Support is requested for a renewal of a multi-disciplinary training program in genomics at Princeton, aimed at educating genome scientists with the quantitative and computational tools likely to be required for the biology of the future. The genome training program will support students in Princeton's Graduate Program in Quantitative and Computational Biology (QCB), a joint undertaking between the Lewis-Sigler Institute for Integrative Genomics and five Princeton departments (Computer Science, Ecology and Evolutionary Biology, Molecular Biology, Chemistry and Physics) and administered by the Institute. Genomics trainees will be able to do their thesis research with any of 49 QCB faculty in 10 departments united by common interests in quantitative and computational biology. Trainees will do research in functional genomics in bacteria, eukaryotic models and mammalian systems;computational projects ranging from bio-informatics and molecular evolution to high-throughput data visualization and systems biology projects ranging from microbial metabolism to systems neuroscience;and theoretical projects ranging from basic dynamical modeling to modeling signal transduction in epithelia or neurons. Because the training program, completely new when the training grant was awarded, is still growing, and because it is still one of the few of its kind, we request a modest increase from 9 positions (the current level), ramping up one position per year to a new steady state of 12 slots. Trainees will have an individualized training plan administered by the Executive Committee of the QCB and a Genomics Committee;formal training will include new courses in genomics and genomic analysis, a seminar series, a student-run journal club, and other multi-disciplinary activities centered in the Institute. Trainees will have the opportunity to teach in a new innovative multidisciplinary introductory program for undergraduates at Princeton. Finally, trainees and eligible faculty will 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. In order that the medical science of the future takes full advantage of this revolution, a new kind of education for Ph.D. biomedical scientists 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.
|Falahati, Hanieh; Wieschaus, Eric (2017) Independent active and thermodynamic processes govern the nucleolus assembly in vivo. Proc Natl Acad Sci U S A 114:1335-1340|
|Klibaite, Ugne; Berman, Gordon J; Cande, Jessica et al. (2017) An unsupervised method for quantifying the behavior of paired animals. Phys Biol 14:015006|
|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|
|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|
|Strandburg-Peshkin, Ariana; Farine, Damien R; Crofoot, Margaret C et al. (2017) Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement. Elife 6:|
|Jeffers, Tess E; Lieb, Jason D (2017) Nucleosome fragility is associated with future transcriptional response to developmental cues and stress in C. elegans. Genome Res 27:75-86|
|Kaletsky, Rachel; Lakhina, Vanisha; Arey, Rachel et al. (2016) The C. elegans adult neuronal IIS/FOXO transcriptome reveals adult phenotype regulators. Nature 529:92-6|
|Falahati, Hanieh; Pelham-Webb, Bobbie; Blythe, Shelby et al. (2016) Nucleation by rRNA Dictates the Precision of Nucleolus Assembly. Curr Biol 26:277-85|
|Zhou, Jian; Troyanskaya, Olga G (2016) Probabilistic modelling of chromatin code landscape reveals functional diversity of enhancer-like chromatin states. Nat Commun 7:10528|
|Krishnan, Arjun; Zhang, Ran; Yao, Victoria et al. (2016) Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder. Nat Neurosci 19:1454-1462|
Showing the most recent 10 out of 74 publications