Abstract:
:Investigation of biological processes using selective chemical interventions is generally applied in biomedical research and drug discovery. Many studies of this kind make use of gene expression experiments to explore cellular responses to chemical interventions. Recently, some research groups constructed libraries of chemical related expression profiles, and introduced similarity comparison into chemical induced transcriptome analysis. Resembling sequence similarity alignment, expression pattern comparison among chemical intervention related expression profiles provides a new way for chemical function prediction and chemical-gene relation investigation. However, existing methods place more emphasis on comparing profile patterns globally, which ignore noises and marginal effects. At the same time, though the whole information of expression profiles has been used, it is difficult to uncover the underlying mechanisms that lead to the functional similarity between two molecules. Here a new approach is presented to perform biological effects similarity comparison within small biologically meaningful gene categories. Regarding gene categories as units, a reduced similarity matrix is generated for measuring the biological distances between query and profiles in library and pointing out in which modules do chemical pairs resemble. Through the modularization of expression patterns, this method reduces experimental noises and marginal effects and directly correlates chemical molecules with gene function modules.
journal_name
Nucleic Acids Resjournal_title
Nucleic acids researchauthors
Li Y,Hao P,Zheng S,Tu K,Fan H,Zhu R,Ding G,Dong C,Wang C,Li X,Thiesen HJ,Chen YE,Jiang H,Liu L,Li Ydoi
10.1093/nar/gkn610subject
Has Abstractpub_date
2008-11-01 00:00:00pages
e137issue
20eissn
0305-1048issn
1362-4962pii
gkn610journal_volume
36pub_type
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