Cited by 418Bioinformatics and Genomic NetworksBiomedical Text Mining and OntologiesGenomics and Rare Diseases

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Computational tools for prioritizing candidate genes: boosting disease gene discovery

Moreau, Yves, Tranchevent, Léon-Charles·2012·Nature Reviews Genetics

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Abstract

At different stages of any research project, molecular biologists need to choose - often somewhat arbitrarily, even after careful statistical data analysis - which genes or proteins to investigate further experimentally and which to leave out because of limited resources. Computational methods that integrate complex, heterogeneous data sets - such as expression data, sequence information, functional annotation and the biomedical literature - allow prioritizing genes for future study in a more informed way. Such methods can substantially increase the yield of downstream studies and are becoming invaluable to researchers.

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Authors: Moreau, Y., & Tranchevent, L.-C.
Affiliations: KU Leuven (BE)
Corresponding author: Moreau, Yves
Tranchevent, Léon-Charles
ORCID: Moreau, Yves
Tranchevent, Léon-Charles
Venue: Nature Reviews Genetics
Publisher: Springer Science and Business Media LLC
Published: 2012-07-03
Volume: 13
Issue: 8
Pages: 523-536
ISSN: 1471-0056 (ISSN-L)
1471-0064
DOI: 10.1038/nrg3253
OpenAlex: W2090247362
Cited by: 417
References: 134
Citations by year: 2026: 5 · 2025: 4 · 2024: 6 · 2023: 15 · 2022: 19 · 2021: 21 · 2020: 31 · 2019: 36 · 2018: 36 · 2017: 42 · 2016: 45 · 2015: 49 · 2014: 52 · 2013: 41 · 2012: 15
FWCI: 4.58
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Nature Reviews Genetics (publishedVersion)
PubMed (publishedVersion)
Funders: FP7 Health
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Keywords: gene prioritization, candidate genes, disease gene discovery, computational tools, heterogeneous data integration, expression data, functional annotation, biomedical text mining, genetic linkage, omics data
MeSH terms: Animals, Humans, Models, Genetic, Computational Biology, Genetic Predisposition to Disease, Databases, Genetic, Mice, Genetic Association Studies, Haploinsufficiency

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Computational tools for prioritizing candidate genes: boosting disease gene discovery

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