Bioinformatics Seminar
Time:
Venue: Na
20 March 2018
NaInferring edge function in protein-protein interaction networks
Daniel EspositoWEHI Bioinformatics
Post-translational modifications (PTMs) regulate many key cellular processes. There has been increasing attention in using information rich databases such as the Gene Ontology (GO) in protein-protein interaction (PPI) and protein function prediction tasks. However ; these methods fail to give insight in the biochemical nature of these interactions ; and more so fail to give insight regarding the dynamic nature of protein function in the context of an interaction. We present a machine learning approach that uses information from Gene Ontology (GO) ; InterPro and Pfam protein annotations to infer edge functions in protein-protein interaction networks. In our approach we train a One-Vs-All estimator on multi-labelled PPIs mined from the Kyoto Encyclopedia Of Genes and Genomes (KEGG) and Human Protein Reference Database (HPRD) ; achieving a 5-fold cross-validation F1 score of 0.86. Furthermore ; when applied to the human interactome our method confidently classifies 62% of interactions at a probability of 0.7 or higher.;;;