title: Analysis of metabolic and regulatory pathways through Gene Ontology-derived semantic similarity measures.
abstract: This study investigates the feasibility of applying Gene Ontology (GO)-derived semantic similarity methods to the biological pathway analysis. The results derived from the analysis of human metabolic and regulatory pathways are consistent with the network biology. It suggests that the semantic similarity measurement may be used to help the pathway modeling.
authors.affiliation: Windber Research Institute, Windber, PA, USA.
authors.forename: Xiang
authors.initials: X
authors.lastname: Guo
authors.forename: Craig D
authors.initials: CD
authors.lastname: Shriver
authors.forename: Hai
authors.initials: H
authors.lastname: Hu
authors.forename: Michael N
authors.initials: MN
authors.lastname: Liebman
mesh_terms: D030541:Databases, Genetic; D006801:Humans; D014176:Protein Biosynthesis; D011506:Proteins / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D012660:Semantics; D015398:Signal Transduction; D018875:Vocabulary, Controlled
chemical_list: D011506:Proteins