Author

Vikram R. Shaw

Baylor College of MedicineORCID 0000-0002-1172-5686Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 2 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1 Approach:statistical model· 1

Frequent Co-Authors

Christopher Ian AmosiD· 2 shared Jinyoung ByuniD· 2 shared Alex T. RamseyiD· 1 shared Ariya ChaloemtoemiD· 1 shared Dana B. HancockiD· 1 shared Dheeman SahaiD· 1 shared Eric Otto JohnsoniD· 1 shared Gretchen SaundersiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Christopher Ian AmosORCID

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2 papers

Recent·Most cited

A Polygenic Score for Smoking Persistence Captures Differences in Cessation Age

Ariya Chaloemtoem, Yoonhoo Chang, Louis W. Fox, Vikram R. Shaw, Jinyoung Byun, Tony Chen, Ricardo Cortez Cardoso Penha, Dana B. Hancock, Rayjean J. Hung, Eric Otto Johnson, Alex T. Ramsey, Nancy L. Saccone, Gretchen Saunders, Haoyu Zhang, James McKay, , Laura Jean Bierut

This paper develops a polygenic score for smoking persistence and finds it is associated with earlier or later cessation ages across diverse populations.

medRxiv · Oct 26, 2026 · PreprintGenetic & Genomic Medicine

Uncovering High-Order Epistatic Interactions in GWAS via a Machine Learning-Based Feature Engineering Framework

Jinyoung Byun, Dheeman Saha, Younghun Han, Vikram R. Shaw, Katherine Siminovitch, Christopher Ian Amos

The paper introduces a machine learning framework to detect high-order genetic interactions in GWAS by encoding decision paths from classification trees as features, improving model accuracy and interpretability.

bioRxiv · Aug 9, 2026 · PreprintGenomics