期刊
NUCLEIC ACIDS RESEARCH
卷 44, 期 W1, 页码 W488-W493出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkw409
关键词
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资金
- Canadian Institutes of Health Research (CIHR)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Michael Smith Foundation for Health Research (MSFHR) [CI-SCH-03020(11-1)]
- CIHR
- NSERC
- Genome Canada
- Genome BC [175REG]
- MSFHR [CI-SCH-03020(11-1)]
Molecular recognition features, MoRFs, are short segments within longer disordered protein regions that bind to globular protein domains in a process known as disorder-to-order transition. MoRFs have been found to play a significant role in signaling and regulatory processes in cells. Highconfidence computational identification of MoRFs remains an important challenge. In this work, we introduce MoRFchibi SYSTEM that contains three MoRF predictors: MoRFCHiBi, a basic predictor best suited as a component in other applications, MoRFCHiBi_ Light, ideal for high-throughput predictions and MoRFCHiBi_Web, slower than the other two but best for high accuracy predictions. Results show that MoRFchibi SYSTEM provides more than double the precision of other predictors. MoRFchibi SYSTEM is available in three different forms: as HTML web server, RESTful web server and downloadable software at: http://www.chibi.ubc.ca/faculty/joerggsponer/gsponer-lab/software/morfchibi/
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