Author

Kaiqian Zhang

Princeton UniversityORCID 0000-0002-6847-6473Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:ChIP-seq· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Research Focus:polygenic risk· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Joshua L. WetzeliD· 1 shared Joshua M. AkeyiD· 1 shared Mona SinghiD· 1 shared Rob BiermaniD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 2 mutual co-author links

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1 shared paperMolecular Biology

Joshua L. WetzelORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintAug 29, 2026

A Principled Framework for Using Correlated Traits to Improve Risk Prediction

Kaiqian Zhang, Rob Bierman, Joshua M. Akey

This paper develops a framework to improve polygenic risk scores by using correlated traits, showing that helper traits can significantly enhance prediction accuracy for type 2 diabetes.

DOI 10.64898/2026.08.23.746504

humanGWAS summary statistics

𝕏 PostBluesky

Molecular BiologyGenome ResearchPeer-reviewedSep 1, 2022

Learning probabilistic protein-DNA recognition codes from DNA-binding specificities using structural mappings

Joshua L. Wetzel, Kaiqian Zhang, Mona Singh

This paper introduces rCLAMPS, a method to infer protein-DNA recognition codes from DNA-binding specificities, enabling prediction of TF specificities and mutation effects.

19 citations

DNA methylationChIP-seq

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