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Methods. 2015 Mar;74:47-53. doi: 10.1016/j.ymeth.2014.10.026. Epub 2014 Oct 28.

Protein-protein interaction predictions using text mining methods.

Author information

1
Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece.
2
Division of Basic Sciences, School of Medicine, University of Crete, Heraklion 71003, Greece. Electronic address: iliopj@med.uoc.gr.

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.

KEYWORDS:

Computational tools; Protein–protein interaction prediction; Text mining

PMID:
25448298
DOI:
10.1016/j.ymeth.2014.10.026
[Indexed for MEDLINE]

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