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Hao, P.* ; Zheng, S.* ; Ping, J.* ; Tu, K.* ; Gieger, C. ; Wang-Sattler, R. ; Zhong, Y.* ; Li, Y.*

Human gene expression sensitivity according to large scale meta-analysis.

BMC Bioinformatics 10, Suppl.1:S56 (2009)
Publ. Version/Full Text Volltext DOI PMC
Open Access Gold
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BACKGROUND: Genes show different sensitivities in expression corresponding to various biological conditions. Systematical study of this concept is required because of its important implications in microarray analysis etc. J.H. Ohn et al. first studied this gene property with yeast transcriptional profiling data. RESULTS: Here we propose a calculation framework for gene expression sensitivity analysis. We also compared the functions, centralities and transcriptional regulations of the sensitive and robust genes. We found that the robust genes tended to be involved in essential cellular processes. Oppositely, the sensitive genes perform their functions diversely. Moreover while genes from both groups show similar geometric centrality by coupling them onto integrated protein networks, the robust genes have higher vertex degree and betweenness than that of the sensitive genes. An interesting fact was also found that, not alike the sensitive genes, the robust genes shared less transcription factors as their regulators. CONCLUSION: Our study reveals different propensities of gene expression to external perturbations, demonstrates different roles of sensitive genes and robust genes in the cell and proposes the necessity of combining the gene expression sensitivity in the microarray analysis.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords PROTEIN-INTERACTION NETWORK; HOUSEKEEPING GENES; ESSENTIALITY; MICROARRAYS; PROFILES; DATABASE; UPDATE; GENOME; MOUSE
ISSN (print) / ISBN 1471-2105
e-ISSN 1471-2105
Quellenangaben Volume: 10, Issue: SUPPL. 1, Pages: , Article Number: S56, Supplement: Suppl.1
Publisher BioMed Central
Non-patent literature Publications
Reviewing status Peer reviewed