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NIAID to Fund Systems Biology Research Network

NEW YORK (GenomeWeb) – The National Institute of Allergy and Infectious Diseases (NIAID) has committed $11 million in fiscal year 2018 to fund the creation of a network of research centers that will use systems biology approaches to build predictive models for infectious diseases.

Since it established the Systems Biology for Infectious Diseases Research program in 2008, the NIAID has funded a number of projects that have used high-throughput sequencing and other omics technologies to generate large, diverse, and complex datasets that can be combined with behavioral, environmental, clinical, immunological, and other data to generate host/pathogen molecular interaction networks, the agency said.

While there has been progress made in using these networks to build predictive models and identify biosignatures for infectious disease, "these studies are mostly limited to analyzing and integrating genomics, transcriptomics, and experimental immunological data, and lack the depth and breadth to capture human diversity and variation at a resolution to identify predictive biosignatures of infectious disease risk, severity, response to interventions, adverse drug reactions, and other factors of potential clinical utility on an individual, personalized level," the NIAID noted.

To address this, the NIAID this week said it aims to establish up to five Systems Biology Centers focused on building predictive models of infectious diseases from hypothesis-driven projects that perform large-scale data generation, data analysis, and integration with statistical inference modeling. The centers will also be tasked with developing and improving innovative experimental methods, technologies, bioinformatics and computational tools, machine learning software, and statistical inference methods that can be used by the broader scientific community for systems-level data analysis.

Research areas of interest to the NIAID under this funding opportunity include the determination of host/pathogen disease processes or molecular networks that are relevant to multiple strains, species, or genera; the identification of host/pathogen molecular networks and predictive models that may be used to discover biosignatures of risk, severity, and response to therapeutic interventions; and the determination of molecular networks and predictive models that focus on genetic and epigenetic pathways, diversity, and mechanisms in regulating host responses.

Additional details can be found here.