Journal article
SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models
X Wang, C Li, F Li, VS Sharma, J Song, GI Webb
BMC Bioinformatics | BMC | Published : 2019
Open access
Abstract
Background: S-sulphenylation is a ubiquitous protein post-translational modification (PTM) where an S-hydroxyl (-SOH) bond is formed via the reversible oxidation on the Sulfhydryl group of cysteine (C). Recent experimental studies have revealed that S-sulphenylation plays critical roles in many biological functions, such as protein regulation and cell signaling. State-of-the-art bioinformatic advances have facilitated high-throughput in silico screening of protein S-sulphenylation sites, thereby significantly reducing the time and labour costs traditionally required for the experimental investigation of S-sulphenylation. Results: In this study, we have proposed a novel hybrid computational f..
View full abstractGrants
Awarded by Australian Research Council
Funding Acknowledgements
This work was supported by grants from the Australian Research Council (ARC) (LP110200333 and DP120104460), National Health and Medical Research Council of Australia (NHMRC) (1144652, 490989), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (R01 AI111965), and a Major Inter-Disciplinary Research (IDR) Grant Awarded by Monash University (201402). C.L. is currently supported by an NHMRC CJ Martin Early Career Research Fellowship (1143366). The funding bodies ARC, NHMRC, NIH, and Monash University had no role in the design of the study; collection, analysis, and interpretation of data; or in writing the manuscript.