Author

Boyan Zhou

New York UniversityORCID 0000-0001-7067-4578Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Research Focus:cell-cell communication· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Huilin LiiD· 3 shared Jiyuan HuiD· 2 shared Alejandro PirontiiD· 1 shared Ann Marie SchmidtiD· 1 shared Chan WangiD· 1 shared Chan WangiD· 1 shared Fen WuiD· 1 shared Gary C. CurhaniD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersBioinformatics

Huilin LiORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 21, 2026

Vritra: gene-specific reference construction for species-resolved functional profiling of metagenomic and metatranscriptomic data

Boyan Zhou, Menghan Liu, Gary C. Curhan…·Huilin Li

Vritra constructs gene-specific references for metagenomic and metatranscriptomic data to enable species-resolved functional profiling and uncover gene-taxa associations.

DOI 10.64898/2026.09.17.752478

metagenomicsstatistical model

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedJan 21, 2026

Joint Modeling of Longitudinal Biomarker and Survival Outcomes with the Presence of Competing Risk in Nested Case-Control Studies with Application to the TEDDY Microbiome Dataset

Yanan Zhao, TingFang Lee, Boyan Zhou…·Jiyuan Hu

The paper introduces JM-NCC, a joint modeling framework for nested case-control studies with competing risks, applied to the TEDDY microbiome dataset to analyze biomarker and survival outcomes.

DOI 10.1093/bioinformatics/btag038

metagenomicsstatistical model

𝕏 PostBluesky

BioinformaticsMicrobiology SpectrumPeer-reviewedSep 23, 2024

An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data

Boyan Zhou, Chan Wang, Gregory Putzel…·Huilin Li

LongStrain improves strain-level analysis in longitudinal metagenomic data by jointly modeling strain proportions and genomic variants, outperforming existing methods in variant calling and proportion estimation.

6 citations

metagenomicsstatistical model

𝕏 PostBluesky