Science
An immunogenetic basis for lung cancer risk
Krishna C*, Tervi A*, Saffern M*, Wilson EA*, et al. An immunogenetic basis for lung cancer risk. Science. 2024.
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Decoding the language of immune recognition
OUR ENGINE
We are an interdisciplinary lab harnessing the tools of computational biology, machine learning, and experimentation to decipher the molecular determinants of immune recognition, dissect the major contributing factors in cancer development, and predict responses to cancer immunotherapy.
Research
IMMUNE RECOGNITION
Deciphering the molecular determinants of antigen recognition by T cells by employing deep learning algorithms and high-dimensional proteomic data.
CANCER ECOSYSTEMS
By combining traditional cancer biology, immunology, genomics, transcriptomics, and computational modeling, we dissect the reciprocal interactions between the evolving tumor genomes and their host immune ecosystems.
IN SILICO PREDICTION OF IMMUNOTHERAPY RESPONSE
With the world’s largest library of molecular, genetic, and clinical data, we can predict how patients with cancer will respond to immune checkpoint inhibitors using machine learning algorithms.
CANCER RISK
We are investigating the major contributing factors in cancer development.
About Us
Our Mission
We employ and develop quantitative approaches to solve both basic science and clinically relevant problems in cancer.
Our Impact
Our work will substantially improve the outcomes of patients with cancer and provide novel targets for therapeutic intervention.
Our Team
We are a dedicated group of scientists, postdocs, and students with diverse backgrounds ranging from cancer genomics to computational biology and machine learning. Each member brings expertise in their field to our unique and highly collaborative research environment.
Featured Publications
Cell Systems
The electrostatic landscape of MHC-peptide binding revealed using inception networks
Wilson EA, Cava JK, Chowell D, et al. The electrostatic landscape of MHC-peptide binding revealed using inception networks. Cell Systems. 2024.
Read MoreWant to work with us?
We are actively looking for talented and highly motivated students, interns, postdocs, and staff scientists to join our laboratory. Apply your skills to help us solve some of the most complex and clinically relevant scientific problems in cancer research.
If you are interested in a position in the lab, please contact Diego Chowell and include a cover letter and curriculum vitae (CV). Letters of recommendations are required at a later stage.