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 versus orphan pairs; and (iii) k-fold cross validation on experimentally validated datasets.

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Kara, A., Vickers, M., Swain, M., Whitworth, D. E., & Fernandez-Fuentes, N. (2016). MetaPred2CS: A sequence-based meta-predictor for protein-protein interactions of prokaryotic two-component system proteins. Bioinformatics, 32(21), 3339–3341. https://doi.org/10.1093/bioinformatics/btw403

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