Open AccessCross-species common regulatory network inference without requirement for prior gene affiliation
Author(s) -
Amin Moghaddas Gholami,
Kurt Fellenberg
Publication year - 2010
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btq096
Subject(s) - inference , computer science , context (archaeology) , gene regulatory network , data mining , source code , kegg , bayes' theorem , bayesian network , computational biology , bayesian probability , gene , machine learning , biology , artificial intelligence , gene ontology , genetics , paleontology , gene expression , operating system
Cross-species meta-analyses of microarray data usually require prior affiliation of genes based on orthology information that often relies on sequence similarity.
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