This Core's agenda is to build a Cancer Biology Systems Science (CBSS) curriculum, with implications for the nature and scope of biology related to cancer and the application of a systems research approach from engineering and mathematics. Based on groundbreaking efforts at UCB and UCSF, we propose to design a sequence of undergraduate and graduate level courses in CBSS. These courses will be introduced through UCB's Bioengineering program (see Letter of Support from Dr. Tirrell), the graduate program of which is jointly administered by UCB and UCSF. The courses will be open to students from both campuses and will be made widely available to encourage critical discussion and facilitate adoption. In addition, new undergraduate students (usually juniors) from minority institutions will be recruited through the SUPERB program at UCB. Undergraduate curriculum development. UCB has begun a drastic revision of its undergraduate systems curriculum in Engineering, with new courses that focus on methods to model and analyze complex systems (combining differential equation modeling with that of discrete event systems), and new courses that emphasize a computational view of systems. Also, in conjunction with UCB's campus-wide Designated Emphasis in Computational and Genomic Biology, undergraduates in any discipline can take a wide array of courses covering computational methods, algorithm design, and statistics in molecular biology and genomics. A relatively new course in UCB's Bioengineering department, Frontiers in Microbial Systems Biology (which is offered at both the undergraduate and graduate levels), introduces students to the basic modeling and analysis methods for network discovery and dynamic model design, focusing on two model systems, the chemotaxis network and Lambda bacteriophage infection. To complement these offerings, and to provide an important example of a concrete system for our undergraduates studying systems theory, we will develop a "mezzaninelevel" (upper year undergraduate, first year graduate) project course called "Modeling cancer pathways". Each semester, a different signaling network of a pathway related to cancer will be chosen as a focus for the whole class. Students would work in groups on projects related to the development of dynamic models, analysis results, and identification of new parts of the network from data, and developing an understanding of the cancer pathway. We will use this course as an opportunity to bring in new research results from our HER, AKT, MEK and ERK projects that the students may use. We propose to introduce the course initially as a UCB/UCSF Bioengineering course, crosslisted in Electrical Engineering and Computer Sciences, Mechanical Engineering, and Civil and Environmental Engineering, and open to any student on campus. The course will be self-contained: the tools that will be used in the class, such as Bayesian analysis and modeling, statistical association models, and differential equation models, and the assumptions that one makes in using these tools, will be presented in the first several weeks of the class, followed by lectures focusing on explanations of what is already known or hypothesized about the system under study. The course will be developed and initially taught by Tomlin and Spellman, in conjunction with project personnel, and we will work with other faculty who have expressed interest in such a course, such as Professors Adam Arkin and Jan Liphardt, who has proposed a complementary course entitled Cancer Biology for the Physical Scientist. Initially, enrollment will be limited to 40 students, though based on undergraduate systems course offerings and initial feedback, demand is expected to be higher than this. The course materials and lectures will be available on the web.

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Specialized Center--Cooperative Agreements (U54)
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Werner, Henrica M J; Mills, Gordon B; Ram, Prahlad T (2014) Cancer Systems Biology: a peek into the future of patient care? Nat Rev Clin Oncol 11:167-76
Akbani, Rehan; Ng, Patrick Kwok Shing; Werner, Henrica M J et al. (2014) A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat Commun 5:3887
Lee, Jiyoung; Lee, Jinho; Farquhar, Kevin S et al. (2014) Network of mutually repressive metastasis regulators can promote cell heterogeneity and metastatic transitions. Proc Natl Acad Sci U S A 111:E364-73
Hines, William C; Su, Ying; Kuhn, Irene et al. (2014) Sorting out the FACS: a devil in the details. Cell Rep 6:779-81
Mertins, Philipp; Yang, Feng; Liu, Tao et al. (2014) Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels. Mol Cell Proteomics 13:1690-704
Nishikawa, Taichiro; Bellance, Nad├Ęge; Damm, Aaron et al. (2014) A switch in the source of ATP production and a loss in capacity to perform glycolysis are hallmarks of hepatocyte failure in advance liver disease. J Hepatol 60:1203-11
Iadevaia, Sergio; Nakhleh, Luay K; Azencott, Robert et al. (2014) Mapping network motif tunability and robustness in the design of synthetic signaling circuits. PLoS One 9:e91743
Hoadley, Katherine A; Yau, Christina; Wolf, Denise M et al. (2014) Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158:929-44
Cope, Leslie M; Fackler, Mary Jo; Lopez-Bujanda, Zoila et al. (2014) Do breast cancer cell lines provide a relevant model of the patient tumor methylome? PLoS One 9:e105545
Oates, Chris J; Dondelinger, Frank; Bayani, Nora et al. (2014) Causal network inference using biochemical kinetics. Bioinformatics 30:i468-74

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