Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins
作者： Castrense Savojardo , Piero Fariselli , Damiano Piovesan , Pier Luigi Martelli , Rita Casadio
DOI: 10.1007/978-3-642-35686-5_11
关键词:
摘要: A reliable predictor of protein-protein interaction sites is necessary to investigate and model protein functional networks. Hidden Markov Support Vector Machines (HM-SVM) have been shown be among the best performing methods on this task. Furthermore, it has noted that performance a improves when its input takes advantage difference between observed predicted residue solvent accessibility. In paper, for first time, we combine these elements present ISPRED2, new HM-SVM-based method overpasses state art (Q2=0.71 correlation=0.43). ISPRED2 consists sets Python scripts aimed at integrating different third-party software obtain final prediction.
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