Franke Vedran, Sikić Mile, Vlahoviček Kristian
Department of Molecular Biology, University of Zagreb, Zagreb, Croatia.
Methods Mol Biol. 2012;819:233-51. doi: 10.1007/978-1-61779-465-0_16.
Identifying hotspots responsible for protein interactions with other macromolecules or drugs provides insight into functional aspects of the protein network, and is a pivotal task in systems biology and drug discovery. Here, we present the protocol for the application of a machine-learning method - Random Forest - to prediction of interacting residues in proteins, based on either the structural parameters or the primary sequence alone.
识别与其他大分子或药物发生蛋白质相互作用的热点，有助于深入了解蛋白质网络的功能方面，是系统生物学和药物发现中的关键任务。在此，我们介绍一种机器学习方法——随机森林——基于结构参数或仅基于一级序列来预测蛋白质中相互作用残基的应用方案。
