Siyuan Feng

Siyuan Feng

Computational Biologist

Population Genomics · Functional Multi-omics · Cancer Diagnostics

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About

  • Computational Biologist highly skilled in population genomics and functional multi-omics, with 13 peer-reviewed papers published in five years.
  • Experienced in building and executing both computational and wet-lab multi-omic pipelines, able to solve complex biological questions using samples or public datasets.
  • Interdisciplinary problem-solver and collaborator applying statistical modeling to real-world challenges in public health and athletic training, with 11 additional peer-reviewed papers published in three years.
  • Product developer who has promoted innovations in molecular cancer diagnostics.

Education

University of Wisconsin - Madison

2020 - 2026

PhD candidate & MS, Genetics (GPA: 4.0/4.0)

Madison, US

Thesis: Decode the regulatory blueprint of adaptive evolution using multi-omics

Advisor: Prof. John Pool

Sichuan Agricultural University

2013 - 2019

BS & MS, Animal Genetics, Breeding and Reproduction (GPA: 3.9/4.0)

Chengdu, China

Advisor: Prof. Qianzi Tang

Skills

Cancer Genomics & Diagnostics

Variant DB integration, oncogenicity prediction & classification

Multi-omic Analyses

WGS, ATAC-seq, transcriptomics, proteomics, metabolome

Gene-Regulatory Profiling

Chromatin accessibility, TF binding, RNA expression, alternative splicing, RNA editing, small RNA regulation

Population Genomics

SNPs/CNV detection, demographic inference, population structure, introgression, selection, GEA

Statistical Methods

Mendelian randomization, SEM, hypothesis testing, regression, ANOVA, mixed models

LLM & AI

RAG, API integration, prompt engineering, structured output

Programming

Python, R, Bash, Git, GitHub, Docker, Nextflow

Backend Development

Django, SQL, AWS cloud computing

Experience

Computational Oncology Research Intern

Jun - Aug 2025

BillionToOne, Inc., CA

  • Built an LLM-powered tumor-variant annotation and interpretation system to deliver higher-quality diagnostic reports while reducing cost.
  • Built a web app and database to visualize and curate variant annotations and experimental evidence.
  • Collaborated with clinical genomics scientists to de-risk the project.

PhD Research Assistant

2020 - Present

Laboratory of Genetics, University of Wisconsin-Madison

  • Decoded the regulatory blueprint of adaptive evolution using multi-omics and Bayesian statistical modeling.
  • Developed multi-omic computational and wet-lab workflows for WGS, ATAC-seq, RNA-seq, and proteomics.
  • Developed a novel statistical framework to identify adaptive multi-omic traits.
  • Uncovered the genomic basis of the invasion success of an agricultural pest that causes $1 billion loss per year.
  • Collaborated with human geneticists to examine the effects of scaling in population genetic simulations.
  • Discovered causal effects of physical activity intensity on COVID-19 outcomes by performing Mendelian randomization.
  • Invited to present genomic research at seven international conferences and university departments.

Bioinformatician & Master's Research Assistant

2013 - 2019

Sichuan Agricultural University, China

  • Published 11 peer-reviewed papers as the lead bioinformatician on a 30-people research team.
  • Collaborated with wet-lab scientists in over 20 research projects involving transcriptomics of over 20 species from plants to animals.

Publications

24 peer-reviewed research papers · 737 citations · Google Scholar

Featured

Feng S, DeGrey SP, Guédot C, Schoville SD, Pool JE. Genomic Diversity Illuminates the Environmental Adaptation of Drosophila suzukii. Genome Biology and Evolution. 2024 Sep;16(9):evae195. DOI

Abstract: Drosophila suzukii (spotted-wing Drosophila) is an invasive agricultural pest that causes substantial damage to soft-skinned fruit crops. We generated whole-genome sequences from 384 flies spanning native and invasive populations. Our analysis revealed patterns of genetic diversity consistent with both adaptive evolution to new environments and demographic processes during invasion. We identified genomic regions under selection associated with traits relevant to invasion success and environmental adaptation.

  1. Ferrari T, Feng S, Zhang X, Mooney J. Parameter Scaling in Population Genetics Simulations May Introduce Unintended Background Selection: Considerations for Scaled Simulation Design. Genome Biology and Evolution. 2025 May 23;evaf097.
  2. Feng S, DeGrey SP, Guédot C, Schoville SD, Pool JE. Genomic Diversity Illuminates the Environmental Adaptation of Drosophila suzukii. Genome Biology and Evolution. 2024 Sep;16(9):evae195.

Featured

Feng S*, Ma J*, Long K*, Zhang J, Qiu W, et al. Comparative microRNA transcriptomes in domestic goats reveal acclimatization to high altitude. Frontiers in Genetics. 2020 Jul 31;11:809. DOI

Abstract: High-altitude adaptation is a complex physiological process. We performed small RNA sequencing on heart and lung tissues from goats living at different altitudes to identify microRNAs involved in high-altitude acclimatization. Our analysis identified differentially expressed miRNAs associated with hypoxia response, energy metabolism, and cardiovascular function, providing insights into the molecular mechanisms underlying high-altitude adaptation in livestock.

  1. Wang X*, Yan P*, Feng S*, et al. Identification and expression pattern analysis of miRNAs in pectoral muscle during pigeon (Columba livia) development. PeerJ. 2021 Jun 23;9:e11438.
  2. Fu Y, Fan P, Wang L, Shu Z, Zhu S, Feng S, et al. Improvement, identification, and target prediction for miRNAs in the porcine genome by using massive, public high-throughput sequencing data. Journal of Animal Science. 2021 Feb;99(2):skab018.
  3. Feng S*, Ma J*, Long K*, Zhang J, Qiu W, et al. Comparative microRNA transcriptomes in domestic goats reveal acclimatization to high altitude. Frontiers in Genetics. 2020 Jul 31;11:809.
  4. Wang X*, Lin Z*, Feng S*, Liu L, Zhao L, et al. MicroRNA expression profile analysis during myogenic differentiation in pigeon (Columba livia) skeletal muscle satellite cells. International Journal of Agriculture and Biology. 2020;24(5):7.
  5. Long K*, Feng S*, Ma J*, Zhang J, Jin L, et al. Small non-coding RNA transcriptome of four high-altitude vertebrates and their low-altitude relatives. Scientific Data. 2019 Oct 4;6(1):192.
  6. Zhou J, Zhao H, Zhang L, Liu C, Feng S, et al. Integrated analysis of RNA-seq and microRNA-seq depicts miRNA–mRNA networks involved in stripe patterns of Botia superciliaris skin. Functional & integrative genomics. 2019 Sep;19(5):827-38.
  7. Ma Y*, Feng S*, Wang X, Qazi IH, Long K, et al. Exploration of exosomal microRNA expression profiles in pigeon 'Milk' during the lactation period. BMC Genomics. 2018 Dec;19:1-2.
  8. Wang Y*, Ma J*, Qiu W*, Zhang J, Feng S, et al. Guanidinoacetic acid regulates myogenic differentiation and muscle growth through miR-133a-3p and miR-1a-3p Co-mediated Akt/mTOR/S6K signaling pathway. International Journal of Molecular Sciences. 2018 Sep 19;19(9):2837.
  9. Xiao J*, Feng S*, Wang X, Long K, Luo Y, et al. Identification of exosome-like nanoparticle-derived microRNAs from 11 edible fruits and vegetables. PeerJ. 2018 Jul 31;6:e5186.
  10. Ma J*, Fu Y*, Zhang J*, Feng S, et al. Testosterone-Dependent miR-26a-5p and let-7g-5p Act as Signaling Mediators to Regulate Sperm Apoptosis via Targeting PTEN and PMAIP1. International Journal of Molecular Sciences. 2018 Apr 18;19(4):1233.
  11. Li X*, Feng S*, Luo Y, Long K, et al. Expression profiles of microRNAs in oxidized low-density lipoprotein-stimulated RAW 264.7 cells. In Vitro Cellular & Developmental Biology – Animal. 2018 Feb;54(2):99–110.

Featured

Zhang X, Zhang X, Feng S, Li H. The causal effect of physical activity intensity on COVID-19 susceptibility, hospitalization, and severity: Evidence from a mendelian randomization study. Frontiers in Physiology. 2023 Mar 8;14:1089637. DOI

Abstract: We used Mendelian randomization to examine the causal relationship between physical activity intensity and COVID-19 outcomes. Using genetic variants associated with physical activity from UK Biobank and COVID-19 data from the Host Genetics Initiative, we found that moderate-to-vigorous physical activity was causally associated with reduced COVID-19 susceptibility and hospitalization, suggesting that promoting physical activity could be an effective public health strategy.

  1. Jiang C, Zhang X, Feng S, Li H. Engaging in Physical Activity in Green Spaces at Night Is Associated with Mental Well-Being and Happiness. Behavioral Sciences. 2025; 15(3):313.
  2. Luo H, Zhang X, Su S, Zhang M, Yin M, Feng S, Peng R, Li H. Using structural equation modeling to explore the influences of physical activity, mental health, well-being, and loneliness on Douyin usage at bedtime. Frontiers in Public Health. 2024 Jan 5;11:1306206.
  3. Yang T, Bi S, Zhang X, Yin M, Feng S, Li H. The Impact of Different Intensities of Physical Activity on Serum Urate and Gout: A Mendelian Randomization Study. Metabolites. 2024 Jan 19;14(1):66.
  4. Zhang X, Li H, Feng S, Su S. The Effect of Various Training Variables on Developing Muscle Strength in Velocity-based Training: A Systematic Review and Meta-analysis. International Journal of Sports Medicine. 2023 Aug 15.
  5. Zhang X, Zhang X, Feng S, Li H. The causal effect of physical activity intensity on COVID-19 susceptibility, hospitalization, and severity: Evidence from a mendelian randomization study. Frontiers in Physiology. 2023 Mar 8;14:1089637.
  6. Li H, Zhang X, Zhang X, Wang Z, Feng S, Zhang G. Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study. Journal of Intelligence. 2023 Jan 31;11(2):29.
  7. Zhang X, Feng S, Li H. The Effect of Velocity Loss on Strength Development and Related Training Efficiency: A Dose–Response Meta–Analysis. Healthcare. 2023 Jan;11(3):337.
  8. Tian H, Li H, Liu H, Huang L, Wang Z, Feng S, Peng L. Can Blood Flow Restriction Training Benefit Post-Activation Potentiation? A Systematic Review of Controlled Trials. International Journal of Environmental Research and Public Health. 2022 Sep 21;19(19):11954.
  9. Zhang X, Feng S, Peng R, Li H. Using Structural Equation Modeling to Examine Pathways between Physical Activity and Sleep Quality among Chinese TikTok Users. International Journal of Environmental Research and Public Health. 2022 Apr 23;19(9):5142.
  10. Zhang X, Feng S, Peng R, Li H. The Role of Velocity-Based Training (VBT) in Enhancing Athletic Performance in Trained Individuals: A Meta-Analysis of Controlled Trials. International Journal of Environmental Research and Public Health. 2022 Jan;19(15):9252.
  11. Chen H, Zhang G, Wang Z, Feng S, Li H. The Associations between Daytime Physical Activity, While-in-Bed Smartphone Use, Sleep Delay, and Sleep Quality: A 24-h Investigation among Chinese College Students. International Journal of Environmental Research and Public Health. 2022 Jan;19(15):9693.

Awards

$50,000

Louis and Elsa Thomsen Wisconsin Distinguished Graduate Fellowship

UW-Madison College of Algricultural & Life Sciences
For research excellence

$6,000

Marie Christine Kohler Fellowship

Wisconsin Institute of Discovery
For promoting art & science fusion

The receipient of 2025

Schlimgen Award

UW-Madison Genetics
For outstanding scholarship and research performance