The goal of the Education and Outreach Core is to increase the number of physical scientists capable of developing and applying new quantitative approaches within the context of cancer research, and to catalyze lasting collaborations that will foster innovations in the integration of the physical sciences and cancer. Our multidisciplinary educational efforts will be designed to give mathematicians and physicists an understanding of the critical computational needs within cancer research and provide cancer researchers opportunities to present challenges in cancer biology that are in need of new and more effective quantitative approaches. To this end, we will design new graduate courses at Columbia and organize a New York Metropolitan Area Discussion Group composed of mathematicians, physicists, and cancer biologists from the region. We will facilitate opportunities for mathematicians and physicists to become embedded within cancer biology laboratories with the goal of learning about cancer biology and developing new quantitative applications for the study of cancer. Finally, we will organize an annual workshop at prominent centers for theoretical physics and advanced mathematics that will bring together researchers from around the world working at the intersection of cancer biology, mathematics, and physics.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA193313-05
Application #
9697783
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
2021-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Type
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Gartrell, Robyn D; Marks, Douglas K; Hart, Thomas D et al. (2018) Quantitative Analysis of Immune Infiltrates in Primary Melanoma. Cancer Immunol Res 6:481-493
Giudice, I Del; Rigolin, G M; Raponi, S et al. (2018) Refined karyotype-based prognostic stratification of chronic lymphocytic leukemia with a low- and very-low-risk genetic profile. Leukemia 32:543-546
Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia et al. (2018) On statistical modeling of sequencing noise in high depth data to assess tumor evolution. J Stat Phys 172:143-155
Levitin, Hanna Mendes; Yuan, Jinzhou; Sims, Peter A (2018) Single-Cell Transcriptomic Analysis of Tumor Heterogeneity. Trends Cancer 4:264-268
Arnes, Luis; Liu, Zhaoqi; Wang, Jiguang et al. (2018) Comprehensive characterisation of compartment-specific long non-coding RNAs associated with pancreatic ductal adenocarcinoma. Gut :
Cimino, Patrick J; Kim, Youngmi; Wu, Hua-Jun et al. (2018) Increased HOXA5 expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma. Genes Dev 32:512-523
Puchalski, Ralph B; Shah, Nameeta; Miller, Jeremy et al. (2018) An anatomic transcriptional atlas of human glioblastoma. Science 360:660-663
Lee, Suk Hyung; Hu, Wenhuo; Matulay, Justin T et al. (2018) Tumor Evolution and Drug Response in Patient-Derived Organoid Models of Bladder Cancer. Cell 173:515-528.e17
Yuan, Jinzhou; Levitin, Hanna Mendes; Frattini, Veronique et al. (2018) Single-cell transcriptome analysis of lineage diversity in high-grade glioma. Genome Med 10:57
Tzoneva, Gannie; Dieck, Chelsea L; Oshima, Koichi et al. (2018) Clonal evolution mechanisms in NT5C2 mutant-relapsed acute lymphoblastic leukaemia. Nature 553:511-514

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