检索结果-内蒙古大学图书馆

TriGen: A genetic algorithm to mine triclusters in temporal gene expression data

NEUROCOMPUTING 2014年 132卷 42-53页

作者： Gutierrez-Aviles, D. Rubio-Escudero, C. Martinez-Alvarez, F. Riquelme, J. C. Univ Seville Dept Comp Sci Seville Spain Pablo de Olavide Univ Seville Dept Comp Sci Seville Spain

Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. We present the TriGen algorithm, a genetic algorithm that finds triclusters of gene expression that take into account the experimental conditions and the time points simultaneously. We have used TriGen to mine datasets related to synthetic data, yeast (Saccharomyces cerevisiae) cell cycle and human inflammation and host response to injury experiments. TriGen has proved to be capable of extracting groups of genes with similar patterns in subsets of conditions and times, and these groups have shown to be related in terms of their functional annotations extracted from the Gene Ontology. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Tricluster Genetic algorithms microarray data Time series

来源：评论

学校读者我要写书评

暂无评论

A Functional and Phylogenetic Comparison of Quorum Sensing Related Genes in Brucella melitensis 16M

引用

JOURNAL OF MICROBIOLOGY 2014年第8期52卷 709-715页

作者： Leticia Brambila-Tapia, Aniel Jessica Perez-Rueda, Ernesto Univ Nacl Autonoma Mexico Inst Biotecnol Dept Ingn Celular & Biocatalisis Cuernavaca 62191 Morelos Mexico Univ Nacl Autonoma Mexico Fac Ciencias Unidad Multidisciplinaria Docencia & Invest Sisal Yucatan Mexico

A quorum-sensing (QS) system is involved in Brucella melitensis survival inside the host cell. Two transcriptional regulators identified in B. melitensis, BlxR and VjbR, regulate the expression of virB, an operon required for bacterial intracellular persistence. In this work, 628 genes affected by VjbR and 124 by BlxR were analyzed to gain insights into their functional and taxonomical distributions among the Bacteria and Archaea cellular domains. In this regard, the Cluster of Orthologous Groups (COG) genes and orthologous genes in 789 nonredundant bacterial and archaeal genomes were obtained and compared against a group of randomly selected genes. From these analyses, we found 71 coaffected genes between VjbR and BlxR. In the COG comparison, VjbR activated genes associated with intracellular trafficking, secretion and vesicular transport and defense mechanisms, while BlxR affected genes related to energy production and conversion (with an equal effect) and translation, ribosomal structure and biogenesis, posttranslational modifications and carbohydrate and amino acid metabolism (with a negative effect). When the taxonomical distribution of orthologous genes was evaluated, the VjbR- and BlxR-related genes presented more orthologous genes in Crenarchaeota (Archaea), Firmicutes, and Tenericutes and fewer genes in Proteobacteria than expected by chance. These findings suggest that QS system exert a fine-tuning modulation of gene expression, by which VjbR activates genes related to infection persistence and defense, while BlxR represses general bacterial metabolism for intracellular adaptations. Finally, these affected genes present a degree of presence among Bacteria and Archaea genomes that is different from that expected by chance.

关键词： Brucella melitensis quorum sensing microarray data taxonomical distribution orthologous genomics

来源：评论

学校读者我要写书评

暂无评论

Gene expression in superior temporal cortex of schizophrenia patients

引用

EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE 2014年第4期264卷 297-309页

作者： Sellmann, C. Pildain, L. Villarin Schmitt, A. Leonardi-Essmann, F. Durrenberger, P. F. Spanagel, R. Arzberger, T. Kretzschmar, H. Zink, M. Gruber, O. Herrera-Marschitz, M. Reynolds, R. Falkai, P. Gebicke-Haerter, P. J. Matthaeus, F. Heidelberg Univ Inst Pharm & Mol Biotechnol D-69120 Heidelberg Germany Max Planck Inst Mol Genet D-14195 Berlin Germany Ludwig Maximilians Univ Munchen Dept Psychiat & Psychotherapy D-80336 Munich Germany Univ Sao Paulo Inst Psychiat Lab Neurosci LIM27 BR-05453010 Sao Paulo Brazil Heidelberg Univ Med Fac Mannheim Cent Inst Mental Hlth Inst Psychopharmacol D-68159 Mannheim Germany Univ London Imperial Coll Sci Technol & Med Div Neurosci & Mental Hlth London W12 0NN England Univ Munich Inst Neuropathol D-81377 Munich Germany Heidelberg Univ Cent Inst Mental Hlth Dept Psychiat D-68159 Mannheim Germany Univ Chile Fac Med ICBM Program Mol & Clin Pharmacol Santiago 7 Chile Univ London Imperial Coll Sci Technol & Med Fac Med Wolfson Neurosci Labs London W12 0NN England Heidelberg Univ Ctr Modeling & Simulat Biosci D-69120 Heidelberg Germany

We investigated gene expression pattern obtained from microarray data of 10 schizophrenia patients and 10 control subjects. Brain tissue samples were obtained postmortem;thus, the different ages of the patients at death also allowed a study of the dynamic behavior of the expression patterns over a time frame of many years. We used statistical tests and dimensionality reduction methods to characterize the subset of genes differentially expressed in the two groups. A set of 10 genes were significantly downregulated, and a larger set of 40 genes were upregulated in the schizophrenia patients. Interestingly, the set of upregulated genes includes a large number of genes associated with gene transcription (zinc finger proteins and histone methylation) and apoptosis. We furthermore identified genes with a significant trend correlating with age in the control (MLL3) or the schizophrenia group (SOX5, CTRL). Assessments of correlations of other genes with the disorder (RRM1) or with the duration of medication could not be resolved, because all patients were medicated. This hypothesis-free approach uncovered a series of genes differentially expressed in schizophrenia that belong to a number of distinct cell functions, such as apoptosis, transcriptional regulation, cell motility, energy metabolism and hypoxia.

关键词： Schizophrenia microarray data Dimension reduction Trend identification Transcriptional regulation Hypoxia

来源：评论

学校读者我要写书评

暂无评论

The Impact of Measurement Error on Principal Component Analysis

引用

SCANDINAVIAN JOURNAL OF STATISTICS 2014年第4期41卷 1051-1063页

作者： Hellton, Kristoffer Herland Thoresen, Magne Univ Oslo Inst Basic Med Sci Dept Biostat N-0317 Oslo Norway

We investigate the effect of measurement error on principal component analysis in the high-dimensional setting. The effects of random, additive errors are characterized by the expectation and variance of the changes in the eigenvalues and eigenvectors. The results show that the impact of uncorrelated measurement error on the principal component scores is mainly in terms of increased variability and not bias. In practice, the error-induced increase in variability is small compared with the original variability for the components corresponding to the largest eigenvalues. This suggests that the impact will be negligible when these component scores are used in classification and regression or for visualizing data. However, the measurement error will contribute to a large variability in component loadings, relative to the loading values, such that interpretation based on the loadings can be difficult. The results are illustrated by simulating additive Gaussian measurement error in microarray expression data from cancer tumours and control tissues.

关键词： eigenvalues eigenvectors high-dimensional data measurement error microarray data perturbation theory principal component analysis

来源：评论

学校读者我要写书评

暂无评论

A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS

引用

ANNALS OF APPLIED STATISTICS 2014年第2期8卷 999-1021页

作者： Zhao, Yize Kang, Jian Yu, Tianwei Emory Univ Dept Biostat & Bioinformat Atlanta GA 30322 USA

It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with a clinical/biological outcome. Alternatively, in this paper, we propose a non-parametric Bayesian model for gene selection incorporating network information. In addition to identifying genes that have a strong association with a clinical outcome, our model can select genes with particular expressional behavior, in which case the regression models are not directly applicable. We show that our proposed model is equivalent to an infinity mixture model for which we develop a posterior computation algorithm based on Markov chain Monte Carlo (MCMC) methods. We also propose two fast computing algorithms that approximate the posterior simulation with good accuracy but relatively low computational cost. We illustrate our methods on simulation studies and the analysis of Spellman yeast cell cycle microarray data.

关键词： Dirichlet process mixture ising priors density estimation feature selection microarray data

来源：评论

学校读者我要写书评

暂无评论

An effective measure corresponding to biological significance

引用

NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS 2014年第1期3卷 1-15页

作者： Goyal, Ankita Ahmed, Hasin A. Bhattacharyya, Dhruba K. Tezpur Univ Dept CSE Tezpur 784028 Assam India

Shifting and scaling correlations are correspondent of biological significance in gene expression data analysis. Recent works have mentioned about the significance of negative correlation as well. In this paper, we distinguish and define the negative form of shifting and scaling correlations as negatively shifted correlation and negatively scaled correlation, respectively. Another issue in gene expression data analysis is simultaneous detection of both negative and positive correlation (shifting and scaling) over two disjoint subsets of features in a pair of gene expressions while most existing measures can detect only either of the correlations at a time. Here we propose a measure that can detect positive and negative forms of shifting and scaling correlation simultaneously between a pair of gene expressions over two disjoint subsets of features.

关键词： microarray data Gene expression data analysis Shifting correlation Scaling correlation Negative correlation

来源：评论

学校读者我要写书评

暂无评论

Identification of Biological Targets of Therapeutic Intervention for Diabetic Nephropathy with Bioinformatics Approach

引用

EXPERIMENTAL AND CLINICAL ENDOCRINOLOGY & DIABETES 2014年第10期122卷 587-591页

作者： Wu, T. Li, Q. Wu, T. Liu, H. Y. Shandong Univ Hosp 2 Dept Nephrol Jinan 250033 Shandong Peoples R China Shandong Univ Inst Biomed Engn Sch Med Jinan 250033 Shandong Peoples R China Qilu Univ Technol Jinan Shandong Peoples R China

We aimed to discover the potential microRNA (miRNA) targets for diabetic nephropathy (DN) treatment. The microarray data of GSE1009 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between DN patients and normal individuals were analyzed using limma package. The significant miRNAs targeting DEGs were collected based on Web-based Gene Set Enrichment Analysis Toolkit (WebGestalt) system. Then we predicted the protein-protein interaction (PPI) pairs regulated by significant miRNAs and constructed the PPI pairs-miRNA network using Cytoscape software. Besides, the significant function modules were explored using Molecular Complex Detection (MCODE) and Biological Networks Gene Ontology (BiNGO) plugin. Total 752 DEGs were obtained, including 318 down-regulated ones and 434 up-regulated ones. There were 10 significant miRNAs, among which miRNA-25 was the most significant. The PPI pairs-miRNA network was established with 103 PPI pairs and 10 miRNAs. Three function modules were obtained, including module A involved with miRNA-29, module B with miRNA-106 and module C with miRNA-124A and miRNA-21B. MiRNA-25, 29, 124 and 21 play key roles in DN progression and these miRNAs may be potential targets for DN treatment.

关键词： diabetic nephropathy microarray data differential expression genes protein pairs microRNAs

来源：评论

学校读者我要写书评

暂无评论

Supervised redundant feature detection for tumor classification

引用

BMC MEDICAL GENOMICS 2014年第2期7卷 1-9页

作者： Zeng, Xue-Qiang Li, Guo-Zheng Nanchang Univ Ctr Comp Nanchang 330029 Peoples R China Tongji Univ Dept Control Sci & Engn Shanghai 201804 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Comp Shanghai 201804 Peoples R China

Background: As a high dimensional problem, analysis of microarray data sets is a challenging task, where many weakly relevant or redundant features affect overall performance of classifiers. Methods: The previous works used redundant feature detection methods to select discriminative compact gene set, which only considered the relationship among features, not the redundancy of classification ability among features. This study propose a novel algorithm named RESI (Redundant fEature Selection depending on Instance), which considers label information in the measure of feature subset redundancy. Results: Experimental results on benchmark data sets show that RESI performs better than the previous state of the-art algorithms on redundant feature selection methods like mRMR. Conclusions: We propose an effective supervised redundant feature detection method for tumor classification.

关键词： Feature selection Redundant feature microarray data Tumor classification

来源：评论

学校读者我要写书评

暂无评论

K-nearest neighbors clustering algorithm

K-nearest neighbors clustering algorithm

引用

Conference on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments

作者： Gauza, Dariusz Zukowska, Anna Nowak, Robert Warsaw Univ Technol Fac Elect & Informat Technol Warsaw Poland

ISBN: (纸本)9781628413694

Cluster analysis, understood as unattended method of assigning objects to groups solely on the basis of their measured characteristics, is the common method to analyze DNA microarray data. Our proposal is to classify the results of one nearest neighbors algorithm (INN). The presented method well cope with complex, multidimensional data where the number of groups is properly identified. The numerical experiments on benchmark microarray data shows that presented algorithm give a better results than k-means clustering.

关键词： cluster analysis nearest neighbour k-means microarray data multidimensional data

来源：评论

学校读者我要写书评

暂无评论

An Incremental Updating Based Fast Phenotype Structure Learning Algorithm

An Incremental Updating Based Fast Phenotype Structure Learn...

引用

10th International Conference on Intelligent Computing (ICIC)

作者： Cheng, Hao Zhao, Yu-Hai Yin, Ying Zhang, Li-Jun Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China Northeastern Univ Coll Sci Shenyang Peoples R China

ISBN: (纸本)9783319093307;9783319093291

Unsupervised phenotype structure learning is important in microarray data analysis. The goal is to (1) find groups of samples corresponding to different phenotypes (e.g. disease or normal), and (2) find a subset of genes that can distinguish different groups. Due to the large number of genes and a mass of noise in microarray data, the existing methods are often of some limitations in terms of efficicency and effectiveness. In this paper, we develop an incremental updating based phenotype structure learning algorithm, namely FPLA. With a randomly selected initial state, the algorithm iteratively tries three possible adjustments, i.e. gene addition, gene deletion and sample move, to improve the quality of the current result. Accordingly, four incremental updating based optimization strategies are devised to eliminate the redundancy computations in each iteration. Further, by utilizing a harmonic quality function, it improves the result accuracy by penalizing the "outlier" effect. The experiments conducted on several real microarray datasets show that FPLA outperforms the two representative competing algorithms on both effectiveness and efficiency.

关键词： data mining microarray data phenotype structure bioinformatics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：