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Park, Chan Young
Calcium Dynamics Lab
Research Interests
  • Calcium Signaling, Calcium Channels, Immune, neuroscience, Drug Development, Virus and host cell interaction.

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REGNET: Mining context-specific human transcription networks using composite genomic information

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Title
REGNET: Mining context-specific human transcription networks using composite genomic information
Author
Chi, Sang-MunSeo, Young KyoPark, Young-KyuYoon, SoraPark, Chan YoungKim, Yong SungKim, Seon-YoungNam, Dougu
Issue Date
2014-06
Publisher
BIOMED CENTRAL LTD
Citation
BMC GENOMICS, v.15, no.1, pp.450
Abstract
Background: Genome-wide expression profiles reflect the transcriptional networks specific to the given cell context. However, most statistical models try to estimate the average connectivity of the networks from a collection of gene expression data, and are unable to characterize the context-specific transcriptional regulations. We propose an approach for mining context-specific transcription networks from a large collection of gene expression fold-change profiles and composite gene-set information.Results: Using a composite gene-set analysis method, we combine the information of transcription factor binding sites, Gene Ontology or pathway gene sets and gene expression fold-change profiles for a variety of cell conditions. We then collected all the significant patterns and constructed a database of context-specific transcription networks for human (REGNET). As a result, context-specific roles of transcription factors as well as their functional targets are readily explored. To validate the approach, nine predicted targets of E2F1 in HeLa cells were tested using chromatin immunoprecipitation assay. Among them, five (Gadd45b, Dusp6, Mll5, Bmp2 and E2f3) were successfully bound by E2F1. c-JUN and the EMT transcription networks were also validated from literature.Conclusions: REGNET is a useful tool for exploring the ternary relationships among the transcription factors, their functional targets and the corresponding cell conditions. It is able to provide useful clues for novel cell-specific transcriptional regulations. The REGNET database is available at http://mgrc.kribb.re.kr/regnet.
URI
https://scholarworks.unist.ac.kr/handle/201301/5110
URL
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84902549053
DOI
10.1186/1471-2164-15-450
ISSN
1471-2164
Appears in Collections:
BIO_Journal Papers
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