Curriculum Vitae

Executive Summary

Zhenguo Zhang · [email protected] · GitHub · LinkedIn

I’m a passionate bioinformatics scientist and mentor working to transform healthcare, particularly cancer diagnostics and MRD, through data-driven analysis and AI-assisted workflows. I bring 20+ years of R&D experience in multi-omic data analysis, biomarker discovery, and translational research. My deep understanding of gene regulation, genome evolution, and cancer genomics is reflected in 20+ peer-reviewed publications. I have led analyses for NGS assay development and cancer biomarker discovery and built high-performance cancer detection machine learning models. My experience spans the full cancer diagnostics product development lifecycle, from initial ideas and experimental design to computational execution and commercial product prototyping, with expertise in four areas:

Scalable NGS pipeline development: Developed dozens of robust Nextflow pipelines to shorten processing time and ensure reproducibility.

Reproducible data analysis and visualization: Created hundreds of R Markdown and Jupyter workflows to automate biological data analysis and generate publication-ready figures.

Machine learning and AI: Built cancer detection models using DNA methylation and RNA markers, and applied AI to automate data analysis and biomarker discovery workflows.

Project management: Delivered dozens of high-priority NGS projects through strategic planning, effective execution, and close collaboration with lab scientists and DevOps, earning a 2024 Annual Employee Award at Exact Sciences.

Professional Experience

Exact Sciences (now Abbott)

San Diego, CA

Staff Bioinformatics Scientist · March 2026–September 2026

• Led cancer biomarker discovery through strategic planning, pipeline architecture, cross-functional collaboration, and AI adoption
• Spearheaded fragmentomic and RNA biomarker discovery for early cancer detection
• Applied AI workflows to reduce programming cycle times by 50%, support ideation, and enhance predictive modeling

Senior Bioinformatics Scientist · April 2023–February 2026

• Drove cancer product development by identifying methylation/RNA markers using statistical and machine learning modeling
• Slashed NGS analysis time by >70% by engineering dozens of Nextflow pipelines using AWS, GitHub, Docker, bash, Python, R
• Empowered 15+ lab scientists with multi-omic data analysis capabilities by building user interfaces using Streamlit and Shiny
• Mentored junior scientists to foster professional growth through technical training, project guidance, and research collaborations
• Drove seamless collaboration across DevOps, wet-lab scientists, and bioinformaticians through goal alignment, reproducible analyses, and effective communication

Zymo Research Corp.

Bioinformatics Scientist · March 2017–February 2023 · Irvine, CA

• Developed scalable WGBS and RRBS analysis pipelines on AWS using Nextflow, GitHub Actions, R Markdown, and MultiQC, reducing turnaround times and ensuring reproducibility
• Co-developed commercial NGS assays (PicoMethyl, ATAC-seq, and cfDNA) by leading tailored bioinformatics analyses
• Delivered high-quality bioinformatics analyses and guidance to internal and external teams, earning a Team Excellence Award
• Improved liquid biopsy diagnostic performance through DNA methylation-based deconvolution of cell-type composition
• Developed a DNA methylation-based algorithm to detect fetal DNA in cfDNA for noninvasive prenatal testing (NIPT)
• Trained junior team members through technical instruction, scientific guidance, and hands-on practice
• Documented data analysis methods and result interpretation to accelerate delivery.

University of Rochester

Postdoctoral Research Associate · May 2014–March 2017 · Rochester, NY

• Discovered that X-linked genes in fruit flies have lower mRNA translation rates despite stronger codon usage bias, challenging previous assumptions; findings published in Molecular Biology and Evolution (MBE)
• Identified translational compensation for aneuploidy-induced gene copy number alterations in Drosophila melanogaster, advancing understanding of aneuploidy’s effects; findings published in Nucleic Acids Research (NAR)
• Investigated the evolution of promoter motifs associated with testis expression using population and evolutionary genomics tools
• Accelerated gene expression analysis by developing an RNA-seq pipeline and deploying it on a Slurm HPC cluster
• Developed Codon Usage Analyzer to compute all codon usage bias metrics and accelerate codon bias analysis

Pennsylvania State University

Postdoctoral Scholar · November 2009–April 2014 · State College, PA

• Informed viral outbreak prevention by tracing the origins of pathogenic H7N9 and H6N1 influenza viruses through phylogenetic analysis of genomic sequences
• Pinpointed the molecular changes underlying the novel sex-determination function of the Sex-lethal gene by analyzing sequences from 18 organisms
• Compared the effects of two RNA-silencing pathways (nonsense-mediated mRNA decay and microRNA-mediated silencing) on plant gene expression, resulting in one cover article
• Quantified the impact of fluctuating natural selection on human genetic variation using population genomics models
• Determined the contribution of alternative splicing to functional complexity in mammals by analyzing next-generation RNA-seq data
• Wrote and published eight peer-reviewed papers and presented my research at multiple conferences

Education

• Ph.D. in Genetics (Bioinformatics) — Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences · Shanghai, China · 2004–2009.
• B.S. in Biotechnology — Nanjing University · Nanjing, China · 2000–2004.

Technical Skills

• Cloud & Pipeline Infrastructure: Nextflow, AWS (Batch, EC2, S3, SageMaker, Athena), Docker, Singularity, GitHub Actions (CI/CD), Slurm/HPC, Databricks, DNAnexus, Git.
• Programming & Data Engineering: R, Python, SQL, Linux, C, Perl, Groovy, Pandas, NumPy, Apache Arrow, DuckDB, Sparklyr, Parquet.
• Biostatistics & Machine Learning: Classical statistical testing, ElasticNet regression, random forests, SVM, neural networks, Scikit-learn, TensorFlow.
• Bioinformatics: DESeq2, edgeR, Seurat, Cell Ranger, GATK, SnpEff, bismark, bcftools, STAR, Bedtools, Leafcutter, DEXSeq, PAML, MEGA.
• Genomic Databases: TCGA, GTEx, DepMap, CCLE, GEO, COSMIC, ClinVar, MSigDB, gnomAD, ENSEMBL, UCSC, dbSNP.
• Data Visualization: RMarkdown, ggplot2, Shiny, Streamlit, plotnine, Jupyter, Plotly, Pkgdown, Confluence.
• Generative & Agentic AI: Agentic AI frameworks, Model Context Protocol (MCP), RAG, Claude Code, GitHub Copilot, AWS Bedrock, ChatGPT, Gemini, Perplexity.
• Domain Expertise & Assays: Epigenomics, cancer diagnostics, liquid biopsy, RNA regulation, WGS, WGBS, RNA-seq, ChIP-seq, hybrid capture, CLIA/CAP/IVD.

Awards and Scholarships

Technical Projects

• Technical knowledge base — Technical knowledge recorded in my blog.
• Nextflow dashboard — Shiny app tracking Nextflow pipeline execution.
• PDF database builder — Automated parsing of PDF papers into searchable databases.
• Programming learning notes — Curated code references, snippets, and tips.
• Agent skills — Verified AI workflows to accelerate daily work.
• MCP servers — Model Context Protocol servers for DevOps.

Certificates and Trainings

Talks and Posters

Publications

1. Ruiz, C., Kim, H., Yancey, R., Bhasin, J., Jin, M., Xu, Y., Yang, X., & Jia, L. (2022). Applications of innovative whole-genome bisulfite sequencing (WGBS) for cancer biomarker discovery in plasma liquid biopsy. Cancer Research, 82.

2. Zhang, L., Yang, J.-R., Zhang, Z., & Lin, Z. (2020). Genomic variations of COVID-19 suggest multiple outbreak sources of transmission. MedRxiv, 2020–2002.

3. Zhang, Z., & Sablok, G. (2018). Estimate codon usage bias using codon usage analyzer (CUA). Brachypodium Genomics: Methods and Protocols, 139–148.

4. Wang, M., Zhang, P., Zhu, Y., Kong, X., Zhang, Z., & Hu, L. (2017). Assessing the activity of nonsense-mediated mRNA decay in lung cancer. BMC Medical Genomics, 10, 1–7.

5. Zhang, Z., & Presgraves, D. C. (2017). Translational compensation of gene copy number alterations by aneuploidy in drosophila melanogaster. Nucleic Acids Research, 45(6), 2986–2993.

6. Zou, Q., Chen, L., Huang, T., Zhang, Z., & Xu, Y. (2017). Machine learning and graph analytics in computational biomedicine. In Artificial Intelligence in Medicine (Vol. 83, p. 1).

7. Zhang, Z., & Presgraves, D. C. (2016). Drosophila x-linked genes have lower translation rates than autosomal genes. Molecular Biology and Evolution, 33(2), 413–428.

8. Huang, T., Chen, L., Song, J., Zheng, M., Yang, J., Zhang, Z., et al. (2016). Integrated analysis of multiscale large-scale biological data for investigating human disease 2016. In BioMed Research International (No. 1; Vol. 2016, p. 6585069). Hindawi Publishing Corporation.

9. Zhang, Z. (2015). Cua: A flexible and comprehensive codon usage analyzer. bioRxiv, 22814.

10. Wang, M., Zhang, P., Shu, Y., Yuan, F., Zhang, Y., Zhou, Y., Jiang, M., Zhu, Y., Hu, L., Kong, X., et al. (2014). Alternative splicing at GYNNGY 5′ splice sites: More noise, less regulation. Nucleic Acids Research, 42(22), 13969–13980.

11. Zhang, Z., Klein, J., & Nei, M. (2014). Evolution of the sex-lethal gene in insects and origin of the sex-determination system in drosophila. Journal of Molecular Evolution, 78, 50–65.

12. Li, X., Chen, X., Hu, G., Liu, Y., Zhang, Z., Wang, P., Zhou, Y., Yi, X., Zhang, J., Zhu, Y., et al. (2014). Combined analysis with copy number variation identifies risk loci in lung cancer. BioMed Research International, 2014(1), 469103.

13. Zhang, L., Zhang, Z., Weng, Z., & Shi, W. (2013). Substitution rates of the internal genes in the novel avian H7N9 influenza virus. Clinical Infectious Diseases, 57(8), 1213–1215.

14. Zhang, L., & Zhang, Z. (2013). The origin of human-infecting avian influenza a H6N1 virus. bioRxiv, 398.

15. Zhang, Z., Hu, L., & Kong, X. (2013). MicroRNA or NMD: Why have two RNA silencing systems? Journal of Genetics and Genomics, 40(10), 497–513.

16. Zhang, L., Zhang, Z., & Weng, Z. (2013). Rapid reassortment of internal genes in avian influenza a (H7N9) virus. Clinical Infectious Diseases, 57(7), 1059–1061.

17. Miura, S., Zhang, Z., & Nei, M. (2013). Random fluctuation of selection coefficients and the extent of nucleotide variation in human populations. Proceedings of the National Academy of Sciences, 110(26), 10676–10681.

18. Liu, Y., Xu, H., Chen, S., Chen, X., Zhang, Z., Zhu, Z., Qin, X., Hu, L., Zhu, J., Zhao, G.-P., et al. (2011). Genome-wide interaction-based association analysis identified multiple new susceptibility loci for common diseases. PLoS Genetics, 7(3), e1001338.

19. Zhou, L., Zhang, Z., Zheng, Y., Zhu, Y., Wei, Z., Xu, H., Tang, Q., Kong, X., & Hu, L. (2011). SKAP2, a novel target of HSF4b, associates with NCK2/f-actin at membrane ruffles and regulates actin reorganization in lens cell. Journal of Cellular and Molecular Medicine, 15(4), 783–795.

20. Zhang, Z., Zhou, L., Hu, L., Zhu, Y., Xu, H., Liu, Y., Chen, X., Yi, X., Kong, X., & Hurst, L. D. (2010). Nonsense-mediated decay targets have multiple sequence-related features that can inhibit translation. Molecular Systems Biology, 6(1), 442.

21. Xu, H., Wang, P., Fu, Y., Zheng, Y., Tang, Q., Si, L., You, J., Zhang, Z., Zhu, Y., Zhou, L., et al. (2010). Length of the ORF, position of the first AUG and the kozak motif are important factors in potential dual-coding transcripts. Cell Research, 20(4), 445–457.

22. Chen, X., Li, X., Wang, P., Liu, Y., Zhang, Z., Zhao, G., Xu, H., Zhu, J., Qin, X., Chen, S., et al. (2010). Novel association strategy with copy number variation for identifying new risk loci of human diseases. PloS One, 5(8), e12185.

23. Zhang, Z., Xin, D., Wang, P., Zhou, L., Hu, L., Kong, X., & Hurst, L. D. (2009). Noisy splicing, more than expression regulation, explains why some exons are subject to nonsense-mediated mRNA decay. BMC Biology, 7, 1–13.

24. Zhang, Z., Zhou, L., Wang, P., Liu, Y., Chen, X., Hu, L., & Kong, X. (2009). Divergence of exonic splicing elements after gene duplication and the impact on gene structures. Genome Biology, 10, 1–14.

25. Yin, S., Deng, W., Zheng, H., Zhang, Z., Hu, L., & Kong, X. (2009). Evidence that the nonsense-mediated mRNA decay pathway participates in x chromosome dosage compensation in mammals. Biochemical and Biophysical Research Communications, 383(3), 378–382.

26. Wang, P., Yin, S., Zhang, Z., Xin, D., Hu, L., Kong, X., & Hurst, L. D. (2008). Evidence for common short natural trans sense-antisense pairing between transcripts from protein coding genes. Genome Biology, 9, 1–11.