Computational Scientist
Computational Scientist


Jeremy Zucker is the Principal Investigator (PI) for the Mathematics for Artificial Reasoning in Science (MARS) causal inference for viral pathogenesis project. He has over 15 years of experience developing causal models to obtain actionable insights from systems biology data to advance knowledge in the study of metabolic engineering, circadian rhythms, evolution, human health, and infectious disease.

Research Interest

  • Causal modeling, genome annotation, constraint-based metabolic reconstruction and analysis, pathway engineering
  • Single-cell and bulk transcriptomics, ChIP-Seq, metabolomics, proteomics, 13C-metabolic flux analysis, 
  • Causal inference, bayesian inference, convex optimization, deep learning, reinforcement learning
  • Agile development, literate programming, reproducible research

Disciplines and Skills

  • Comparative genomics
  • Computational biochemistry
  • Computational systems biology
  • Bioinformatics and computational biology
  • Genomics
  • High throughput sequencing
  • Nucleic acid hybridization


  • B.S., Computer Science, University of Colorado (1997)
  • B.S., Applied Mathematics, University of Colorado (1997)

Affiliations and Professional Service

  • MetaCyc Advisory Board Member, (2010-Present)
  • EcoCyc Steering Committee (2018-Present)
  • Engineering Biology Research Consortium (2019-Present)
  • Software Carpentry Lead Instructor (2017-Present)
  • CoronaWhy Vaccines & Therapeutics Causal Knowledge Graph Task Lead (2020-Present)

Awards and Recognitions

  • First place for “Most creative method” in the Whole-Cell Parameter Estimation DREAM Challenge (2013)
  • First place for “Minimum combined prediction and parameter distance” in the Whole-Cell Parameter Estimation DREAM Challenge (2013)
  • New PI Award – PNNL “BESTie” (2019)



Zucker, Jeremy, Sara Mohammad-Taheri, Kaushal Paneri, Somya Bhargava, Pallavi Kolambkar, Craig Bakker, Jeremy Teuton, et al. 2021. “Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis - IEEE Journals & Magazine.” IEEE Transactions on Big Data, January.

Kim, Joonhoon, Samuel T. Coradetti, Young-Mo Kim, Yuqian Gao, Junko Yaegashi, Jeremy D. Zucker, Nathalie Munoz, et al. 2021. “Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium Toruloides.” Frontiers in Bioengineering and Biotechnology 8 (January).


Gao, Yuqian, Thomas L Fillmore, Nathalie Munoz, Gayle J Bentley, Christopher W Johnson, Joonhoon Kim, Jamie A Meadows, Jeremy Zucker et al. 2020. “High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas Putida KT2440.” Frontiers in Bioengineering and Biotechnology 8 (December): 603488.

Keating, Sarah M, Dagmar Waltemath, Matthias König, Fengkai Zhang, Andreas Dräger, Claudine Chaouiya, Frank T Bergmann, Jeremy Zucker et al. 2020. “SBML Level 3: An Extensible Format for the Exchange and Reuse of Biological Models.” Molecular Systems Biology 16 (8): e9110.


Roy Chowdhury, Taniya, Joon-Yong Lee, Eric M Bottos, Colin J Brislawn, Richard Allen White, Lisa M Bramer, Joseph Brown, Jeremy Zucker et al. 2019. “Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations.” MSystems 4 (4).


  • Cannon W.R., J.D. Zucker, D.J. Baxter, N. Kumar, S.E. Baker, J. Hurley, and J.C. Dunlap. 2018. "Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation using Maximum Entropy-based Simulations with Application to Central Metabolism of Neurospora crassa." Processes 6, no. 6:Article No. 63. PNNL-SA-134563. doi:10.3390/pr6060063
  • Hurley J.M., M.S. Jankowski, H. De Los Santos, A.M. Crowell, S. Fordyce, J.D. Zucker, and N. Kumar, et al. 2018. "Circadian proteomic analysis uncovers mechanisms of post-transcriptional regulation in metabolic pathways." Cell Systems 7, no. 6:613-626. PNNL-SA-138421. doi:10.1016/j.cels.2018.10.014


  • White R.A., J.M. Brown, S.M. Colby, C.C. Overall, J. Lee, J.D. Zucker, and K.R. Glaesemann, et al. 2017. "ATLAS (Automatic Tool for Local Assembly Structures) - A Comprehensive Infrastructure for Assembly, Annotation, and Genomic Binning of Metagenomic and Metaranscripomic Data." PeerJ Preprints 5. PNNL-SA-124317. doi:10.7287/peerj.preprints.2843v1


  • Henry C.S., H.C. Bernstein, P. Weisenhorn, R.C. Taylor, J. Lee, J.D. Zucker, and H. Song. 2016. "Microbial Community Metabolic Modeling: A Community Data-Driven Network Reconstruction." Journal of Cellular Physiology 231, no. 11:2339-2345. PNNL-SA-118336. doi:10.1002/jcp.25428
  • White R.A., E.M. Bottos, T. Roy Chowdhury, J.D. Zucker, C.J. Brislawn, C.D. Nicora, and S.J. Fansler, et al. 2016. "Moleculo long-read sequencing facilitates assembly and resolves functionally active genomic bins from complex soil metagenomes." mSystems 1, no. 3. PNNL-SA-117268. doi:10.1128/mSystems.00045-16