Network Component Analysis of Nitric Oxide Challenge to Escherichia Coli |
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Launch in standalone player | |
Air date: | Tuesday, July 10, 2007, 2:00:00 PM |
Category: | Systems Biology |
Runtime: | 70 minutes |
NLM Title: | Network component analysis of nitric oxide challenge to Escherichia coli [electronic resource] / James Liao. |
Author: | Liao, James. National Institutes of Health (U.S.). Systems Biology Special Interest Group. |
Publisher: | [Bethesda, Md. : National Institutes of Health, 2007] |
Abstract: | (CIT): Systems Biology Special Interest Group Traditional methods for analyzing genomic scale expression data ignore the underlying network structures and provide inferences based purely on statistical constraints of the computed signals. The resulting decomposition thus provides a phenomenological model for the observed data and does not necessarily contain physically or biologically meaningful signals. We develop a method, called network component analysis (NCA), for uncovering hidden regulatory signals from outputs of networked systems, when only a partial knowledge of the underlying network topology is available. This analysis, combined with other biochemical and genetic techniques, was used to deduce the direct nitric oxide (NO) targets in E. coli and the associated response networks. NCA was used to identify transcription factors that are perturbed by NO. Such information was screened with potential NO reaction mechanisms and phenotypical data from genetic knockouts to identify active chemistry and direct NO targets in E. coli. This approach identified the comprehensive E. coli NO response network and evinced that NO halts bacterial growth via inhibition of branched-chain amino acid biosynthesis enzyme dihydroxyacid dehydratase. |
Subjects: | Escherichia coli Gene Expression Regulation, Bacterial Gene Regulatory Networks Nitric Oxide--metabolism Transcription Factors |
Publication Types: | Government Publications Lectures |
Download: | Download
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NLM Classification: | QW 51 |
NLM ID: | 101313562 |
CIT File ID: | 13928 |
CIT Live ID: | 5997 |
Permanent link: | http://videocast.nih.gov/launch.asp?13928 |