title: Protein-protein interaction predictions using text mining methods.
abstract: It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools.
authors.affiliation: Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece.
authors.forename: Nikolas
authors.initials: N
authors.lastname: Papanikolaou
authors.affiliation: Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece.
authors.forename: Georgios A
authors.initials: GA
authors.lastname: Pavlopoulos
authors.affiliation: Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece.
authors.forename: Theodosios
authors.initials: T
authors.lastname: Theodosiou
authors.affiliation: Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece. Electronic address: iliopj@med.uoc.gr.
authors.forename: Ioannis
authors.initials: I
authors.lastname: Iliopoulos
mesh_terms: D000818:Animals; D057225:Data Mining / Q000379:methods* / Q000639:trends; D030562:Databases, Protein / Q000639:trends; D005544:Forecasting; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods* / Q000639:trends
keywords: Computational tools; Protein–protein interaction prediction; Text mining