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Bioinformatics. 2014 Jun 1;30(11):1601-8. doi: 10.1093/bioinformatics/btu074. Epub 2014 Feb 3.

The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities.

Author information

1
Gene Function and Evolution, Centre for Genomic Regulation (CRG), Dr. Aiguader 88 and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain.

Abstract

MOTIVATION:

The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups.

DESCRIPTION:

The central part of the cleverSuite is the cleverMachine (CM), an algorithm that performs statistics on protein sequences by comparing their physico-chemical propensities. The second element is called cleverClassifier and builds on top of the models generated by the CM to allow classification of new datasets.

RESULTS:

We applied the cleverSuite to predict secondary structure properties, solubility, chaperone requirements and RNA-binding abilities. Using cross-validation and independent datasets, the cleverSuite reproduces experimental findings with great accuracy and provides models that can be used for future investigations.

AVAILABILITY:

The intuitive interface for dataset exploration, analysis and prediction is available at http://s.tartaglialab.com/clever_suite.

PMID:
24493033
PMCID:
PMC4029037
DOI:
10.1093/bioinformatics/btu074
[Indexed for MEDLINE]
Free PMC Article

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