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Improving the Interpretability of Random Forest Models of Genetic Association in the Presence of Non-Additive Interactions

(2020)10.21203/rs.3.rs-29752/v1Source: DataRank Database

Improving the Interpretability of Random Forest Models of Genetic Association in the Presence of Non-Additive Interactions is a research paper (2020). On theSindex it has a DataRank of 0. It has been cited 1 time.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (9 grants)OA: goldTopics (20)IDs (PubMed, OpenAlex)

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Authors (2)

Jason H. Moore ORCID,Alena Orlenko ORCID

Live enrichment

PubMed:36284789 OpenAlex:https://openalex.org/W3178040407

Wellcome Trust

Grant: unidentified

unidentified

National Institutes of Health

Grant: 5R01AI116794-03

Biomedical Computing and Informatics Strategies for Infectious Disease Research

National Institutes of Health

Grant: 5R01LM010098-14

Bioinformatics Strategies for Genome Wide Association Studies

National Centre for the Replacement, Refinement and Reduction of Animals in Research

Grant: NC/P001076/1

Biotechnology and Biological Sciences Research Council

Grant: BBS/E/T/000PR9817

Wellcome Trust

Grant: 209558/Z/17/Z

HCRW_

Grant: RFPPB-18-1497(T)

Medical Research Council

Grant: MR/S036954/1

Medical Research Council

Grant: MR/K010468/1

goldLicense: cc-by

https://www.researchsquare.com/article/rs-29752/v1.pdf?c=1631855647000

publisherhttps://www.researchsquare.com/article/rs-29752/v1

publisherhttps://www.researchsquare.com/article/rs-29752/v1.html

https://doi.org/10.21203/rs.3.rs-29752/v1

Fields of Study

Genetic and phenotypic traits in livestockGene expression and cancer classificationBioinformatics and Genomic Networks0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

InterpretabilityAssociation (psychology)Random forestAdditive modelComputer scienceEconometricsMathematicsArtificial intelligencePsychologycarotid-cavernous fistulaendoscopyendovascular treatmenttranssphenoidal surgeryvideo