title: Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.
abstract: Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.
authors.affiliation: Quantiative Study Group, Faculty of Business Administration, University of New Brunswick, Fredericton, New Brunswick, Canada.
authors.forename: Donglei
authors.initials: D
authors.lastname: Du
authors.forename: Connie F
authors.initials: CF
authors.lastname: Lee
authors.forename: Xiu-Qing
authors.initials: XQ
authors.lastname: Li
mesh_terms: D000465:Algorithms; D017124:Conserved Sequence; D057225:Data Mining / Q000379:methods*; D030562:Databases, Protein; D019143:Evolution, Molecular; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods*; D015398:Signal Transduction