Overview

• Omics-driven metabolic modeling & machine learning for microbial communities 💩
• Open source, transparent, and reproducible research + software 🦾
• Programming languages: Bash, R, Python, MATLAB 💻
• High performance computer cluster aficionado 🛩️
• Native speaker: English, Spanish 💬
• Citizenship: Argentina 🇦🇷 / Italy 🇮🇹

Work Experience

• Postdoctoral researcher - ETH Zürich, Zürich 🇨🇭 2024 - Present
• Computational biologist - European Molecular Biology Laboratory, Heidelberg 🇩🇪 2019 - 2020

Education

• Ph.D. Biology - University of Cambridge 🇬🇧 2020 - 2024
• M.Sc. Biotechnology - Chalmers University of Technology 🇸🇪 2017 - 2019
• B.Sc. Biological Systems Engineering - University of California, Davis 🇺🇸 2013 - 2017

Software

• 💎 metaGEM is a workflow that enables the reconstruction & simulation of genome scale metabolic models directly from metagenomic data

• 📊 com-dFBA is a MATLAB implementation of community dynamic flux balance analysis (dFBA), developed for iGEM 2018

Publications

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Francisco Zorrilla, Filip Buric, Kiran R Patil, Aleksej Zelezniak
Nucleic acids research, 2021; https://doi.org/10.1093/nar/gkab815

Plastic-degrading potential across the global microbiome correlates with recent pollution trends
Jan Zrimec, Mariia Kokina, Sara Jonasson, Francisco Zorrilla, Aleksej Zelezniak
MBio, 2021; https://doi.org/10.1128/mBio.02155-21

Microbial communities form rich extracellular metabolomes that foster metabolic interactions and promote drug tolerance
Jason SL Yu, Clara Correia-Melo, Francisco Zorrilla, Lucia Herrera-Dominguez, Mary Y Wu, Johannes Hartl, Kate Campbell, Sonja Blasche, Marco Kreidl, Anna-Sophia Egger, Christoph B Messner, Vadim Demichev, Anja Freiwald, Michael Mülleder, Michael Howell, Judith Berman, Kiran R Patil, Mohammad Tauqeer Alam, Markus Ralser
Nature microbiology, 2022; https://doi.org/10.1038/s41564-022-01072-5

Reconstruction of genome--scale metabolic model for Hansenula polymorpha using RAVEN toolbox
Francisco Zorrilla, Eduard J Kerkhoven
Yeast Metabolic Engineering, 2022 ; https://doi.org/10.1101/2021.06.18.448943 

Please use the Google Scholar link below for a complete list of publications.

Contact

Last updated 24/05/2025