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Protein Sci. 2018 Jan;27(1):195-201. doi: 10.1002/pro.3297. Epub 2017 Oct 24.

The SubCons webserver: A user friendly web interface for state-of-the-art subcellular localization prediction.

Author information

1
Science for Life Laboratory, Stockholm University, 171 21, Solna, Sweden.
2
Department of Biochemistry and Biophysics, Stockholm University, 106 91, Stockholm, Sweden.
3
Sweden Bioinformatics Infrastructure for Life Sciences (BILS), Stockholm University, Stockholm, Sweden.

Abstract

SubCons is a recently developed method that predicts the subcellular localization of a protein. It combines predictions from four predictors using a Random Forest classifier. Here, we present the user-friendly web-interface implementation of SubCons. Starting from a protein sequence, the server rapidly predicts the subcellular localizations of an individual protein. In addition, the server accepts the submission of sets of proteins either by uploading the files or programmatically by using command line WSDL API scripts. This makes SubCons ideal for proteome wide analyses allowing the user to scan a whole proteome in few days. From the web page, it is also possible to download precalculated predictions for several eukaryotic organisms. To evaluate the performance of SubCons we present a benchmark of LocTree3 and SubCons using two recent mass-spectrometry based datasets of mouse and drosophila proteins. The server is available at http://subcons.bioinfo.se/.

KEYWORDS:

machine learning; sequence analysis; subcellular localization

PMID:
28901589
PMCID:
PMC5734273
[Available on 2019-01-01]
DOI:
10.1002/pro.3297
[Indexed for MEDLINE]

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