Bioinformatics and computational biology are two related disciplines that have developed from the need to analyze and interpret large, complex datasets which have emerged in the last decade as genomics, proteomics, systems biology, and other high-throughput approaches have become more feasible. Bioinformatics and computational biology utilize techniques from applied mathematics, informatics, statistics, and computer science to solve biological problems. The Predoctoral Training Program in Bioinformatics and Computational Biology (BCB) was established at UNC-Chapel Hill in the Fall 2002 to address these needs. In 2007 the training program transitioned to the Ph.D. Curriculum in Bioinformatics and Computational Biology. The goal of the Ph.D. Curriculum is to train the next generation of scientists who can develop and apply quantitative/analytical tools to driving biological problems. The Ph.D. curriculum provides the necessary latitude to prepare students with the right balance of quantitative skills (e.g., mathematics, statistics, and computer science) and experimental approaches (e.g., genetics, cell biology, molecular biology) for making important contributions to modern biological research. There are currently 13 full professors, 8 associate professors, and 16 assistant professors among the 37 total BCB faculty. The Ph.D. curriculum consists of four key components: formal coursework, research rotations, Ph.D. research and a colloquium. The coursework is includes three tiers of training: foundational courses, core modules, and advanced courses. Eight specialized core modules have been developed that cover major areas of bioinformatics and computational biology, such as information theory, machine learning, sequence comparison, phylogeny, data management, ontology, data mining, biostatistics, biomolecular structure/function prediction, and modeling of complex systems. Funds are requested to support six predoctoral students per year. The requested funds will dovetail with the UNC investment in research infrastructure, faculty recruitment, and education in both genomics and bioinfonnatics and computational biology, leveraging intramural as well as extramural industrial support to expand this vital interdisciplinary training program.

Public Health Relevance

Interpreting the vast amount of data produced by high throughput biomedical technologies requires novel computational and mathematical approaches. The Curriculum in Bioinformatics and Computational Biology at the University of North Carolina at Chapel Hill provides the graduate training needed to develop and apply computational methods for solving driving complex biomedical problems.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Institutional National Research Service Award (T32)
Project #
5T32GM067553-08
Application #
8289468
Study Section
National Institute of General Medical Sciences Initial Review Group (BRT)
Program Officer
Somers, Scott D
Project Start
2005-07-01
Project End
2015-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
8
Fiscal Year
2012
Total Cost
$143,844
Indirect Cost
$8,490
Name
University of North Carolina Chapel Hill
Department
Biochemistry
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Chesler, Elissa J; Gatti, Daniel M; Morgan, Andrew P et al. (2016) Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection. G3 (Bethesda) 6:3893-3902
Morgan, Andrew P; Holt, J Matthew; McMullan, Rachel C et al. (2016) The Evolutionary Fates of a Large Segmental Duplication in Mouse. Genetics 204:267-85
Parry, Traci L; Desai, Gopal; Schisler, Jonathan C et al. (2016) Fenofibrate unexpectedly induces cardiac hypertrophy in mice lacking MuRF1. Cardiovasc Pathol 25:127-40
Lyons, Shawn M; Cunningham, Clark H; Welch, Joshua D et al. (2016) A subset of replication-dependent histone mRNAs are expressed as polyadenylated RNAs in terminally differentiated tissues. Nucleic Acids Res 44:9190-9205
Kardos, Jordan; Chai, Shengjie; Mose, Lisle E et al. (2016) Claudin-low bladder tumors are immune infiltrated and actively immune suppressed. JCI Insight 1:e85902
Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra et al. (2016) CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect 124:1023-33
Shobair, Mahmoud; Dagliyan, Onur; Kota, Pradeep et al. (2016) Gain-of-Function Mutation W493R in the Epithelial Sodium Channel Allosterically Reconfigures Intersubunit Coupling. J Biol Chem 291:3682-92
Morgan, Andrew P; Didion, John P; Doran, Anthony G et al. (2016) Whole Genome Sequence of Two Wild-Derived Mus musculus domesticus Inbred Strains, LEWES/EiJ and ZALENDE/EiJ, with Different Diploid Numbers. G3 (Bethesda) 6:4211-4216
Xu, Zheng; Zhang, Guosheng; Duan, Qing et al. (2016) HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants. BMC Res Notes 9:159
Schoenrock, Sarah Adams; Oreper, Daniel; Young, Nancy et al. (2016) Ovariectomy results in inbred strain-specific increases in anxiety-like behavior in mice. Physiol Behav 167:404-412

Showing the most recent 10 out of 58 publications