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Bioinformatics. 2015 Jun 15;31(12):2052-3. doi: 10.1093/bioinformatics/btv073. Epub 2015 Feb 8.

FUN-L: gene prioritization for RNAi screens.

Author information

1
Research Department of Structural & Molecular Biology, University College London, London, UK, Cell Biology/Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, Inflamex-Laboratoire Analyse Géométrie et Applications, Université Paris Nord-Sorbonne, France, Structural Bioinformatics Group, Spanish National Cancer Research Centre (CNIO) and Spanish National Bioinformatics Institute (INB), Madrid, Spain, Institute of Molecular and Cell Biology, and Institute of Computer Science, University of Tartu, Tartu, Estonia and Department of Molecular Biology and Biochemistry-CIBER de Enfermedades Raras, University of Malaga, Malaga, Spain.

Abstract

MOTIVATION:

Most biological processes remain only partially characterized with many components still to be identified. Given that a whole genome can usually not be tested in a functional assay, identifying the genes most likely to be of interest is of critical importance to avoid wasting resources.

RESULTS:

Given a set of known functionally related genes and using a state-of-the-art approach to data integration and mining, our Functional Lists (FUN-L) method provides a ranked list of candidate genes for testing. Validation of predictions from FUN-L with independent RNAi screens confirms that FUN-L-produced lists are enriched in genes with the expected phenotypes. In this article, we describe a website front end to FUN-L.

AVAILABILITY AND IMPLEMENTATION:

The website is freely available to use at http://funl.org

PMID:
25667547
DOI:
10.1093/bioinformatics/btv073
[Indexed for MEDLINE]

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