Modern biomedical research relies on interdisciplinary approaches such as bioinformatics that synthesize knowledge and methods from other disciplines to provide an integrated framework for solving biomedical problems. The rapid advancement of high-throughput technologies for measuring biological systems has generated a significant demand at Dartmouth College and other research institutions across Northern New England for interdisciplinary approaches in the quantitative sciences (e.g. bioinformatics, biostatistics, genomics, mathematical biology, proteomics, and systems biology). Integrating high-dimensional research databases with clinical databases from medical schools and hospitals across the region will be needed for translational medicine to become a reality. Unfortunately, the research institutions in Maine, New Hampshire, and Vermont are in a largely rural setting have not kept pace those in larger metropolitan areas such as nearby Boston or New York. The goal of this COBRE program is to establish a Quantitative Biology Research Institute (QBRI) that will support and enhance quantitative biology research across the region and facilitate its integration and synergy with experimental and observational biology. This will be accomplished by 1) establishing a Quantitative Biology Research Institute (QBRI) focused on developing, supporting, and enhancing quantitative biology research in Maine, New Hampshire, and Vermont that will become nationally and internationally recognized, free standing, and will foster meaningful collaborations with experimental biologists thus improving the ability of investigators in the region to compete for NIH funding, 2) recruiting talented tenure track quantitative biologists to Maine, New Hampshire, and Vermont, 3) mentoring the development of four junior quantitative biologists across the region and 4) promoting synergistic collaborations between quantitative biologists and experimental biologists through four research projects, an Administrative Core and an Integrative Biology Core. The scientific focus of the four research projects is gene-environment interaction within the context of environmental health and toxicology. This provides an important unifying and synergistic theme for the COBRE.

Public Health Relevance

The goal of this program is to establish a Quantitative Biology Research Institute that will enhance the ability of scientists working in Northern New England to use mathematics and computer science to solve complex biomedical research questions. As such it is highly responsive to the RFA and to the strategic mission of the NCRR.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Exploratory Grants (P20)
Project #
1P20RR024475-01A2
Application #
7825972
Study Section
Special Emphasis Panel (ZRR1-RI-B (01))
Program Officer
Liu, Yanping
Project Start
2011-09-01
Project End
2016-07-31
Budget Start
2011-09-01
Budget End
2012-07-31
Support Year
1
Fiscal Year
2011
Total Cost
$2,253,453
Indirect Cost
Name
Dartmouth College
Department
Genetics
Type
Schools of Medicine
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755
Moyer, Benjamin J; Rojas, Itzel Y; Murray, Iain A et al. (2017) Indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors activate the aryl hydrocarbon receptor. Toxicol Appl Pharmacol 323:74-80
Andrew, Angeline S; Baron, John A; Butterly, Lynn F et al. (2017) Hyper-Methylated Loci Persisting from Sessile Serrated Polyps to Serrated Cancers. Int J Mol Sci 18:
Moyer, Benjamin J; Rojas, Itzel Y; Kerley-Hamilton, Joanna S et al. (2017) Obesity and fatty liver are prevented by inhibition of the aryl hydrocarbon receptor in both female and male mice. Nutr Res 44:38-50
Moyer, Benjamin J; Rojas, Itzel Y; Kerley-Hamilton, Joanna S et al. (2016) Inhibition of the aryl hydrocarbon receptor prevents Western diet-induced obesity. Model for AHR activation by kynurenine via oxidized-LDL, TLR2/4, TGF?, and IDO1. Toxicol Appl Pharmacol 300:13-24
Gui, Jiang; Greene, Casey S; Sullivan, Con et al. (2015) Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study. BioData Min 8:17
Andrew, Angeline S; Marsit, Carmen J; Schned, Alan R et al. (2015) Expression of tumor suppressive microRNA-34a is associated with a reduced risk of bladder cancer recurrence. Int J Cancer 137:1158-66
Andrew, Angeline S; Gui, Jiang; Hu, Ting et al. (2015) Genetic polymorphisms modify bladder cancer recurrence and survival in a USA population-based prognostic study. BJU Int 115:238-47
Gabor, Kristin A; Kim, Dahan; Kim, Carol H et al. (2015) Nanoscale imaging of caveolin-1 membrane domains in vivo. PLoS One 10:e0117225
Thomas, Alissa A; Fisher, Jan L; Rahme, Gilbert J et al. (2015) Regulatory T cells are not a strong predictor of survival for patients with glioblastoma. Neuro Oncol 17:801-9
Pan, Qinxin; Hu, Ting; Malley, James D et al. (2014) A system-level pathway-phenotype association analysis using synthetic feature random forest. Genet Epidemiol 38:209-19

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