Partial correlation coefficient between distance matrices as a new indicator of protein–protein interactions | Zendy

Tetsuya Sato | Zendy; Yoshihiro Yamanishi | Zendy; Katsuhisa Horimoto | Zendy; Minoru Kanehisa | Zendy; Hiroyuki Toh | Zendy

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Partial correlation coefficient between distance matrices as a new indicator of protein–protein interactions

Author(s) -

Tetsuya Sato,

Yoshihiro Yamanishi,

Katsuhisa Horimoto,

Minoru Kanehisa,

Hiroyuki Toh

Publication year - 2006

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/btl419

Subject(s) - partial correlation , correlation coefficient , false positive paradox , correlation , computer science , projection (relational algebra) , pearson product moment correlation coefficient , true positive rate , data mining , statistics , mathematics , algorithm , artificial intelligence , machine learning , geometry

The computational prediction of protein-protein interactions is currently a major issue in bioinformatics. Recently, a variety of co-evolution-based methods have been investigated toward this goal. In this study, we introduced a partial correlation coefficient as a new measure for the degree of co-evolution between proteins, and proposed its use to predict protein-protein interactions.

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