MetaPred2CS: A sequence-based meta-predictor for protein-protein interactions of prokaryotic two-component system proteins

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Abstract

Motivation: Two-component systems (TCS) are the main signalling pathways of prokaryotes, and control a wide range of biological phenomena. Their functioning depends on interactions between TCS proteins, the specificity of which is poorly understood.

Results: The MetaPred2CS web-server interfaces a sequence-based meta-predictor specifically designed to predict pairing of the histidine kinase and response-regulator proteins forming TCSs. MetaPred2CS integrates six sequence-based methods using a support vector machine classifier and has been intensively tested under different benchmarking conditions: (i) species specific gene sets; (ii) neighbouring vs. orphan pairs; and (iii) k-fold cross validation on experimentally validated datasets.

Availability: Web server at: http://metapred2cs.ibers.aber.ac.uk/, Source code: https://github.com/martinjvickers/MetaPred2CS or implemented as Virtual Machine at: http://metapred2cs.ibers.aber.ac.uk/download
Original languageEnglish
Pages (from-to)3339-3341
Number of pages3
JournalBioinformatics
Volume32
Issue number21
Early online date04 Jul 2016
DOIs
Publication statusPublished - 01 Nov 2016

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