Turning the data collected by the Human Genome Project into knowledge is one of the biggest scientific challenges of the 21st Century. The enormous volume of DNA sequence data and protein data now collected cannot be accessed, manipulated, or analyzed without computers. However, the greatest bottlenecks involve software rather than hardware. In spite of current levels of sophistication, we still lack adequate theory and algorithms to perform many fundamental tasks in molecular genetics and genetic epidemiology with speed and precision. It will take a new generation of scientists trained in both the biological and mathematical sciences to push forward our nation's genomic agenda. Few universities have the infrastructure and human resources to mount a genomics training program of the scope possible at UCLA. This training grant has brought together faculty from four different schools and 14 different departments in the university to address the current gap in scientific training. During the years 2002 to 2006, it has trained 20 predoctoral students in the art of genomic analysis and interpretation.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Institutional National Research Service Award (T32)
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Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Graham, Bettie
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University of California Los Angeles
Biostatistics & Other Math Sci
Schools of Medicine
Los Angeles
United States
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Kusters, Cynthia D J; Paul, Kimberly C; Guella, Ilaria et al. (2017) Dopamine receptors and BDNF-haplotypes predict dyskinesia in Parkinson's disease. Parkinsonism Relat Disord :
Lin, Jer-Young; Le, Brandon H; Chen, Min et al. (2017) Similarity between soybean and Arabidopsis seed methylomes and loss of non-CG methylation does not affect seed development. Proc Natl Acad Sci U S A 114:E9730-E9739
Thompson, Michael J; vonHoldt, Bridgett; Horvath, Steve et al. (2017) An epigenetic aging clock for dogs and wolves. Aging (Albany NY) 9:1055-1068
Beichman, Annabel C; Phung, Tanya N; Lohmueller, Kirk E (2017) Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories. G3 (Bethesda) 7:3605-3620
Keys, Kevin L; Chen, Gary K; Lange, Kenneth (2017) Iterative hard thresholding for model selection in genome-wide association studies. Genet Epidemiol 41:756-768
Duong, Dat; Zou, Jennifer; Hormozdiari, Farhad et al. (2016) Using genomic annotations increases statistical power to detect eGenes. Bioinformatics 32:i156-i163
Men, Yujie; Han, Ping; Helbling, Damian E et al. (2016) Biotransformation of Two Pharmaceuticals by the Ammonia-Oxidizing Archaeon Nitrososphaera gargensis. Environ Sci Technol 50:4682-92
Gold, David A; Grabenstatter, Jonathan; de Mendoza, Alex et al. (2016) Sterol and genomic analyses validate the sponge biomarker hypothesis. Proc Natl Acad Sci U S A 113:2684-9
Chen, Haodong; Orozco, Luz D; Wang, Jessica et al. (2016) DNA Methylation Indicates Susceptibility to Isoproterenol-Induced Cardiac Pathology and Is Associated With Chromatin States. Circ Res 118:786-97
Zhang, Wenjuan; Taylor, S Paige; Nevarez, Lisette et al. (2016) IFT52 mutations destabilize anterograde complex assembly, disrupt ciliogenesis and result in short rib polydactyly syndrome. Hum Mol Genet 25:4012-4020

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