Author

Charles Huang

National Institutes of HealthORCID 0000-0003-1697-1496Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Organism:human· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Álex RodrígueziD· 1 shared Andrew W. CarrolliD· 1 shared Benedict PateniD· 1 shared Chao PengiD· 1 shared Charles J. MarkelloiD· 1 shared David H. HaussleriD· 1 shared Jordan M. EizengaiD· 1 shared Peize ZhaoiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Álex RodríguezORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintApr 20, 2023

AbFold -- an AlphaFold Based Transfer Learning Model for Accurate Antibody Structure Prediction

Chao Peng, Zelong Wang, Peize Zhao…·Charles Huang

AbFold improves antibody structure prediction by refining 3D point clouds and using unsupervised learning, achieving better accuracy than AlphaFold and IgFold for CDR loops.

3 citations

protein structuredeep learning

𝕏 PostBluesky

BioinformaticsGenome ResearchPeer-reviewedApr 28, 2022

A Complete Pedigree-Based Graph Workflow for Rare Candidate Variant Analysis

Charles J. Markello, Charles Huang, Álex Rodríguez…·Benedict Paten

The paper introduces a pedigree-aware workflow using pangenome graphs to improve variant calling in rare disease analysis, detecting more deleterious variants in probands than unaffected siblings.

6 citations

humanwhole-genome sequencing

𝕏 PostBluesky