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Carolina Environmental Bioinformatics Center
EPA Grant Number: R832720Center: The Carolina Environmental Bioinformatics Research Center
Center Director: Wright, Fred A.
Title: Carolina Environmental Bioinformatics Center
Investigators: Wright, Fred A. , Galluppi, Kenneth J. , Kupper, Lawrence , Marron, J. Stephen , Prins, Jan F. , Rusyn, Ivan , Stotts, David , Threadgill, David , Tropsha, Alex
Current Investigators: Wright, Fred A. , Farber, Rosann , Hemminger, Brad , Rusyn, Ivan , Stotts, David , Tropsha, Alex
Institution: University of North Carolina at Chapel Hill
EPA Project Officer: Mustra, David
Project Period: October 1, 2005 through September 30, 2010
Project Amount: $4,494,117
RFA: Computational Toxicology: Environmental Bioinformatics Research Center (2004)
Research Category: Health Effects , Computational Toxicology
Description:
Objective:The Carolina Environmental Bioinformatics Research Center brings together multiple investigators and disciplines, combining expertise in biostatistics, computational biology, chem-informatics and computer science to advance the field of Computational Toxicology.
The objective of this proposal is to create an Environmental Bioinformatics Research Center with broad-ranging capability to enhance and advance the field of Computational Toxicology. The Center will develop novel analytic and computational methods, create efficient user-friendly tools to disseminate the methods to the wider community, and will apply the computational methods to data from molecular toxicology and other studies.
Approach:Effort will be divided into three Research Projects and an Administrative Unit. Each Research Project is further divided into Functional Areas consisting of Analysis, Methods Development, and Tools Development. Project 1 (Biostatistics in Computational Biology) will provide biostatistical support to the Center, performing analysis and developing new methods in collaboration with EPA personnel and the computational toxicology community. Project 2 (Chem-informatics) will coordinate the compilation and mining of data from relevant external databases and perform analysis and methods development for investigating Quantitative Structure-Activity Relationships with burgeoning high-throughput chem-informatics data. In addition, Project 2 will develop computational tools to perform these tasks. Project 3 (Computational Infrastructure for Systems Toxicology) will create a framework for merging data from various –omic technologies in a systems biology approach. The investigation of rodent liver toxicity is used as a driving biological problem, inspiring new methods and architectures for data storage. Finally, Project 3 will provide programming support for the further development of tools arising from Projects 1 and 2. The Administration Core provides and staff and support to the Center, is responsible for ensuring that Center objectives and goals are being met, and provides oversight for each for the Functional Areas. A detailed Quality Management Plan ensures that the research and data management will be conducted with integrity and adhering to appropriate data interchange standards. The plans for Public Outreach and Translation Activity will ensure that the activities of the Center are translated into useable information and materials for the public and policy makers.
Expected Results:The Center is expected to advance the field of computational toxicology through the development of new methods and tools, as well as through direct collaborative efforts with EPA and other environmental scientists. In each Project, we expect that new methods will be developed and published that represent the state-of-the-art. The tools developed within each project will be widely disseminated, and will be useful both to trained bioinformatics scientists and bench scientists. The synthesis of data from a variety of sources will move the field of computational toxicology from a hypothesis-driven science toward a predictive science. Each Project is goal-oriented, with criteria for success that will be reviewed by the Scientific Advisory Committee.
Journal Articles: 10 Displayed | Download in RIS Format
| Other center views: | All 50 publications | 10 publications in selected types | All 10 journal articles |
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Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Genome-level analysis of genetic regulation of liver gene expression networks. Hepatology 2007;46(2):548-557. |
R832720 (2007) |
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Graham MR, Virtaneva K, Porcella SF, Gardner DJ, Long RD, Welty DM, Barry WT, Johnson CA, Parkins LD, Wright FA, Musser JM. Analysis of the transcriptome of Group A Streptococcus in mouse soft tissue infection. American Journal of Pathology 2006;169(3):927-942. |
R832720 (2007) |
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Hu J, Wright FA, Zou F. Estimation of expression indexes for oligonucleotide arrays using the singular value decomposition. Journal of the American Statistical Association 2006;101(473):41-50. |
R832720 (2006) |
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Nadler JJ, Zou F, Huang H, Moy SS, Lauder J, Crawley JN, Threadgill DW, Wright FA, Magnuson TR. Large-scale gene expression differences across brain regions and inbred strains correlates with a behavioral phenotype. Genetics 2006;174(3):1229-1236. |
R832720 (2006) |
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Roberts A, Pardo-Manuel de Villena F, Wang W, McMillan L, Threadgill DW. The polymorphism architecture of mouse genetic resources elucidated using genome-wide resequencing data: implications for QTL discovery and systems genetics. Mammalian Genome 2007;18(6-7):473-481. |
R832720 (2007) |
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Tropsha A, Golbraikh A. Predictive QSAR modeling workflow, model applicability domains, and virtual screening. Current Pharmaceutical Design 2007;13(34):3494-3504. |
R832720 (2007) |
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Woods CG, Vanden Heuvel JP, Rusyn I. Genomic profiling in nuclear receptor-mediated toxicity. Toxicologic Pathology 2007;35(4):474-494. |
R832720 (2007) |
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Woods CG, Kosyk O, Bradford BU, Ross PK, Burns AM, Cunningham ML, Qu P, Ibrahim JG, Rusyn I. Time course investigation of PPARα-and Kupffer cell-dependent effects of WY-14,643 in mouse liver using microarray gene expression. Toxicology and Applied Pharmacology 2007;225(3):267-277. |
R832720 (2007) |
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Wright FA, Huang H, Guan X, Gamiel K, Jeffries C, Barry WT, Pardo-Manuel de Villena F, Sullivan PF, Wilhelmsen KC, Zou F. Simulating association studies: a data-based resampling method for candidate regions or whole genome scans. Bioinformatics 2007;23(19):2581-2588. |
R832720 (2007) |
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Zhu H, Rusyn I, Richard A, Tropsha A. The use of cell viability assay data improves the prediction accuracy of conventional quantitative structure activity relationship models of animal carcinogenicity. Environmental Health Perspectives 2008 Jan 4 [Epub ahead of print] doi:10.1289/ehp.10573. |
R832720 (2007) |
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Toxicogenomics, toxics, chemicals, dose-response, QSAR, QSPR, molecular biology, quantitative risk assessment, public policy,
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ENVIRONMENTAL MANAGEMENT, Scientific Discipline, Health, Risk Assessment, Biology, Risk Assessments, Biochemistry, Environmental Monitoring, exposure assessment, biochemical research, chemical composition, ecological risk assessment, toxicologic assessment, bioinformatics, human health risk, biopollution, biostatistics, dose-response, toxicology, environmental risks, risk, outreach and training, computational toxicology
Progress and Final Reports:
2006 Progress Report
2007 Progress Report