Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis | Zendy

Ichigaku Takigawa | Zendy; Hiroshi Mamitsuka | Zendy

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Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis

Author(s) -

Ichigaku Takigawa,

Hiroshi Mamitsuka

Publication year - 2007

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/btm575

Subject(s) - pairwise comparison , ranking (information retrieval) , probabilistic logic , path (computing) , path analysis (statistics) , computer science , computational biology , data mining , statistics , biology , mathematics , artificial intelligence , machine learning , programming language

Pathway knowledge in public databases enables us to examine how individual metabolites are connected via chemical reactions and what genes are implicated in those processes. For two given (sets of) compounds, the number of possible paths between them in a metabolic network can be intractably large. It would be informative to rank these paths in order to differentiate between them.

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