Author

Katherine Wu

Brigham and Women's HospitalPrimary ORCID profile (0000-0002-0472-0166 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Katherine WuiD1 paper · New York University

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1

Frequent Co-Authors

Aaron StreetsiD· 1 shared Achille NazaretiD· 1 shared Adam GayosoiD· 1 shared Carlos N. Talavera-LópeziD· 1 shared Catherine H. FreudenreichiD· 1 shared Chenling A. XuiD· 1 shared Edouard MehlmaniD· 1 shared Eduardo da Veiga BeltrameiD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

Aaron StreetsORCID

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Author profile →

3 papers

Recent·Most cited

Oral Gut Microbial Axis in Inflammatory Bowel Disease and Primary Sclerosing Cholangitis

Shanlin Ke, Z Hong Zhou, Xiaole Yin, Yiyan Yang, Zheng Sun, Fernanda Quevedo, Nadine Javier, Malav Dave, Katherine Wu, Shaikh Danish Mahmood, Yang‐Yu Liu, Joshua R. Korzenik

The study identifies oral microbial signatures associated with IBD and PSC and their potential translocation to the gut, supported by external validation.

bioRxiv · Jul 16, 2026 · PreprintMicrobiology

THO and TRAMP complexes prevent transcription-replication conflicts, DNA breaks, and CAG repeat contractions

Rebecca E. Brown, Xiaofeng A. Su, Stacey Fair, Katherine Wu, Lauren Verra, Robyn M. Jong, Kristin R. Andrykovich, Catherine H. Freudenreich

This study shows that THO and TRAMP complexes prevent CAG repeat instability by reducing RNA polymerase stalling and transcription-replication conflicts in yeast.

PLoS Biology · Dec 27, 2022Peer-reviewedGenetics

scvi-tools: a library for deep probabilistic analysis of single-cell omics data

Adam Gayoso, Romain Lopez, Galen K. Xing, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong, Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran, Gabriel Misrachi, Achille Nazaret, Oscar Clivio, , Nir Yosef

scvi-tools provides a Python package for probabilistic analysis of single-cell omics data, offering standardized interfaces and extensible tools for various analysis tasks.

Nature Biotechnology · Feb 1, 2022Peer-reviewedBioinformatics