In September 2023, we opened our doors at UC San Diego as a mixed computational and experimental group. Our mission is to bring cutting-edge AI for tuberculosis research — from predicting essential protein interactions to designing protein-based inhibitors. At the same time, we pursue foundational problems in biochemistry, with a focus on protein language models and the enzyme-to-substrate mapping challenge.
Our lab uses powerful computers to apply machine learning tools to the protein-small molecule (e.g. enzyme-substrate) mapping problem. We have our own GPU workstations and access to supercomputers at the San Diego Supercomputer Center (SDSC).
Our wet lab focuses on enzyme biochemistry, where among other things, we:
We collaborate with world-class LC-MS experts at UCSD to precisely measure enzyme activities and metabolites.
We strive for excellence in all we do. Our main goal is to nurture scientists and humans; high-quality research and publications naturally follow from this focus. We encourage the use of resources like Materials for Nurturing Scientists from Uri Alon's group to support this mission. We value community engagement through outreach activities and embrace diversity in all its forms. To enhance our scientific productivity and empower our trainees, we actively integrate AI tools, including large language models, into our work.
Click in the Picture to know more about each paper
A full list of publications can be found here.
The Clubes de Ciencia program was created in Guanajuato, Mexico in 2014, and has rapidly expanded to 9 cities and 8 Ibero-American countries. The mission of CdeCMx is to expand access to the highest quality scientific education for young people from all socio-economic backgrounds in high school and higher education levels and to inspire the next generation of Mexican scientists, technologists, and innovators through international education networks. Our volunteer instructors are scientists who are experts in their respective research fields.
Learn MoreWe teach Chem 169/269: Applied Machine Learning and AI for Biochemistry, a hands-on course focused on applying modern AI to real biological data. Students work in teams to analyze protein language model embeddings, predict enzyme function, and explore tools like AlphaFold, UMAP, and contrastive learning — all in the context of cutting-edge biochemical problems.
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