Resources for Researchers
This service can be used to develop and perform a variety of analytical assays to assess the properties of drug substances and their formulations.
This service program supports the development and manufacture, of a wide variety of pharmaceutical dosage formulations, including tablets, capsules, semi-solid preparations, injectibles, and sustained-release products. If requested, manufacturing can be done under GMP.
The Immcantation framework is developed as a start-to-finish analytical ecosystem for large-scale characterization of B cell receptor (BCR) and T cell receptor (TCR) repertoires from high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) datasets.
ImmPort is a Web portal that contains data from NIAID-funded immunology studies, including basic research and clinical trials. The portal provides online tools that allow users to analyze the data and visualize the results.
The Microbicide Trials Network (MTN) is a NIAID-funded worldwide collaborative clinical trials network focused on preventing the sexual transmission of HIV. The MTN accepts concepts for new protocols, ancillary study proposals, secondary data analysis requests, and dataset requests.
Researchers involved with the NIAID Clinical Genomics Program study many diseases of the immune system that are rare and not well understood but often shed light on basic immune function and more common immune disorders.
This Gene Set Enrichment-type test designed for analysis of microarray and RNASeq data is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. QuSAGE extends previous methods with a complete probability density function (PDF).
Current methods for monitoring HIV-infected patients on antiretroviral therapy are expensive and technologically complex, making it difficult for use in resource-limited countries around the world.
The tools in the Systems Immunology Toolkit will collectively allow you to upload microarray data, view that data on a gene-by-gene basis, overlay clinical data, analyze your data using a modular framework, compare your data to other datasets and diseases, and get a quick functional interpretatio