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DPRP:一个从转录因子结合数据中衍生出的表型特异性调控程序数据库。

DPRP: a database of phenotype-specific regulatory programs derived from transcription factor binding data.

机构信息

Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 402, Taiwan, Department of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan, Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH, USA, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan, Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.

出版信息

Nucleic Acids Res. 2014 Jan;42(Database issue):D178-83. doi: 10.1093/nar/gkt1254. Epub 2013 Dec 2.

Abstract

Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we constructed a database of phenotype-specific regulatory programs (DPRP, http://syslab.nchu.edu.tw/DPRP/) derived from the integrative analysis of TF binding data and gene expression data. DPRP provides three methods: the Fisher's Exact Test, the Kolmogorov-Smirnov test and the BASE algorithm to facilitate the application of gene expression data for generating new hypotheses on transcriptional regulatory programs in biological and clinical studies.

摘要

基因表达谱分析在过去几十年中得到了广泛应用,导致公共数据库中提供了大量的表达数据。这些数据集在阐明各种生物和临床条件下基因转录调控方面提供了丰富的信息。然而,通常很难直接从其自身的表达中确定导致基因表达变化的转录因子(TFs),因为 TF 活性通常在转录后水平受到调节。近年来,技术的进步使得通过 ChIP-seq 实验系统地确定 TF 的靶基因成为可能。为了识别基因表达谱背后的调控程序,我们构建了一个基于表型特异性调控程序的数据库(DPRP,http://syslab.nchu.edu.tw/DPRP/),该数据库是通过整合 TF 结合数据和基因表达数据的分析而得出的。DPRP 提供了三种方法:Fisher 精确检验、Kolmogorov-Smirnov 检验和 BASE 算法,以方便将基因表达数据应用于在生物和临床研究中生成转录调控程序的新假设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c04/3965116/9ef8b73e9d04/gkt1254f1p.jpg

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