The human genome project and its offshoots have dramatically increased the amount of genetic data available to researchers. Turning the flood of data generated by rapidly evolving genomic technologies and other biomedical data sources into actionable knowledge is one of the greatest scientific challenges of the 21st Century. In spite of many recent advances in computational hardware, we still lack adequate theory and algorithms to perform many fundamental genomic analysis tasks with speed and precision. It will take a new generation of scientists trained in the biological, mathematical, and computational sciences to push forward our nation's genomic agenda. Our objective is to train students with the skills needed to thrive in this modern, data- driven era of biomedical research. Students with these skills will advance biomedical knowledge and impact public health in ways that we can only dimly foresee. Few universities have the research infrastructure and human resources to mount a genomic training program of the scope possible at UCLA. The convergence of cutting edge genomic technologies, world-class computing resources, an excellent basic and clinical research faculty, and a highly rated educational institution allows us to attract and train students of the highest caliber. Our proposed renewal of the Genomic Analysis Training Program will support eight predoctoral trainees per year from a variety of disciplines. To maximize the number of trainees in genomic analysis and interpretation, we ordinarily limit them to two years of support each. Students who have completed the program will be encouraged to continue to join the training activities throughout their time at UCLA. The program course curriculum provides a rigorous and comprehensive foundation in the biological, computational and statistical sciences. The core curriculum includes courses in molecular biology, human genetics, probability, statistics, bioinformatics, and biomedical ethics. To help students build successful research careers in the current era of rapidly evolving, interdisciplinary science, the program also emphasizes training and resources in critical communication, collaboration, and career development skills. Students are required to present their research at our yearly research retreat, and are strongly encouraged to present at other research conferences. Our diverse training faculty come from multiple UCLA departments and disciplines; all have compelling records in both research, and mentoring students. During the previous funding period we made adjustments based on programmatic assessments, feedback from our trainees, and advances in scientific knowledge and education theory. In this renewal we have undertaken a comprehensive evaluation of the program and revised the program to improve the overall quality of the training experience. We believe this will allow us to continue to produce excellent trainees who will make a substantial impact on biomedical research and the nation's health goals for decades to come.
Genomics is a major driving force for modern biomedical research. Given the recent advances in genomic technologies and electronic health records, analysis and interpretation are the biggest bottlenecks to understanding the basis of human variation and disease. This training program will provide the next generation of computational genomicists with the statistics, computer science, bioinformatics, molecular biology, and genomics skills necessary to turn this flood of data into biomedical knowledge that can advance the understanding, diagnosis, and treatment of disease.
|Kusters, Cynthia D J; Paul, Kimberly C; Guella, Ilaria et al. (2018) Dopamine receptors and BDNF-haplotypes predict dyskinesia in Parkinson's disease. Parkinsonism Relat Disord 47:39-44|
|Miao, Zong; Alvarez, Marcus; Pajukanta, Päivi et al. (2018) ASElux: an ultra-fast and accurate allelic reads counter. Bioinformatics 34:1313-1320|
|Camacho, Jessica; Truong, Lisa; Kurt, Zeyneb et al. (2018) The Memory of Environmental Chemical Exposure in C. elegans Is Dependent on the Jumonji Demethylases jmjd-2 and jmjd-3/utx-1. Cell Rep 23:2392-2404|
|Freund, Malika Kumar; Burch, Kathryn S; Shi, Huwenbo et al. (2018) Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits. Am J Hum Genet 103:535-552|
|Buckner, Janet C; Ellingson, Ryan; Gold, David A et al. (2018) Mitogenomics supports an unexpected taxonomic relationship for the extinct diving duck Chendytes lawi and definitively places the extinct Labrador Duck. Mol Phylogenet Evol 122:102-109|
|Pan, David Z; Garske, Kristina M; Alvarez, Marcus et al. (2018) Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS. Nat Commun 9:1512|
|Rao, Aliz R; Nelson, Stanley F (2018) Calculating the statistical significance of rare variants causal for Mendelian and complex disorders. BMC Med Genomics 11:53|
|Gilbert, Princess S; Wu, Jing; Simon, Margaret W et al. (2018) Filtering nucleotide sites by phylogenetic signal to noise ratio increases confidence in the Neoaves phylogeny generated from ultraconserved elements. Mol Phylogenet Evol 126:116-128|
|Weinhouse, Caren; Truong, Lisa; Meyer, Joel N et al. (2018) Caenorhabditis elegans as an emerging model system in environmental epigenetics. Environ Mol Mutagen 59:560-575|
|Rao, A R; Yourshaw, M; Christensen, B et al. (2017) Rare deleterious mutations are associated with disease in bipolar disorder families. Mol Psychiatry 22:1009-1014|
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