The CMI-X consortium brings together experts from four 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 Einav Lab at La Jolla Institute for Immunology (LJI) has expertise in developing bioinformatics tools that utilize high-dimensional and high-throughput datasets. They develop predictive machine learning models for the CMI-PB Contest.
• The Peters Lab at La Jolla Institute for Immunology (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-X consortium contribute to advancing the understanding of immunology and computational biology through collaboration and data sharing.