N5. Education, Training, and Outreach Program Description and Aims. The overall goal of this Component is to create a seamless interface between the fields of cancer biology and the quantitative and/or physical sciences (e.g., mathematics, computational biology, engineering, physics) to promote integration of disciplines and contribute to the expansion of the Cancer Systems Biology field. The Education and Training Components will target undergraduate and graduate students, postdoctoral fellows, as well as faculty. The Outreach Component aims to target both the broader cancer biology and quantitative research communities.
Aim 1. To educate a new generation of scientists on the application of mathematical and computational modeling to the study of cancer. We will implement focused activities including hands-on workshops, short meetings, and graduate courses.
Aim 2. To train experimental biologists on the application of mathematical and computational modeling tools and those from the quantitative (physical) sciences on the current experimental systems used to populate models. Execution of this Aim will be centered on exchange programs and Summer schools.
Aim 3 : To expand our reach to the scientific community by sharing experimental data, analysis tools, and models developed within the Center. We will implement sharing data, models, and analysis tools developed in the Backbone of our Center with the scientific community at large.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA113007-09
Application #
8449525
Study Section
Special Emphasis Panel (ZCA1-SRLB-C)
Project Start
Project End
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
9
Fiscal Year
2013
Total Cost
$100,270
Indirect Cost
$20,491
Name
Vanderbilt University Medical Center
Department
Type
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Hardeman, Keisha N; Peng, Chengwei; Paudel, Bishal B et al. (2017) Dependence On Glycolysis Sensitizes BRAF-mutated Melanomas For Increased Response To Targeted BRAF Inhibition. Sci Rep 7:42604
Udyavar, Akshata R; Wooten, David J; Hoeksema, Megan et al. (2017) Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity. Cancer Res 77:1063-1074
Harris, Leonard A; Frick, Peter L; Garbett, Shawn P et al. (2016) An unbiased metric of antiproliferative drug effect in vitro. Nat Methods 13:497-500
Franco, Omar E; Tyson, Darren R; Konvinse, Katherine C et al. (2016) Altered TGF-?/? signaling drives cooperation between breast cancer cell populations. FASEB J 30:3441-3452
Werner, Benjamin; Scott, Jacob G; Sottoriva, Andrea et al. (2016) The Cancer Stem Cell Fraction in Hierarchically Organized Tumors Can Be Estimated Using Mathematical Modeling and Patient-Specific Treatment Trajectories. Cancer Res 76:1705-13
Gerlee, Philip; Kim, Eunjung; Anderson, Alexander R A (2015) Bridging scales in cancer progression: mapping genotype to phenotype using neural networks. Semin Cancer Biol 30:30-41
Frick, Peter L; Paudel, Bishal B; Tyson, Darren R et al. (2015) Quantifying heterogeneity and dynamics of clonal fitness in response to perturbation. J Cell Physiol 230:1403-12
Nichol, Daniel; Jeavons, Peter; Fletcher, Alexander G et al. (2015) Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance. PLoS Comput Biol 11:e1004493
Broussard, Joshua A; Diggins, Nicole L; Hummel, Stephen et al. (2015) Automated analysis of cell-matrix adhesions in 2D and 3D environments. Sci Rep 5:8124
Enderling, Heiko (2015) Cancer stem cells: small subpopulation or evolving fraction? Integr Biol (Camb) 7:14-23

Showing the most recent 10 out of 88 publications