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Predicting homologous signaling pathways using machine learning
Author(s) -
Babak Bostan,
Russell Greiner,
Duane Szafron,
Paul Lu
Publication year - 2009
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/btp532
Subject(s) - computer science , homologous chromosome , artificial intelligence , computational biology , signal transduction , machine learning , biology , microbiology and biotechnology , genetics , gene
In general, each cell signaling pathway involves many proteins, each with one or more specific roles. As they are essential components of cell activity, it is important to understand how these proteins work-and in particular, to determine which of the species' proteins participate in each role. Experimentally determining this mapping of proteins to roles is difficult and time consuming. Fortunately, many pathways are similar across species, so we may be able to use known pathway information of one species to understand the corresponding pathway of another.

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