Support is requested for the renewal of an integrated, multidisciplinary training program for pre- doctoral trainees in genomics, with the goal of providing future scientists with the quantitative and computational tools necessary for successful biological research. The genome-training program supports students in Princeton University's Graduate Program in Quantitative and Computational Biology (QCB), a joint undertaking between the Lewis-Sigler Institute for Integrative Genomics and six main partner departments (Molecular Biology, Computer Science, Chemistry, Chemical and Biological Engineering, Physics, and Ecology and Evolutionary Biology) and administered by the Institute. Genomics trainees are able to do their lab rotations and thesis research with any of 35 QCB faculties in seven departments united by common interests in quantitative and computational biology, across a wide range of research areas. We request 12 pre-doctoral positions (our current level) each year during the proposed grant period. Trainees do experimental and computational research in: functional genomics in bacteria, eukaryotic models and mammalian systems; computational projects ranging from bioinformatics and molecular evolution to large-scale data analysis and visualization; systems biology projects ranging from microbial metabolism to the biophysics of embryonic development; and theoretical projects ranging from basic dynamical modeling to modeling signal transduction in epithelia or neurons. Trainees have individualized, efficient training plans, which span on average 5.3 years, for those who received their Ph.D. in the last ten years. Formal training includes courses in genomics and genomic analysis, a seminar series, a new journal club / presentation course, responsible conduct in research training appropriate for both experimental and computational research, and other multidisciplinary activities centered in the Institute. Trainees have the opportunity to teach in a new, innovative multidisciplinary introductory program for undergraduates at Princeton. Finally, trainees and eligible faculty participate in a number of activities designed to recruit and teach individuals who are members of under-represented minority groups.
The genome and the computer have revolutionized biomedical science. To enable the success of future biomedical researchers, a new kind of graduate education program is required, one in which biology and the more quantitative sciences, especially computation, are given equal weight. The NHGRI training program at Princeton is one of the pioneer programs fulfilling this role.
| Treen, Nicholas; Heist, Tyler; Wang, Wei et al. (2018) Depletion of Maternal Cyclin B3 Contributes to Zygotic Genome Activation in the Ciona Embryo. Curr Biol 28:1150-1156.e4 |
| Brush, Eleanor R; Krakauer, David C; Flack, Jessica C (2018) Conflicts of interest improve collective computation of adaptive social structures. Sci Adv 4:e1603311 |
| Kaletsky, Rachel; Yao, Victoria; Williams, April et al. (2018) Transcriptome analysis of adult Caenorhabditis elegans cells reveals tissue-specific gene and isoform expression. PLoS Genet 14:e1007559 |
| Brush, Eleanor; Brännström, Åke; Dieckmann, Ulf (2018) Indirect reciprocity with negative assortment and limited information can promote cooperation. J Theor Biol 443:56-65 |
| Liu, Mochi; Sharma, Anuj K; Shaevitz, Joshua W et al. (2018) Temporal processing and context dependency in Caenorhabditis elegans response to mechanosensation. Elife 7: |
| Lim, Bomyi; Fukaya, Takashi; Heist, Tyler et al. (2018) Temporal dynamics of pair-rule stripes in living Drosophila embryos. Proc Natl Acad Sci U S A 115:8376-8381 |
| Klibaite, Ugne; Berman, Gordon J; Cande, Jessica et al. (2017) An unsupervised method for quantifying the behavior of paired animals. Phys Biol 14:015006 |
| GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group et al. (2017) Genetic effects on gene expression across human tissues. Nature 550:204-213 |
| Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H et al. (2017) Co-expression networks reveal the tissue-specific regulation of transcription and splicing. Genome Res 27:1843-1858 |
| Cleard, Fabienne; Wolle, Daniel; Taverner, Andrew M et al. (2017) Different Evolutionary Strategies To Conserve Chromatin Boundary Function in the Bithorax Complex. Genetics 205:589-603 |
Showing the most recent 10 out of 81 publications
