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About CBI

Now more than ever before, the power to turn huge volumes of data into information about our world has put the answers to some of life’s most challenging questions within our grasp. The George Washington University’s Computational Biology Institute (CBI) brings together leading faculty in biology, medicine and computing to harness this information, opening new doors of discovery that have the potential to benefit millions. CBI is also maximizing the university’s unique relationships in the nation’s capital to form research partnerships and spotlight cutting-­‐edge topics that enhance human and environmental health. By blending its own skills with the expertise of engineers, mathematicians, statisticians, clinicians and others, the CBI is contributing to knowledge and resources that are used by researchers on a global scale, influencing how the world uses science and technology to solve its most pressing problems. With these truly incomparable resources and expertise, the CBI performs cutting-edge research and helps raise awareness of scientific advancements that improve our health, environment and overall quality of life.

 

 

RANKED #11

U.S. News & World Report's List of Best Public Health Graduate Programs

LOCATION

Washington D.C.'s only Public Health School

RESEARCH

Shaping Public Health Policy and Practice

FACULTY

130 Full-time Faculty Leading our Students, and 300 Part-time Faculty.

 

Featured Publications

 

Estimating rare disease prevalence and costs in the USA: a cohort study approach using the Healthcare Cost Institute claims data

July 26, 2024

Estimating rare disease prevalence and costs in the USA: a cohort study approach using the Healthcare Cost Institute claims data

Relationship of abundant microbial species with the risk of higher severity in infants hospitalized for bronchiolitis.

Integrated relationship of nasopharyngeal airway host response and microbiome associates with bronchiolitis severity

July 26, 2024

Bronchiolitis is a leading cause of infant hospitalizations but its immunopathology remains poorly understood.

Distribution of study participants by age and health outcome. (a) colors in all subplots reflect health status of groups as provided in the legend of subplot a. The sample population is not uniform for age ranges, with a higher proportion of older participants falling into the severe group. (b) age has a strong association with health outcomes (p-value = 0.001). (c) BMI is not associated with health outcomes (p-value = 0.1488). For assessing the association of age and gender with the health outcome status,

Metabolite, protein, and tissue dysfunction associated with COVID‑19 disease severity

July 26, 2024

Proteins are direct products of the genome and metabolites are functional products of interactions between the host and other factors.

HAllAgram for block-wise associations.

High-sensitivity pattern discovery in large, paired multiomic datasets

July 26, 2024

We present a novel framework which integrates hierarchical hypothesis testing with FDR correction to reveal linear and non-linear relationships among data.

 

Explore More Publications

 

Projects 

omeClust

We developed omeClust, a generic tool for omics community detection, and applied it to the dissimilarity matrix of the genetic sequences of previous strains of this coronavirus to the newest ones, identifying the sites of genetic difference.

 

Earth Biogenome Project

The CBI works closely with the EBP, which proposes to sequence all life on earth! Click the image above to find out more about the project.

Global Invertebrate Genomics Alliance

GIGA is a collaborative network of researchers seeking to tackle major scintific challenges in the field of genomics. To find out more, click on the link above.

FDA ARGOS

FDA-ARGOS database updates may help researchers rapidly validate diagnostic tests and use qualified genetic sequences to support future product development.