Author

Yiru Zhu

Northwestern 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

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Bioengineering· 1 Cell Biology· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:development & morphogenesis· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Francesca E. DuncaniD· 2 shared Hoi Chang LeeiD· 2 shared David H. GireiD· 1 shared Hannes CampoiD· 1 shared Jeffrey PeaiD· 1 shared Jesse T. MilesiD· 1 shared John ProudfootiD· 1 shared Kevan S. KidderiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersBioengineering

Francesca E. DuncanORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Biocompatible designated Resin-3D-printed polymers exhibit reproductive toxicity prevented by Parylene-C

Hannes Campo, Uyen Tran, Yiru Zhu, Hoi Chang Lee, Francesca E. Duncan

The paper develops MEIOSA to test biocompatibility of 3D-printed resins using oocytes and finds Parylene-C coating prevents toxicity in all tested resins.

bioRxiv · Jun 10, 2026 · PreprintBioengineering

A complex phenotypic assay of mammalian oocyte maturation identifies compounds that block meiotic progression for non-hormonal contraceptive discovery

Jeffrey Pea, Yiru Zhu, Hoi Chang Lee, Lauren Haky, John Proudfoot, Richard M. Nelson, Francesca E. Duncan

This study screens compounds to identify those that block meiotic progression in mouse oocytes, offering potential non-hormonal contraceptive candidates.

bioRxiv · Oct 15, 2025 · PreprintCell Biology

A machine learning approach for detecting vicarious trial and error behaviors

Jesse T. Miles, Kevan S. Kidder, Ziheng Wang, Yiru Zhu, David H. Gire, Sheri J. Y. Mizumori

The paper uses machine learning to classify vicarious trial and error behaviors in rats, finding that trajectory-based features outperform oscillation-based features.

Frontiers in Neuroscience · Jul 7, 2021Peer-reviewedNeuroscience