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Xiaoyue (Serafina) Mei
I am a Ph.D. candidate in the UCSF–UC Berkeley Joint Bioengineering Program. I received my B.A. in Molecular and Cellular Biology with a minor in Data Science from UC Berkeley.
My research uses computational biology and multi-omics analysis to study disease-relevant biological variation. In the Conboy Lab, I worked on aging biology, epigenetic clocks, and age-associated proteomic and epigenetic dysregulation. I am now working in the Capra Lab to identify dominant-and-dispensable genes as potential therapeutic targets using genetic, functional, and multi-omics data.
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Research
My work focuses on building interpretable data-driven approaches to connect molecular patterns with biological mechanisms and clinically relevant outcomes. Representative papers are shown below.
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Human microphysiological systems of aging recreate the in vivo process expediting evaluation of anti-geronic strategies
Lin Qi, Yuchen He, Alexandra Sviercovich, Xiaoyue Mei, Erzhen Chen, Yihan Xia, Michael J. Conboy, Irina M. Conboy & Andreas Stahl
Nature Biomedical Engineering, 2026
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Leveraging human genetic variation to therapeutically target hundreds of genes with dominant & dispensable disease alleles
Grace D. Ramey, Quinn T. Cowan, Akshita G. Saxena, Bria L. Macklin, Hannah L. Watry, Xiaoyue Mei, Philip Dierks, Luke M. Judge, Bruce R. Conklin & John A. Capra
medRxiv, 2026
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Fail-tests of DNA methylation clocks, and development of a noise barometer for measuring epigenetic pressure of aging and disease
Xiaoyue Mei *, Joshua Blanchard *, Connor Luellen, Michael J. Conboy & Irina M. Conboy
Aging, Volume 15, Issue 17, pages 8552-8575 cover (2023)
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perspective
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Old plasma dilution reduces human biological age: a clinical study
Daehwan Kim, Dobri D. Kiprov, Connor Luellen, Michael Lieb, Chao Liu, Etsuko Watanabe, Xiaoyue Mei, Kaitlin Cassaleto,
Joel Kramer, Michael J. Conboy & Irina M. Conboy
GeroScience, 44, pages 2701-2720 (2022)
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