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Final Progress Reports: Dartmouth College: Integrative Biology Core

Superfund Research Program

Integrative Biology Core

Project Leaders: Jason H. Moore, Jason H. Moore
Grant Number: P42ES007373
Funding Period: 2008-2014

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Final Progress Reports

Year:   2013 

Studies and Results: The Institute for Quantitative Biomedical Sciences (iQBS) at Dartmouth is committed to building, enhancing and supporting education, infrastructure and research at the intersection of bioinformatics, biostatistics and epidemiology. These efforts are supported by institutional funds and by support from an $11 million NIH/NIGMS Center of Biomedical Research Excellence (COBRE) grant, awarded in 2012, which focuses on bioinformatics research for understanding gene-environment interactions. In 2012, iQBS received approval from the Board of Trustees to grant Ph.D. degrees as part of the new Graduate Program in Quantitative Biomedical Sciences. In 2012 there were six students in the program from of variety of backgrounds including biology, computer science, engineering and mathematics. In addition to education, iQBS has actively supported bioinformatics and computational infrastructure such as the DISCOVERY high-performance computer cluster that will pass 2000 processors in 2013. Finally, iQBS participated in 2012 in the recruitment of numerous new faculty in the quantitative biomedical sciences. Financial support was provided for the recruitment of Drs. Chris Amos (Director of Biostatistics, Associate Director for Population Sciences), Amar Das (Director of Biomedical Informatics), Chao Cheng (Assistant Professor of Genetics, Bioinformatics), Casey Greene (Assistant Professor of Genetics, Bioinformatics), Diane Gilbert-Diamond (Assistant Professor of Community and Family Medicine, Epidemiology), Scott Williams (Professor of Genetics, Health Disparities), and Olga Zhaxybayeva (Assistant Professor Biology, Bioinformatics), for example. This brings the total number of research labs in iQBS to 28.

In addition to meeting weekly with Superfund investigators, most members of the iQBS are also members of the Integrative Biology Committee for the Geisel School of Medicine at Dartmouth. This committee exists to foster communication and collaboration among diverse groups of scientists. This group also plans the Annual Integrative Biology Symposium that is supported by the Superfund Research Program. In April 2013 the Integrative Biology Core successfully held the Sixth Annual Dartmouth Integrative Biology Symposium with the theme of "Obesity and Human Health". This conference was attended by ~300 scientists and trainees. One talk highly relevant to the mission of the SRP-NIEHS-Dartmouth SRP was titled "Aryl Hydrocarbon Receptor (AHR) and Western Diet as Agents of Obesity".

In 2013 iQBS faculty actively collaborated with all Superfund PIs. Dr. Moore has continued to work closely with Drs. Guerinot and Punshon to adapt and apply machine learning algorithms to the genome-wide analysis of toxic metal response in plants and to develop 3D methods for visualizing high-dimensional toxic metal distributions across rice kernels. The Core also supports Drs. Karagas's and Stanton's efforts to develop network modeling approaches for detecting gene-environment interactions. Dr. Moore also worked to extend and support the Oracle database developed specifically for SRP projects as well as Dr. Jackson and the Trace Elements Analysis Core to support a comprehensive Oracle database for managing orders and finances in order to improve Core efficiency. In addition, the Core supported Dr. Borsuk (CEC) and Dr. Chen they analyze multiple stressors using a novel adaptive interactive design (AID) method, and a model of sediment-water column-food web mercury exchange using the dynamic modeling environment AQUASIM.

Significance: Bioinformatics support of studies in the Superfund Program is significant because this program has demonstrated that very low levels of arsenic and mercury, relevant to the US population, cause significant adverse health effects. The Core enhances the team's research by providing unique and distinctive bioinformatics and data modeling support.

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