Prosiectau fesul blwyddyn
BACKGROUND: Two component systems (TCS) are signalling complexes manifested by a histidine kinase (receptor) and a response regulator (effector). They are the most abundant signalling pathways in prokaryotes and control a wide range of biological processes. The pairing of these two components is highly specific, often requiring costly and time-consuming experimental characterisation. Therefore, there is considerable interest in developing accurate prediction tools to lessen the burden of experimental work and cope with the ever-increasing amount of genomic information.
RESULTS: We present a novel meta-predictor, MetaPred2CS, which is based on a support vector machine. MetaPred2CS integrates six sequence-based prediction methods: in-silico two-hybrid, mirror-tree, gene fusion, phylogenetic profiling, gene neighbourhood, and gene operon. To benchmark MetaPred2CS, we also compiled a novel high-quality training dataset of experimentally deduced TCS protein pairs for k-fold cross validation, to act as a gold standard for TCS partnership predictions. Combining individual predictions using MetaPred2CS improved performance when compared to the individual methods and in comparison with a current state-of-the-art meta-predictor.
CONCLUSION: We have developed MetaPred2CS, a support vector machine-based metapredictor for prokaryotic TCS protein pairings. Central to the success of MetaPred2CS is a strategy of integrating individual predictors that improves the overall prediction accuracy, with the in-silico two-hybrid method contributing most to performance. MetaPred2CS outperformed other available systems in our benchmark tests, and is available online at http://metapred2cs.ibers.aber.ac.uk , along with our gold standard dataset of TCS interaction pairs.
|Rhif yr erthygl||297|
|Dyddiad ar-lein cynnar||18 Medi 2015|
|Dynodwyr Gwrthrych Digidol (DOIs)|
|Statws||Cyhoeddwyd - 2015|
Ôl bysGweld gwybodaeth am bynciau ymchwil 'Genome-wide prediction of prokaryotic two-component system networks using a sequence-based meta-predictor'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.
- 1 Wedi Gorffen
Bioinformatics and genomic and phenomic platform development
Armstead, I., Boyle, R., Doonan, J., Fernandez Fuentes, N., Gay, A., Hegarty, M., Huang, L., Neal, M., Swain, M. & Thomas, I.
Biotechnology and Biological Sciences Research Council
01 Ebr 2012 → 31 Maw 2017
Prosiect: Ymchwil a ariannwyd yn allanol