Renewal is requested for a training program in bioinformatics at North Carolina State University, support for 8 pre-doctoral trainees and 2 postdoctoral trainees. The application rests on the success of the bioinformatics graduate program at NC State. This program began in the fall of 1999 and has now produced 37 Master of Bioinformatics and 38 Ph.D. in Bioinformatics graduates. The doctoral graduates are in academic or postdoctoral positions, or are working in the pharmaceutical industry. The number of applicants to this program has risen steadily every year. The graduate training program has prerequisites in mathematics, statistics, computing, and genetics. Ph.D. candidates are engaged in coursework in bioinformatics, computer science, genetics or biochemistry, and statistics for two years, and are expected to complete their program within five years. Candidates share some courses and a journal club with candidates in a parallel degree program in functional genomics. In the last few years, the program has recruited more faculty members working in the area of environmental health and human diseases and has now a growing number of students pursuing research training in this area.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Institutional National Research Service Award (T32)
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Environmental Health Sciences Review Committee (EHS)
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Shreffler, Carol K
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North Carolina State University Raleigh
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United States
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Balik-Meisner, Michele; Truong, Lisa; Scholl, Elizabeth H et al. (2018) Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure. Environ Health Perspect 126:067010
To, Kimberly T; Fry, Rebecca C; Reif, David M (2018) Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi. BioData Min 11:10
Marvel, Skylar W; To, Kimberly; Grimm, Fabian A et al. (2018) ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models. BMC Bioinformatics 19:80
Mahapatra, Debabrata; Franzosa, Jill A; Roell, Kyle et al. (2018) Confirmation of high-throughput screening data and novel mechanistic insights into VDR-xenobiotic interactions by orthogonal assays. Sci Rep 8:8883
Balik-Meisner, Michele; Truong, Lisa; Scholl, Elizabeth H et al. (2018) Population genetic diversity in zebrafish lines. Mamm Genome 29:90-100
Ash, Jeremy; Fourches, Denis (2017) Characterizing the Chemical Space of ERK2 Kinase Inhibitors Using Descriptors Computed from Molecular Dynamics Trajectories. J Chem Inf Model 57:1286-1299
Zhang, Guozhu; Truong, Lisa; Tanguay, Robert L et al. (2017) A New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish. PLoS One 12:e0169408
Zhang, Guozhu; Roell, Kyle R; Truong, Lisa et al. (2017) A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades. Toxicol Appl Pharmacol 314:109-117
Xue, Shang; Bradbury, Peter J; Casstevens, Terry et al. (2016) Genetic Architecture of Domestication-Related Traits in Maize. Genetics 204:99-113
Zhang, Guozhu; Marvel, Skylar; Truong, Lisa et al. (2016) Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure. Reprod Toxicol 62:92-9

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