Author

Hanchen Huang

Duke University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genetic & Genomic Medicine· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:differential expression· 2 Assay:DNA methylation· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Lily WangiD· 2 shared Xi CheniD· 2 shared Aron BercziD· 1 shared Brian David LehmanniD· 1 shared Chao WuiD· 1 shared David LukacsovichiD· 1 shared J. Joshua Smith· 1 shared Janet A. AlvareziD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Lily WangORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

A data-driven modeling framework for mapping genotypes to synthetic microbial community functions

Yili Qian, Sarvesh D. Menon, Hanchen Huang, Nick Quinn-Bohmann, Sean M. Gibbons, Ophelia S. Venturelli

This paper introduces a data-driven model to predict synthetic microbial community functions from genetic features, enabling predictions for new species not included in training data.

Cell Systems · Jul 1, 2026Peer-reviewedSystems Biology

An Integrative Multi-Omics Random Forest Framework for Robust Biomarker Discovery

Wei Zhang, Hanchen Huang, Lily Wang, Brian David Lehmann, Xi Chen

This paper introduces a multivariate random forest framework for multi-omics biomarker discovery, showing it outperforms existing methods in identifying biologically relevant biomarkers and pathways.

GigaScience · Dec 8, 2025Peer-reviewedBioinformatics

Integrating Tumor and Organoid DNA Methylation Profiles Reveals Robust Predictors of Chemotherapy Response in Rectal Cancer

David Lukacsovich, Wini V. Zambare, Chao Wu, Hanchen Huang, Wei Zhang, Min Jung Kim, Janet A. Alvarez, Aron Bercz, Philip B. Paty, Paul Bernard Romesser, Lily Wang, J. Joshua Smith, Xi Chen

This study integrates DNA methylation profiles from tumors and organoids to identify CpGs predictive of chemotherapy response in rectal cancer, finding a methylation risk score significantly predicts progression-free survival.

medRxiv · Feb 28, 2025 · PreprintGenetic & Genomic Medicine