Computational and Analytical Methodologies

The center will evolve a culture where computational expertise and biological research are blended within each research group, and not siloed into distinct collaborating teams.

Students and postdocs in Sohini Ramachandran’s lab are developing new computational and analytical methodologies to identify risk genes for leukemia that differ in incidence across ethnic groups and genders.

Nicola Neretti, PhD

A Drug Repositioning Strategy for Healthspan Extension

Aging is the single most important risk factor for a wide range of chronic illnesses, including diabetes, heart disease, cancer and neurodegenerative diseases. Hence, interventions that can slow aging have the potential to prevent or at least retard the onset of these debilitating diseases.  It was recently discovered that senescent cell clearance in mouse aging models improves healthspan and extends lifespan.

Shipra Vaishnava, PhD

Spatial and Functional Organization of Intestinal Microbiome

The most prominent diseases of modern times--including inflammatory bowel diseases (IBD) such as Crohn's, ulcerative colitis, and colon cancer as well as metabolic diseases such as diabetes and obesity--are caused as a result of failure to maintain homeostatic interactions with commensal bacteria.  However, at the moment, we do not fully understand the mechanisms that regulate host-microbe interactions.  Moreover, attempts to identifiy common microbiome associated patterns linked with these diseases have either failed or are inconsistent at best.  It is likely that the intestinal flora is s

Alper Uzun, PhD

Computational Genomics of Preeclampsia

In the post genome era, biological research and genomic medicine have been transformed by high-throughput technologies.  New techniques have enabled researchers to investigate biological systems in great detail.  Nonetheless, the extraordinary amount of information in the large number of emerging high-dimension datasets has not been fully exploited.  Increasingly, pathway analysis and other a priori biological knowledge based approaches have improved success in extraction of valuable information from high-throughput experiments and genome-wide association studies.  Preeclampsia is a complex

Welcome to the funding announcements page for the COBRE Center for Computational Biology of Human Disease (CBHD).  This is where you will find our most current funding announcements for our COBRE CBHD Research Project Awards and our COBRE CBHD Institutional Pilot Awards.   If you have any questions regarding our funding announcements, you can email cbhd@brown.edu or call Tricia Werner at 401-863-6275. 

David Rand, PhD

Director of COBRE Center for Computational Biology of Human Disease

Co-Director of Computational Biology Core

Welcome to the Brown University COBRE Center for Computational Biology of Human Disease.  We are grateful to the National Institute of General Medical Sciences (NIGMS) for the support to establish this Center and allow us to build a computational biology infrastructure for the greater Brown and hospital environments that will benefit the study of human disease across all of Rhode Island. This Center provides a centralized service to assist researchers in computational, bioinformatic, and data management challenges of analyzing large data sets made available by modern "omics" technologies.  In addition, this funding will support the research activities of junior investigators to ensure their transition to stand-alone extramurally funded research scientists.  We use an innovative joint mentoring process, where each junior faculty member is advised by both computational and biological or clinical senior faculty members. In addition, staff in our Computational Biology Core will be active members of each of these laboratory groups to better integrate all phases of the research activities.

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