Systems Biology and Informatics

One of the distinguishing capabilities of our team is the organization and presentation of biological data. Our experience includes bringing together the most current, gold-standard knowledge about organisms, their genes and genomes, and the way they interact together in response to different stimuli into databases that are easily queried. Having the data structured in this way enables analyses that span from small-scale studies of select organisms, to broad, systems-wide approaches that can combine thousands of datasets. We have developed computational methods that allow us to identify patterns and correlations across broad categories that include exploring biochemical networks, identifying the metabolites or genes associated with specific diseases, and developing insight into the evolution of different organisms. We have used machine learning in combination with this data to identify biological threats and predict specific disease phenotypes.

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Projects

Bacterial and Viral Bioinformatics Resource Center (BV-BRC)

Project Contact: Rebecca Wattam / Ron Kenyon
Funding Agency: National Institute of Allergy and Infectious Diseases (NIAID)  National Institute of Allergy and Infectious Diseases

The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) has an end-to-end analysis platform that allows researchers to take the direct data from the sequencer, assemble a genome, annotate it, and then use a suite of user-friendly tools to compare it to any public data that is available in the repository. With more than 228,000 bacterial, 3,000 archaeal, and 4,700 bacteriophage genomes, BV-BRC creates a unique research experience with “virtual integration” of private and public data, with many diverse tools and functionalities to explore both genome-scale and gene expression data.

 

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Friend or Foe: iSENTRY

Project Contact: Rebecca Wattam / Allan Dickerman
Funding Agency: Defense Advanced Research Projects Agency (DARPA) DARPA

The DARPA funded Friend or Foe project combines environmental microbiology, high-throughput droplet microfluidics, DNA barcoding, single-cell sequencing, machine learning, and computational biology to detect rapidly good versus bad bacteria in our environment. The target of iSENTRY is to bring about a revolutionary advance in the science, devices, and systems needed for the isolation and characterization of known and potentially unknown or unculturable bacterial pathogens. As a collaborator among several partners, our team provides the computational biology expertise.

 

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GPAAII

Project Contact: Chunhong Mao
Funding agency: National Institutes of Health (NIH)  National Institutes of Health

Genomic and Proteomic Architecture of Atherosclerosis (GPAA) is a collaborative project which aims to comprehensively study the genomic and proteomic architecture of atherosclerosis and identify genes/proteins that are associated with the development of atherosclerosis. This work will provide novel insights into the pathogenesis of atherosclerosis and facilitate development of reliable methods for diagnostics and targeted therapeutic interventions.

 

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Metabolomic Signatures

Project Contact: Chunhong Mao
Funding agency: National Institutes of Health (NIH)   National Institutes of Health

The Metabolomic Signatures of Coronary Artery Disease (CAD)-Associated Genotypes project is an international collaborative venture. The overall goal of the project is to use un-targeted metabolomics to identify metabolites that are associated with CAD genotypes. This work will provide novel insights into the mechanisms and pathways involved in the pathogenesis of CAD, and help identify novel therapeutic targets to CAD.

 

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Y Chromosomes in Mosquitoes

Project Contact: Chunhong Mao
Funding agency: National Institutes of Health (NIH)   National Institutes of Health

This collaborative project aims to identify Y chromosome genes across divergent Anopheles mosquito species, and to study the function and evolution of selected Y genes that are important in male development. This work will provide baseline information on genes that control male mosquito biology, facilitating the creation of novel methods to control mosquito-borne diseases.

 

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