Education, Training and Outreach Program

这个核心的议程是建立一个癌症生物学系统科学(CBSS)课程，涉及与癌症相关的生物学的性质和范围，以及工程学和数学的系统研究方法的应用。基于UCB和UCSF的开创性努力，我们建议在CBSS中设计一系列本科生和研究生水平的课程。这些课程将通过UCB的生物工程项目(见Tirrell博士的支持信)进行介绍，该项目的研究生项目由UCB和UCSF联合管理。这些课程将向两个校区的学生开放，并将广泛提供，以鼓励批判性讨论和促进采用。此外，来自少数族裔院校的新本科生(通常是大三学生)将通过UCB的一流项目招收。 本科课程开发。UCB已经开始对其工程学本科系统课程进行大幅修订，新课程侧重于复杂系统的建模和分析方法(将微分方程建模与离散事件系统相结合)，以及强调系统的计算观点的新课程。此外，与UCB在全校范围内指定的计算和基因组生物学重点相结合，任何学科的本科生都可以选择一系列广泛的课程，涵盖计算方法、算法设计以及分子生物学和基因组学中的统计学。 加州大学伯克利分校生物工程系的一门相对较新的课程-微生物系统生物学前沿(在本科生和研究生水平上都有开设)向学生介绍了网络发现和动态模型设计的基本建模和分析方法，重点是两个模型系统，趋化网络和Lambda噬菌体感染。为了补充这些课程，并为我们的本科生学习系统论提供一个具体系统的重要例子，我们将开发一门名为“癌症途径建模”的“中间层”(高年级本科生，一年级研究生)项目课程。每学期，与癌症相关的通路的不同信号网络将被选为整个课程的重点。学生们将以小组形式开展与动态模型开发、分析 结果，从数据中识别网络的新部分，并发展对癌症途径的理解。我们将以这门课程为契机，从我们的HER、AKT、MEK和ERK项目中引入新的研究成果，供学生使用。我们建议该课程最初作为UCB/UCSF生物工程课程，交叉开设电气工程和计算机科学、机械工程和土木工程与环境工程，并向校园内的任何学生开放。本课程将是独立的：将在课程中使用的工具，如贝叶斯分析和建模、统计关联模型和微分方程式模型，以及人们在使用这些工具时所做的假设，将在课程的前几周介绍，随后的课程将侧重于解释关于正在研究的系统的已知或假设。该课程将被开发和 最初由Tomlin和Spellman与项目人员一起教授，我们将与其他表示对此类课程感兴趣的教职员工合作，如Adam Arkin教授和Jan Liphardt教授，他们提出了一门补充课程，名为面向物理科学家的癌症生物学。最初，招生人数将限制在40人以内，但根据本科课程设置和初步反馈，需求预计会更高。课程材料和讲座将在网上提供。

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.