The NIH, NIAMS. NIAID, pharmaceutical companies and nonprofit organizations have together created the Accelerating Medicines Partnership (AMP) to develop new ways of identifying and validating promising biological targets for diagnostics and drug development.
The purpose of the Bill and Melinda Gates Foundation and University of Cape Town tuberculosis collaboration is to identify prospective immune correlates of risk of tuberculosis (TB) disease.
Through HIPC Program, well-characterized human cohorts are studied using a variety of modern analytic tools, eg., multiplex transcriptional, cytokine, and proteomic assays.
March Of Dimes Database for Preterm Birth Research.
Enabling integrative modeling of human immunological data from the Human Immunology Project Consortium.
The 10,000 Immunomes Project is a reference dataset for human immunology, derived from over 10,000 control subjects in the NIAID ImmPort Database .
Post-donation outcome trajectory network for Living Kidney Donors.
An interactive visualization and query tool for the Cell Ontology.
Coronavirus Disease 19 resources.
immuneXpresso (iX) allows to learn about reported literature interactions between various cell types and regulatory molecules (cytokines and chemokines).
Immunologically relevant list of genes curated with functions and Gene Ontology terms.
Application Program Interface to query the shared data and a tool to download result files.
The Cytokine registry is a master list of cytokines, chemokines and receptors generated for the purpose of collecting, integrating and mapping between entity names and synonyms.
Immcantation framework provides a start-to-finish analytical ecosystem for high-throughput B cell and T cell receptor repertoire sequencing (AIRR-Seq) datasets.
A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires
ImmuneRegulation identifies regulators of the immune system gene of interest.
MMIN will be applied to the investigation of hemebiosynthesis in immune responses.
LinkedImm integrates ImmPort vaccine resources to other public resources to support hypothesis driven queries
An end-to-end, interpretable deep learning model for analyzing Cytometry data.