This proposal is for the renewal of a grant to train graduate and post-doctoral students in computational biology. Over the last 10 years, the University of Pennsylvania has built a strong program for training students in genomics, bioinformatics and computational biology. The training program of this grant is part of a larger training program that also embraces four different undergraduate concentrations in mathematical and computational biology and a Master's program in Bioinformatics, and which occurs in the context of a strong collaborative research effort spanning the many disciplines involved in computational biology. Current problems in computational genomics, such as trying to understand regulatory mechanisms, require combining disparate sources of knowledge such as gene expression, promoter region and intron structure and function, and comparisons across multiple organisms. Such research requires deep understanding of the biology of the organism or phenomenon being studied, and of the experimental techniques and statistical and algorithmic methods available. The purpose of this grant is to train students with these skills and to produce researchers who will be able to address current and future research needs in computational biology. Penn has made tremendous progress in computational biology training in the last few years, as was hoped by the authors of the original training grant proposal. Penn now has a new Graduate Group, Genomics and Computational Biology (GCB) within the Biomedical Graduate Studies (BGS) program in the School of Medicine (SOM), into which we took 8 PhD (including one MD/PhD) students last year, and have 7 PhD students accepted for matriculation in the fall of 2003. While it is envisioned that graduate training support from this grant will be increasingly focused on students in GCB, we plan to continue.supporting PhD students and post docs in the Biology and the Computer and Information Science (CIS) departments, as well as in the School of Medicine. We have also added new courses serving these students, and hired two new faculty members in computational biology. Most Genomics activities at Penn fall under the umbrella of the Penn Genomics Institute (PGI). PGI provides a wide variety of computational and experimental resources including microarry facilities, proteomics facilities, hardware and software for bioinformatics, and training and consulting. All students funded by this grant will have access to these facilities. PGI includes the Penn Center for Bioinformatics (PCBI), which although mainly a research center, is significantly involved with the training program. For example, in their first year, GCB students are housed in PCBI, and students will do research rotations with PCBI faculty.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Institutional National Research Service Award (T32)
Project #
5T32HG000046-07
Application #
6904643
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Graham, Bettie
Project Start
1999-07-16
Project End
2009-05-31
Budget Start
2005-06-01
Budget End
2006-05-31
Support Year
7
Fiscal Year
2005
Total Cost
$502,255
Indirect Cost
Name
University of Pennsylvania
Department
Genetics
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Zheng, Qi; Bartow-McKenney, Casey; Meisel, Jacquelyn S et al. (2018) HmmUFOtu: An HMM and phylogenetic placement based ultra-fast taxonomic assignment and OTU picking tool for microbiome amplicon sequencing studies. Genome Biol 19:82
SanMiguel, Adam J; Meisel, Jacquelyn S; Horwinski, Joseph et al. (2018) Antiseptic Agents Elicit Short-Term, Personalized, and Body Site-Specific Shifts in Resident Skin Bacterial Communities. J Invest Dermatol 138:2234-2243
Shields, Emily J; Sheng, Lihong; Weiner, Amber K et al. (2018) High-Quality Genome Assemblies Reveal Long Non-coding RNAs Expressed in Ant Brains. Cell Rep 23:3078-3090
Way, Gregory P; Greene, Casey S (2018) Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders. Pac Symp Biocomput 23:80-91
Meisel, Jacquelyn S; Sfyroera, Georgia; Bartow-McKenney, Casey et al. (2018) Commensal microbiota modulate gene expression in the skin. Microbiome 6:20
Way, Gregory P; Sanchez-Vega, Francisco; La, Konnor et al. (2018) Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas. Cell Rep 23:172-180.e3
Knijnenburg, Theo A; Wang, Linghua; Zimmermann, Michael T et al. (2018) Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas. Cell Rep 23:239-254.e6
DuBois, Steven G; Mody, Rajen; Naranjo, Arlene et al. (2017) MIBG avidity correlates with clinical features, tumor biology, and outcomes in neuroblastoma: A report from the Children's Oncology Group. Pediatr Blood Cancer 64:
Mellis, Ian A; Gupte, Rohit; Raj, Arjun et al. (2017) Visualizing adenosine-to-inosine RNA editing in single mammalian cells. Nat Methods 14:801-804
Beagan, Jonathan A; Duong, Michael T; Titus, Katelyn R et al. (2017) YY1 and CTCF orchestrate a 3D chromatin looping switch during early neural lineage commitment. Genome Res 27:1139-1152

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