title: Computational approaches for prediction of pathogen-host protein-protein interactions.
abstract: Infectious diseases are still among the major and prevalent health problems, mostly because of the drug resistance of novel variants of pathogens. Molecular interactions between pathogens and their hosts are the key parts of the infection mechanisms. Novel antimicrobial therapeutics to fight drug resistance is only possible in case of a thorough understanding of pathogen-host interaction (PHI) systems. Existing databases, which contain experimentally verified PHI data, suffer from scarcity of reported interactions due to the technically challenging and time consuming process of experiments. These have motivated many researchers to address the problem by proposing computational approaches for analysis and prediction of PHIs. The computational methods primarily utilize sequence information, protein structure and known interactions. Classic machine learning techniques are used when there are sufficient known interactions to be used as training data. On the opposite case, transfer and multitask learning methods are preferred. Here, we present an overview of these computational approaches for predicting PHI systems, discussing their weakness and abilities, with future directions.
authors.affiliation: Department of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University Shiraz, Iran.
authors.forename: Esmaeil
authors.initials: E
authors.lastname: Nourani
authors.affiliation: Department of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University Shiraz, Iran ; School of Computer Science, Institute for Research in Fundamental Sciences (IPM) Tehran, Iran.
authors.forename: Farshad
authors.initials: F
authors.lastname: Khunjush
authors.affiliation: Computational Systems Biology Group, Department of Bioengineering, Gebze Technical University Kocaeli, Turkey.
authors.forename: Saliha
authors.initials: S
authors.lastname: Durmuş
keywords: computational PHI prediction; data mining; machine learning; pathogen-host interaction (PHI); protein-protein interaction