ENDEAVOUR Update: a Web Resource for Gene Prioritization in Multiple Species

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2008 May 30

PMID 18508807

Citations 96

Authors

Leon-Charles Tranchevent

Roland Barriot

Shi Yu

Steven Van Vooren

Peter Van Loo

Bert Coessens

Bart De Moor

Stein Aerts

Yves Moreau

Affiliations

Soon will be listed here.

Abstract

Endeavour (http://www.esat.kuleuven.be/endeavourweb; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes. Using a training set of genes known to be involved in a biological process of interest, our approach consists of (i) inferring several models (based on various genomic data sources), (ii) applying each model to the candidate genes to rank those candidates against the profile of the known genes and (iii) merging the several rankings into a global ranking of the candidate genes. In the present article, we describe the latest developments of Endeavour. First, we provide a web-based user interface, besides our Java client, to make Endeavour more universally accessible. Second, we support multiple species: in addition to Homo sapiens, we now provide gene prioritization for three major model organisms: Mus musculus, Rattus norvegicus and Caenorhabditis elegans. Third, Endeavour makes use of additional data sources and is now including numerous databases: ontologies and annotations, protein-protein interactions, cis-regulatory information, gene expression data sets, sequence information and text-mining data. We tested the novel version of Endeavour on 32 recent disease gene associations from the literature. Additionally, we describe a number of recent independent studies that made use of Endeavour to prioritize candidate genes for obesity and Type II diabetes, cleft lip and cleft palate, and pulmonary fibrosis.

Citing Articles

Identification of the novel FOXP3-dependent T cell transcription factor MEOX1 by high-dimensional analysis of human CD4 T cells.

Bassler K, Schmidleithner L, Shakiba M, Elmzzahi T, Kohne M, Floess S Front Immunol. 2023; 14:1107397.

PMID: 37559728 PMC: 10407399. DOI: 10.3389/fimmu.2023.1107397.

Exome sequencing to explore the possibility of predicting genetic susceptibility to the joint occurrence of polycystic ovary syndrome and Hashimoto's thyroiditis.

Zeber-Lubecka N, Suchta K, Kulecka M, Kluska A, Piatkowska M, Dabrowski M Front Immunol. 2023; 14:1193293.

PMID: 37545519 PMC: 10397507. DOI: 10.3389/fimmu.2023.1193293.

Disease gene prediction with privileged information and heteroscedastic dropout.

Shu J, Li Y, Wang S, Xi B, Ma J Bioinformatics. 2021; 37(Suppl_1):i410-i417.

PMID: 34252957 PMC: 8275341. DOI: 10.1093/bioinformatics/btab310.

Biological Network Mining.

Yue Z, Yan D, Guo G, Chen J Methods Mol Biol. 2021; 2328:139-151.

PMID: 34251623 DOI: 10.1007/978-1-0716-1534-8_8.

Deregulated Adhesion Program in Palatal Keratinocytes of Orofacial Cleft Patients.

Mammadova A, Carels C, Zhou J, Gilissen C, Helmich M, Bian Z Genes (Basel). 2019; 10(11).

PMID: 31652793 PMC: 6895790. DOI: 10.3390/genes10110836.

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