The CMI-PB consortium brings together experts from six different labs with diverse expertise in immunology, bioinformatics, and computational biology.

• The Kleinstein Lab at Yale University is focused on big data analysis and immunology, and collaborates with the community to release data and models for reproducibility and prediction contest participation.
• The Grant Lab at UC San Diego specializes in using computational approaches to study biological macromolecules, and Dr. Grant advises over 40 biology graduate students in the CMI-PB Prediction Contest.
• The Ay Lab at La Jolla Institute for Immunology (LJI) has expertise in developing bioinformatics tools that utilize high-dimensional and high-throughput datasets to gain insights into chromatin conformation, genetic variation, and gene expression regulation. They develop predictive machine learning models for the CMI-PB Contest.
• The CCHI Center is comprised of the Sette Lab (LJI) and Crotty Lab (LJI), both of which study immunology in different ways. The Sette Lab uses epitopes to define immune signatures, while the Crotty Lab investigates immunity against infectious disease and memory of infections and vaccines. They contribute data from separately funded grants.
• The Peters Lab (LJI) conducts experimental and computational studies to understand human immune responses in various contexts. They generate experimental data and coordinate the creation of the prediction contest in a standardized way.
  

Together, the labs in the CMI-PB consortium contribute to advancing the understanding of immunology and computational biology through collaboration and data sharing.