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Dr. Wenyu Zhou

Wenyu Zhou, Ph.D. is a Bioinformatics Research Scientist at Stanford University who enjoys integrating different types of high-throughput data (next-generation sequencing-based, mass spectrometry-based and others) and implementing advanced statistical modelings.

Wenyu has published in Nature, Nature Medicine, Cell Stem Cell, Cell Systems, and others, and actively serves as a reviewer for a number of scientific journals in the genomics field.

Wenyu earned her Ph.D. in Biology in 2012, at the University of Washington in Seattle. She worked on lineage mapping and metabolic regulation in early embryogenesis and discovered interesting similarities between cancer and stem cells. Wenyu employed cutting-edge techniques including SOLiD next-generation sequencing for genome-wide mutation detection, and Seahorse Extracellular Flux Analyzer for real-time measurement of cellular bioenergetics. She has manipulated the genetic level of study models and thus created a hyper-mutable mice strain and introduced gene expression through lentiviral infection.

In 2013, Wenyu began her Postdoctoral Training at Stanford University under Dr. Michael Snyder. She worked on Integrative Human Microbiome Project (iHMP) with a focus on prediabetes, directing and supervising daily activities of the project from clinical regulation/management to laboratory research. As well, she was tracking molecular changes in both human host and microbiome at a variety of physiological stages (healthy/diseased) through large-scale and integrated omics profiling.

Her projects include:

  • Intraspecies Microbial Diversity in the Human Gut, where she designed the experimental scheme, generating next-generation sequencing data with matching clinics and analyzed microbial diversity beyond the species level for the first time in the field by using synthetic long-reads. Her Synthetic long-read sequencing reveals intraspecies diversity in the human microbiome was published in Nature in 2015. 
  • Microbial Taxonomic and Functional Changes Induced by Dietary Supplements: Wenyu established a cohort consisting of human subjects going through periods of dietary supplements. She  profiled and analyzed microbial changes longitudinally at the taxonomic and functional level, and integrated large-scale omics using sophisticated statistics on microbial data, plasma and urine metabolic profiles, clinical measurements, and other environmental/lifestyle related entities.
  • Microbial Expression and Regulation in Respiratorily Infected Individuals: Here Wenyu designed and performed all experiments to profile omics changes in the microbiome. She profiled multi meta-omics of the microbiome to study the molecular expression and regulation by examining meta-genomes, meta-transcriptomes, and meta-proteomes at the same time, and associated meta-omics data with clinical phenotypes by regression models.

She coauthored Integrative personal omics profiles during periods of weight gain and loss, Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information, Hypoxia-inducible factors have distinct and stage-specific roles during reprogramming of human cells to pluripotency, and Derivation of naive human embryonic stem cells.

After 5 years of postdoctoral research, Wenyu became a Bioinformatics Research Scientist in 2018 at Stanford, and since then she has been publishing extensively.

Her papers include:

Wenyu is endlessly amazed by the order and intricacy of life in its forms and interconnections. She enjoys research adventures and discoveries, leveraging her expertise in integrating and implementing different types of data and statistical modelings.

“Individuals are aging at different rates as well as potentially through different biological mechanisms, which provide the opportunities for individualized, targeted intervention”, says Wenyu Zhou.

Wenyu was a 2020 Undoing Aging Speaker and as well she lectured on Quantifying the environmental influences on human health through the lens of human-microbial interactions at the Center for Computational Biology at UC Berkeley.

Read Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. Read Wearable Sensors Spot Lyme Disease, Study shows how big data can be used for personal health, and “Ageotypes” provide window into how individuals age.

Visit her LinkedIn profile and Google Scholar Profile.