Marisa Torres

Portrait of  Marisa Torres

  • Title
    Bioinformatics Lead
  • Email
  • Phone
    (925) 423-2723
  • Organization
    Not Available

Marisa Torres is a Bioinformatics Lead at Lawrence Livermore National Lab. Marisa builds analysis tools to solve disease, working on machine learning for drug discovery and detecting pathogens. She’s working on computational models for fighting cancer for the ATOM consortium and for COVID-19 countermeasures. Her computational tools help biologists make decisions on public health. Marisa’s predictive biology research improves result interpretability for biosecurity. She’s interested in building more useful molecular data modeling systems for understanding disease-related mechanisms and treatment. She enjoys mentoring and reading groups, is a Girls Who Code volunteer, is on the WiDS Ambassador Advisory Council, and sings in a community choir.

MS Biomedical Informatics, Stanford

BA Molecular and Cell Biology, minor Computer Science, UC Berkeley

Stevenson et al. (2023) 'Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method', Journal of Chemical Information and Modeling, doi: 10.1021/acs.jcim.3c00722.

Sandholtz S. H., J. A. Drocco, A. T. Zemla, M. W. Torres, M. S. Silva, J. E. Allen (2023), ‘A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2’, ACS Omega, 8 (24), 21871-21884, doi: 10.1021/acsomega.3c0162 .

Posada R., M. Silva, M. Torres, J. Allen, J. Drocco, S. Sandholtz, A. Zemla (2022), ‘Graph-based featurization methods for classifying small molecule compounds’, UC Merced Undergraduate Research Journal, 14(1),

Stevenson et al. (2021) ‘High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models’, SC '21: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, doi: 10.1145/3458817.3476193.

Lau et al. (2021) ‘Discovery of Small-molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline’, Frontiers in Molecular Biosciences, doi: 10.3389/fmolb.2021.678701.

Slezak T., S. Gardner, J. Allen, E. Vitalis, M. Torres, C. Torres, C. Jaing (2011), ‘Design of Genomic Signatures for Pathogen Identification and Characterization’, Microbial Forensics, Second Edition, 493-508.

Torres, C. L., E. A. Vitalis, B. R. Baker, S. N. Gardner, M. W. Torres, J. M. Dzenitis (2011), ‘LAVA: An Open-Source Approach To Designing LAMP (Loop-Mediated Isothermal Amplification) DNA Signatures’, BMC Bioinformatics, 12:240.

2021 DOE Secretary of Energy Achievement Award – COVID-19 National Virtual Biotechnology Laboratory

2020 LLNL Physical Life Science Institutional Impact Award - Contributed to COVID-19 therapeutic research by developing a computational screening platform and an environmental pipeline

2019 LLNL Director’s Institutional Operational Excellence (DIOE) Award

2017 LLNL Diversity and Inclusion Director’s Award

2014 LLNL Global Security Directorate Gold Award - Developed the first transportable automated system for microbial forensic analysis based on DNA sequencing