ovary. CONCLUSIONS: Based in our results, we propose the use of TBP, UBC and SDHA in uterus and TBP, GNB2L1 and HPRT1 in ovary for normalization of longitudinal expression studies using quantitative PCR in sows.

  17. Methods for particle-mediated gene transfer into skin.

    Science.gov (United States)

    Yang, N S; McCabe, D E; Swain, W F

    1997-01-01

    During the past 5 yr, particle-mediated delivery techniques have been developed as a physical means for gene transfer into various eukaryotic systems, including plants, insects, fish, and mammals (1-7). For mammalian somatic tissues, this technology, popularly known as the gene gun method, has been shown effective in transfection of skin, liver, pancreas, muscle, spleen, and other organs in vivo (3,4); brain, mammary, and leukocyte pnmary cultures or explants ex vivo (2,5-7); and a wide range of different mammalian cell lines in vitro (3,6,7).

  18. Selection Pressure on Haemagglutinin Genes of H9N2 Influenza Viruses from Different Hosts

    Institute of Scientific and Technical Information of China (English)

    Wei-feng SHI; Ai-she DUN; Zhong ZHANG; Yan-zhou ZHANG; Guang-fu YU; Dong-ming ZHUANG; Chao-dong ZHU

    2009-01-01

    Positive selection and differential selective pressure analyses were carried out to study Haemagglutinin (HA) genes of H9N2 influenza viruses from different hosts in this paper. Results showed that, although most positions in HAs were under neutral or purifying evolution, a few positions located in the antigenic regions and receptor binding sites were subject to positive selection and some of them were even positively selected at the population level. In addition, there were always some positions differentially selected for viruses from different hosts. Both selection pressure working on HA codons and positions differentially selected might account for the extension of the host range and adaptations to different hosts of H9N2 influenza viruses.

  19. Pulsed irradiation improves target selectivity of infrared laser-evoked gene operator for single-cell gene induction in the nematode C. elegans.

    Directory of Open Access Journals (Sweden)

    Motoshi Suzuki

    Full Text Available Methods for turning on/off gene expression at the experimenter's discretion would be useful for various biological studies. Recently, we reported on a novel microscope system utilizing an infrared laser-evoked gene operator (IR-LEGO designed for inducing heat shock response efficiently in targeted single cells in living organisms without cell damage, thereby driving expression of a transgene under the control of a heat shock promoter. Although the original IR-LEGO can be successfully used for gene induction, several limitations hinder its wider application. Here, using the nematode Caenorhabditis elegans (C. elegans as a subject, we have made improvements in IR-LEGO. For better spatial control of heating, a pulsed irradiation method using an optical chopper was introduced. As a result, single cells of C. elegans embryos as early as the 2-cell stage and single neurons in ganglia can be induced to express genes selectively. In addition, the introduction of site-specific recombination systems to IR-LEGO enables the induction of gene expression controlled by constitutive and cell type-specific promoters. The strategies adopted here will be useful for future applications of IR-LEGO to other organisms.

  20. Evidence for positive selection in the gene fruitless in Anastrepha fruit flies

    Science.gov (United States)

    2010-01-01

    Background Many genes involved in the sex determining cascade have indicated signals of positive selection and rapid evolution across different species. Even though fruitless is an important gene involved mostly in several aspects of male courtship behavior, the few studies so far have explained its high rates of evolution by relaxed selective constraints. This would indicate that a large portion of this gene has evolved neutrally, contrary to what has been observed for other genes in the sex cascade. Results Here we test whether the fruitless gene has evolved neutrally or under positive selection in species of Anastrepha (Tephritidae: Diptera) using two different approaches, a long-term evolutionary analysis and a populational genetic data analysis. The first analysis was performed by using sequences of three species of Anastrepha and sequences from several species of Drosophila using the ratio of nonsynonymous to synonymous rates of evolution in PAML, which revealed that the fru region here studied has evolved by positive selection. Using Bayes Empirical Bayes we estimated that 16 sites located in the connecting region of the fruitless gene were evolving under positive selection. We also investigated for signs of this positive selection usin