Author

Victor Chukwudi Osamor

Covenant UniversityORCID 0000-0003-1868-0967Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

David EnomaiD· 1 shared Olubanke Olujoke OgunlanaiD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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1 shared paperBioinformatics

David EnomaORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintOct 27, 2023

Extreme gradient boosting machine learning algorithm identifies genome-wide relevant genetic variants in prostate cancer risk prediction.

David Enoma, Victor Chukwudi Osamor, Olubanke Olujoke Ogunlana

The paper uses XGBoost to identify genetic variants associated with prostate cancer risk, finding 2798 SNPs linked to 847 genes with non-linear interactions.

4 citations

humanGWAS summary statistics

𝕏 PostBluesky