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Title: Gene expression profiles of 400 siRNA knocked down on HUVEC      
keywords:
Transcriptome or Gene expression
ID:
PRJNA141887
description:
Gene regulatory networks inferred from RNA abundance data have generated significant interest. Several high-profile studies have suggested that gene networks may be useful for identifying molecular pathways related to development, human disease and drug action. However despite, this potential, gene network approaches are used relatively infrequently and their use generally requires input from specialist bioinformaticians. To make their use and evaluation more accessible to non-specialist bioinformaticians and to laboratory scientists, we have assembled a comprehensive but easily used suite of tools for the generation and evaluation of gene regulatory networks, applicable to both microarray and RNA-seq data. We illustrate the use of these tools with two previously unpublished microarray datasets generated in primary human endothelial cells by 400 siRNA-mediated knockdowns. Using these tools and data sets, we reverse-engineered a range of different types of transcriptional regulatory network model, and compared these networks with known molecular pathways reported in the literature. Overall design: In this study, we generated microarray data from human umbilical vein endothelial cells (HUVECs) transfected with 400 siRNAs and infered gene networks from them by using five different methods.
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landingpage: http://www.ncbi.nlm.nih.gov/bioproject/PRJNA141887
authentication:
none
authorization:
none
ID:
pmid:22121215
dateReleased:
11-29-2011
name:
Homo sapiens
ncbiID:
ncbitax:9606
abbreviation:
NCBI
homePage: http://www.ncbi.nlm.nih.gov
ID:
SCR:006472
name:
National Center for Biotechnology Information
homePage: http://www.ncbi.nlm.nih.gov/bioproject
ID:
SCR:004801
name:
NCBI BioProject