Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Life Sciences
Dprp: A Database Of Phenotype-Specific Regulatory Programs Derived From Transcription Factor Binding Data, David T. W. Tzeng, Yu-Ting Tseng, Matthew Ung, I-En Liao, Chun-Chi Liu, Chao Cheng
Dprp: A Database Of Phenotype-Specific Regulatory Programs Derived From Transcription Factor Binding Data, David T. W. Tzeng, Yu-Ting Tseng, Matthew Ung, I-En Liao, Chun-Chi Liu, Chao Cheng
Dartmouth Scholarship
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 …
Orthoclust: An Orthology-Based Network Framework For Clustering Data Across Multiple Species, Koon-Kiu Yan, Daifeng Wang, Joel Rozowsky, Henry Zheng, Chao Cheng, Mark Gerstein Gerstein
Orthoclust: An Orthology-Based Network Framework For Clustering Data Across Multiple Species, Koon-Kiu Yan, Daifeng Wang, Joel Rozowsky, Henry Zheng, Chao Cheng, Mark Gerstein Gerstein
Dartmouth Scholarship
Increasingly, high-dimensional genomics data are becoming available for many organisms.Here, we develop OrthoClust for simultaneously clustering data across multiple species. OrthoClust is a computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific. We demonstrate the application of OrthoClust using the RNA-Seq expression profiles of Caenorhabditis elegans and Drosophila melanogaster from the modENCODE consortium. A potential application of cross-species modules is to infer putative analogous functions of uncharacterized elements like non-coding RNAs based on guilt-by-association.