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Rethinking GWAS: how lessons from genetic screens and artificial intelligence could reveal biological mechanisms

Bioinformatics(2025)10.1093/bioinformatics/btaf153Source: DataRank Database

Rethinking GWAS: how lessons from genetic screens and artificial intelligence could reveal biological mechanisms is a research paper published in Bioinformatics (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.

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Open Access1 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (5 grants)OA: goldTopics (15)IDs (PubMed, PMC)

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Accessible (1/2)

Open Access

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Authors (1)

Dennis J. Hazelett ORCID

Live enrichment

PubMed:40198231 PMC:PMC12014097

National Institutes of Health

Grant: R01LM010098

National Institutes of Health

Grant: U01AG066833

National Institutes of Health

Grant: 1R01AG066833-01A1

Artificial Intelligence Strategies for Alzheimer's Disease Research

National Institutes of Health

Grant: 5R01LM010098-14

Bioinformatics Strategies for Genome Wide Association Studies

National Institutes of Health

Grant: 3U01AG066833-04S1

Artificial Intelligence Strategies for Alzheimer's Disease Research

goldLicense: cc-by

publisherhttps://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaf153/62890228/btaf153.pdf

publisherhttps://academic.oup.com/bioinformatics/article-pdf/41/4/btaf153/62890228/btaf153.pdf

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12014097

Europe_PMChttps://europepmc.org/articles/PMC12014097

Europe_PMChttps://europepmc.org/articles/PMC12014097?pdf=render

Fields of Study

0206 medical engineering02 engineering and technology

MeSH Terms

AnimalsHumansComputational BiologyPhenotypeArtificial IntelligenceGenome-Wide Association Study

Keywords

PhenotypeArtificial IntelligenceHumansAnimalsComputational BiologyReviewGenome-Wide Association Study