Development of Bioinformatic and Experimental Technologies for Identification of Prokaryotic Regulatory Networks | |
Lawrence, Charles E ; McCue, Lee Ann | |
关键词: bioinformatics; transcription regulation; centroid; | |
DOI : 10.2172/935264 RP-ID : DOE/ER/63942-1 PID : OSTI ID: 935264 |
|
美国|英语 | |
来源: SciTech Connect | |
【 摘 要 】
The transcription regulatory network is arguably the most important foundation of cellular function, since it exerts the most fundamental control over the abundance of virtually all of a cellâs functional macromolecules. The two major components of a prokaryotic cellâs transcription regulation network are the transcription factors (TFs) and the transcription factor binding sites (TFBS); these components are connected by the binding of TFs to their cognate TFBS under appropriate environmental conditions. Comparative genomics has proven to be a powerful bioinformatics method with which to study transcription regulation on a genome-wide level. We have further extended comparative genomics technologies that we introduced over the last several years. Specifically, we developed and applied statistical approaches to analysis of correlated sequence data (i.e., sequences from closely related species). We also combined these technologies with functional genomic, proteomic and sequence data from multiple species, and developed computational technologies that provide inferences on the regulatory network connections, identifying the cognate transcription factor for predicted regulatory sites. Arguably the most important contribution of this work emerged in the course of the project. Specifically, the development of novel procedures of estimation and prediction in discrete high-D settings has broad implications for biology, genomics and well beyond. We showed that these procedures enjoy advantages over existing technologies in the identification of TBFS. These efforts are aimed toward identifying a cellâs complete transcription regulatory network and underlying molecular mechanisms.
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO201705180001426LZ | 40KB | download |