Current Research and Scholarly Interests
The Mallick lab translates multi-omic discovery into precision diagnostics. We use integrated computational and experimental approaches to understand how cells behave — and misbehave — and how diseases like cancer and Alzheimer's develop and progress. By formalizing this understanding in predictive mathematical models, we aim to identify biomarkers that detect disease earlier and describe how it will behave: aggressive vs. indolent, drug sensitive vs. resistant.
We work in three focus areas. In Systems Biology, we study the processes driving tumor evolution and the tumor microenvironment, including how microenvironmental heterogeneity creates drug-resistant niches, and the multi-omic regulatory mechanisms underlying acquired resistance. In Multi-scale Biomarker Biology, we build models connecting tumor biology to circulating biomarkers, guiding more rational, principled biomarker discovery for early detection and prediction of therapeutic response. In Foundational Methods and AI, we build physics-based, interpretable AI — including the Prospector Head architecture — that incorporates prior knowledge into model design so models can train on realistic amounts of biomedical data while remaining human-interpretable. We also develop and maintain open-source tools, including ProteoWizard, DISK, and SpellBook, supporting reproducible multi-omic analysis across the field.
Many of our studies investigate fundamental physiological processes and are broadly applicable across cell types and diseases, spanning oncology, neurodegeneration, and autoimmune and infectious disease.
For more information see http://mallicklab.stanford.edu
