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

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 versus orphan pairs; and (iii) k-fold cross validation on experimentally validated datasets.
Availability and Implementation: 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
Contact: [e-mail]
Supplementary information: Supplementary data are available at Bioinformatics online.

Source: Bioinformatics - October 24, 2016 Category: Bioinformatics Authors: Kara, A., Vickers, M., Swain, M., Whitworth, D. E., Fernandez-Fuentes, N. Tags: SEQUENCE ANALYSIS Source Type: research