Dr. Qingzhou Zhang
Computational Systems Biologist & Bioinformatician
I build and lead computational programs that transform high-dimensional omics data into actionable biological discovery. My work spans single-cell genomics, spatial transcriptomics, and machine learning frameworks to decode the regulatory mechanisms of disease.
With 15+ years of computational biology leadership and first/co-authored publications in Nature Biotechnology, Cell Systems, and Nature Communications, I develop reproducible analytical frameworks for complex biological challenges.
Omics
with Johnson 101
Omics with Johnson 101
A rigorous foundational curriculum on the physical, mathematical, and statistical principles of bioinformatics. Move beyond black-box pipelines to deeply understand model assumptions, sequencing physics, and statistical overdispersion.
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Master sequencing mechanics, error models, and foundational statistical algorithms -
Select correct generalized linear & negative binomial models for biological variance -
Design containerized, version-controlled, and reproducible computational pipelines
Case Studies
In-depth spatiotemporal, single-cell, and transcriptomic analyses.
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Open Source Tools
Bioconductor packages, PyPI libraries, and automated bioinformatics workflows.
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Publications
Articles, perspectives, and reviews in leading peer-reviewed journals.
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