The NIAID/Division of Microbiology and Infectious Diseases (DMID) Systems Biology Consortium for Infectious Diseases is a group of interdisciplinary scientists that bridge disparate scientific disciplines including microbiology, immunology, infectious diseases, microbiome, mathematics, physics, bioinformatics, computational biology, machine learning, statistical methods, and mathematical modeling. These teams integrate large-scale experimental biological and clinical data across temporal and spatial scales. Scientists iteratively test and validate hypotheses to gain insight into the overall complexity of the biological, biochemical, and biophysical molecular processes within microbial organisms as well as their interaction with the host. The research findings drive innovation and discovery, with the goal of developing novel therapeutic and diagnostic strategies, and predictive signatures of disease to alleviate infectious disease burden and provide solutions to complex public health challenges and disease outbreaks.
Programs
Previously Funded Systems Biology Centers
For more information, please see the Systems Biology Program History page.
Currently Funded: Systems Biology for Infectious Diseases
In response to RFA-AI-21-065 Centers conduct research to develop and validate predictive models of infectious disease initiation, progression, and outcomes. These models are derived from the study of the architecture and dynamics of systems-wide host/pathogen molecular interaction networks during infection. The research findings will provide a deeper understanding of the overall complexity of the biological, biochemical, and biophysical molecular processes within microbial organisms, as well as their interaction with the host, and help researchers identify targets for the development of diagnostics, vaccines, and therapeutics.
Publications
PubMed search for articles from the current Systems Biology for Infectious Diseases Program.
- Scripps Research Institute; Consortium for Viral Systems Biology (CViSB)
- Contact PI: Kristian Andersen
- Project PIs: Kristian Andersen & Robert Garry
- Data Core PI: Laura Hughes
- Technology Core PI: Bryan Briney
- Modeling Core PI: Douglas Lauffenburger
- Icahn School of Medicine at Mount Sinai; SARS-CoV adaptations through a Systems Biology Lens (SYBIL)
- Contact PI: Adolfo Garcia-Sastre
- Project PIs: Adolfo Garcia-Sastre, Sumit Chanda, Michael Schotsaert, & Rafael Medina
- Data Core PI: Lars Pache
- Technology Core PI: Nevan Krogan
- Modeling Core PI: Rafick Sekaly
- Northwestern University at Chicago; Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center
- Contact PI: Richard Wunderink
- Project PIs: Richard Wunderink & Alan Hauser
- Data Core PI: Justin Starren
- Technology Core PI: Benjamin Singer
- Modeling Core PI: Alexander Misharin & Luis Nuñes Amaral
- University of California, San Francisco; HPMI: Host Pathogen Mapping Initiative
- Contact PI: Nevan Krogan
- Project PIs: Jeffrey Cox & Melanie Ott
- Data Core PI: Andrej Sali
- Technology Core PI: Danielle Swaney
- Modeling Core PI: Trey Ideker
- University of California, Los Angeles; Systems Epigenomics of Persistent Bloodstream Infection
- Contact PI: Michael Yeaman
- Project PIs: Elaine Reed, Scott Filler & Michael Yeaman
- Data Core PI: David Gjertson
- Technology Core PI: Monica Cappelletti
- Modeling Core PI: Aaron Meyer
Working Groups
The NIAID/DMID Systems Biology Consortium for Infectious Diseases established working groups composed of members from each of the centers to foster collaboration in areas of shared expertise and project milestones. The working groups focus on critical areas of the program: modeling, data dissemination, and clinical.
Resources and Data Sharing
Rapid and unrestricted sharing of data and research resources is essential for advancing research on human health and infectious diseases. The utility of data and resources to the scientific community is largely dependent on how quickly these data are deposited into public databases, whether the data are easy to find, accessible, and can be re-used by others. NIAID is committed to rapid release of experimental data including genomic and other large-scale data types and in addition recognizes that clinical data and other metadata associated with the genomic, -omics, and other data are valuable research resources.
Meetings
The NIAID/DMID Systems Biology Consortium for Infectious Diseases hosts a webinar series to share the expertise, technological advances, and scientific breakthroughs at each of the centers, and serves as a platform to foster collaboration and knowledge sharing. This lecture series includes members of the NIAID/DMID Systems Biology Consortium and other invited scientists. Lectures are given by participating or invited scientists, ranging from senior investigators to graduate student researchers.
Training Opportunities
The NIAID/DMID Systems Biology Consortium for Infectious Diseases is committed to training the next generation of researchers and informing the community about the approaches and resources (datasets, analysis tools, predictive models) generated by the programs.
Consortium training and outreach activities include workshops, annual meeting postdoctoral networking sessions, and a webinar series.