Zhenguo Zhang
Passionate Bioinformatics Scientist and Mentor · zhangz.sci@gmail.com · GitHub · LinkedIn
Executive Summary
Bioinformatics Scientist with 20+ years of R&D expertise in multi-omic data analysis, biomarker discovery, and translational research, backed by 20+ peer-reviewed publications across gene regulation, genome evolution, and cancer genomics. Experienced across the full R&D lifecycle—from idea initiation and experimental design to computational execution and commercial product delivery. Over the past decade, engineered dozens of Nextflow pipelines, automated reporting via RMarkdown, and identified dozens of DNA methylation and RNA cancer markers for novel diagnostic products. Recipient of a 2024 Annual Employee Award for cross-functional scientific leadership and dedicated mentorship of junior scientists.
Professional Experience
Exact Sciences (now Abbott)
San Diego, CA
Staff Bioinformatics Scientist · March 2026–September 2026
- Drove departmental research forward through strategic planning, pipeline architecture, technical analysis oversight, and AI adoption.
- Spearheaded cancer biomarker discovery across FFPE, liquid biopsy, and stool samples using DNA fragmentomics and RNA expression/splicing profiles.
- Applied AI workflows to shorten programming cycles by 50%, drive ideation, and enhance predictive modeling.
Senior Bioinformatics Scientist · April 2023–February 2026
- Discovered dozens of DNA methylation cancer biomarkers via integrative analysis of blood and tissue data from hundreds of samples, enabling commercial product development.
- Advanced departmental goals by building dozens of pipelines and RMarkdown reporting templates, reducing analysis time by 70%.
- Built a machine learning model utilizing blood-derived RNA biomarkers, achieving an AUC of 0.7.
- Built custom R Shiny and Streamlit apps, enabling 15 lab scientists to self-serve pipeline execution and result visualization.
- 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
- Co-developed commercial NGS assays (PicoMethyl, ATAC-seq, cfDNA) by leading tailored bioinformatics analyses, earning a Team Excellence Award.
- Boosted liquid biopsy diagnostic performance by estimating cell-type compositions via DNA-methylation-based deconvolution.
- Engineered scalable Nextflow pipelines on AWS for omics data, shortening turnaround times and ensuring reproducibility.
- Upskilled junior team members through technical training, scientific guidance, and hands-on practice.
University of Rochester
Postdoctoral Research Associate · May 2014–March 2017 · Rochester, NY
- Advanced X-linked gene translation understanding by discovering slower translation despite more use of optimal codons (MBE).
- Advanced aneuploidy understanding by discovering novel translational compensation using multi-omic analysis (NAR).
- Expedited gene expression analysis by developing an RNAseq pipeline and deploying to a Slurm HPC cluster.
Pennsylvania State University
Postdoctoral Scholar · November 2009–April 2014 · State College, PA
- Informed virus outbreak prevention by retracing H7N9/H6N1 origin using phylogenetic analysis of genomic sequences.
- Published three peer-reviewed papers on the distinct impacts of nonsense-mediated mRNA decay, alternative splicing, and microRNAs on gene regulation and evolution.
- Quantified the impact of fluctuating natural selection on human genetic variations using population genomics models.
Education
- Ph.D. in Genetics (Bioinformatics) — Shanghai Institutes for Biological Sciences, Chinese Academy of Science · 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
| Year | Award | Organization | Location |
|---|---|---|---|
| 2024 | Annual Employee Teamwork Award | Exact Sciences | San Diego, CA |
| 2018 | Team Excellence Award | Zymo Research Corp. | Irvine, CA |
| 2016 | The Allied Genetics Conference Travel Award | Genetics Society of America | Orlando, FL |
| 2011 | Travel Award of SMBE Annual Meeting | Society of Molecular Biology and Evolution | Kyoto, Japan |
| 2009 | Excellence Award in the Graduate Academic Forum | Shanghai Institutes for Biological Sciences | Shanghai, China |
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
| Year | Training | Provider |
|---|---|---|
| 2026 | Executive Leadership | |
| 2026 | Maximize Your Claude Code Programming Productivity | |
| 2025 | Getting into the Serverless Mindset | AWS |
| 2025 | Hands-On AI: Build a Generative Language Model from Scratch | |
| 2025 | Introduction to Artificial Intelligence | |
| 2025 | Copilot Agents: Leveraging Customized AI Assistants in Copilot and Teams | |
| 2025 | Visual Studio Code Productivity Tips | |
| 2024 | Academy Accreditation - Generative AI Fundamentals | Databricks |
| 2024 | Leadership: Practical Skills | |
| 2024 | What is Generative AI? | |
| 2023 | Learning Jira and Confluence | |
| 2022 | Kaggle Python Tutorial on Machine Learning | DataCamp |
Talks and Posters
| Year | Event | Location |
|---|---|---|
| 2016 | The Allied Genetics Conference (TAGC) Annual Meeting | Orlando, FL |
| 2015 | ASBMB Symposium on Evolution and Core Processes in Gene Regulation at Washington University | St. Louis, MO |
| 2013 | Annual Society for Molecular Biology and Evolution Meeting | Chicago, IL |
| 2011 | Bioinformatics and Genomics Retreat at Pennsylvania State University | State College, PA |
| 2011 | SMBE Symposium on Molecular and Genomic Evolution at Pennsylvania State University | State College, PA |
| 2009 | Graduate Academic Forum at Shanghai Institutes for Biological Sciences | Shanghai, China |
Publications
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.
Zhang, L., Yang, J.-R., Zhang, Z., & Lin, Z. (2020). Genomic variations of COVID-19 suggest multiple outbreak sources of transmission. MedRxiv, 2020–2002.
Zhang, Z., & Sablok, G. (2018). Estimate codon usage bias using codon usage analyzer (CUA). Brachypodium Genomics: Methods and Protocols, 139–148.
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.
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.
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).
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.
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.
Zhang, Z. (2015). Cua: A flexible and comprehensive codon usage analyzer. bioRxiv, 22814.
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.
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.
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.
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.
Zhang, L., & Zhang, Z. (2013). The origin of human-infecting avian influenza a H6N1 virus. bioRxiv, 398.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.