Hum-mPLoc: an ensemble classifier for large-scale human protein subcellular location prediction by incorporating samples with multiple sites. Proteins may simultaneously exist at, or move between, two or more different subcellular locations. Proteins with multiple locations or dynamic feature of this kind are particularly interesting because they may have some very special biological functions intriguing to investigators in both basic research and drug discovery. For instance, among the 6408 human protein entries that have experimentally observed subcellular location annotations in the Swiss-Prot database (version 50.7, released 19-Sept-2006), 973 ( approximately 15%) have multiple location sites. The number of total human protein entries (except those annotated with ”fragment” or those with less than 50 amino acids) in the same database is 14,370, meaning a gap of (14,370-6408)=7962 entries for which no knowledge is available about their subcellular locations. Although one can use the computational approach to predict the desired information for the gap, so far all the existing methods for predicting human protein subcellular localization are limited in the case of single location site only. To overcome such a barrier, a new ensemble classifier, named Hum-mPLoc, was developed that can be used to deal with the case of multiple location sites as well. Hum-mPLoc is freely accessible to the public as a web server at http://220.127.116.11/bioinf/hum-multi. Meanwhile, for the convenience of people working in the relevant areas, Hum-mPLoc has been used to identify all human protein entries in the Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The large-scale results thus obtained have been deposited in a downloadable file prepared with Microsoft Excel and named ”Tab_Hum-mPLoc.xls”. This file is available at the same website and will be updated twice a year to include new entries of human proteins and reflect the continuous development of Hum-mPLoc.
Keywords for this software
References in zbMATH (referenced in 26 articles )
Showing results 21 to 26 of 26.
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- Chen, Ying-Li; Li, Qian-Zhong: Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo-amino acid composition (2007)
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- Kurgan, Lukasz A.; Stach, Wojciech; Ruan, Jishou: Novel scales based on hydrophobicity indices for secondary protein structure (2007)
- Shen, Yao Qing; Burger, Gertraud: ’Unite and conquer’: Enhanced prediction of protein subcellular localization by integrating multiple specialized tools (2007) ioport