Author

Haichen Zhang

Primary ORCID profile (0000-0001-9000-589X · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Haichen ZhangiD1 paper · University of Maryland, Baltimore

Biology Disciplines

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Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Abigail SvedeniD· 1 shared Adolfo CorreaiD· 1 shared Alanna C. MorrisoniD· 1 shared Alex P. ReineriD· 1 shared Allan R LinnebergiD· 1 shared Andrew D. MorrisiD· 1 shared Andy Dahl· 1 shared Angélica Graciela Martínez-HernándeziD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Abigail SvedenORCID

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1 paper

Recent·Most cited

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Julia K. Goodrich, Moriel Singer‐Berk, Rachel Son, Abigail Sveden, Jordan C. Wood, Eleina M. England, Joanne B. Cole, Ben Weisburd, Nick Watts, Lizz Caulkins, Peter Dornbos, Ryan Koesterer, Zachary Zappala, Haichen Zhang, Kristin A. Maloney, , Kerrin S. Small

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

Nature Communications · Jun 9, 2021Peer-reviewedGenetic & Genomic Medicine