Intellectual merit. The discipline of computational cell biology seeks to develop mathematical models of living systems, such as the molecular interactions that take place during cell division. The goals for such models are twofold: 1) predict outcomes from dynamical systems in the cell, thereby allowing scientists to 2) explain how cellular processes go awry in disease. To build successful models, mathematicians and computer scientists must work closely with experimental cell biologists. In this partnership, experimentalists collect quantitative information about cellular processes and how they change over time, while mathematicians use the information to build and improve upon computer models that accurately reflect the biology. The Cold Spring Harbor Laboratory (CSHL) short course on Computational Cell Biology has taken place every summer since 2008. The course provides intensive, hands-on training over a three-week period that prepares participants to initiate their own research projects in the modeling and simulation of cellular processes or systems. Perhaps most importantly, the course provides experimental cell biologists with the language and tools necessary to launch effective collaborations with mathematical and computational scientists. Indeed, the primary audience for the course is experimental cell biologists, as the curriculum is optimized to introduce biologists to fundamental principles of mathematical modeling and not vice versa. The Computational Cell Biology course seeks to meet this special need for interdisciplinary training in advanced methodologies that is not generally available in other formal learning environments. The CSHL Computational Cell Biology course encompasses several topics that have long been studied using mathematical approaches, such as calcium signaling, the cell cycle, molecular motors, cell motility, and gene expression during development. In addition, the CSHL course provides an intellectual base for the development of newer areas of inquiry, such as the dynamics of intracellular second-messenger signaling, programmed cell death, mitotic chromosome movements, and synthetic gene networks. The course has a proven track record of bringing together theoreticians who develop the mathematical framework at the heart of the discipline with experimentalists who test the relevance of the models on real-world examples, and this creates a synergistic, interdisciplinary environment in the classroom. The course also has a high faculty-to-trainee ratio, ensuring maximal opportunity for interactions with experts in the discipline.
Broader impacts. Both the staff at CSHL and the course instructors make materials from Computational Cell Biology as widely available as possible via the Web, allowing broad dissemination of the materials to interested scientists who were not selected or were otherwise unable to attend the course. Such dissemination takes a number of forms. Materials given directly to course students are shared with members of their laboratories and other colleagues; examples include the informal manual and the course Web site, both of which are updated and produced annually. A separate online resource based on course material is aimed at educators in computational cell biology. In addition, a number of textbooks co-authored by course instructors and available to the general public include material related at least in part to the Computational Cell Biology curriculum. Applicants are selected for the course by its instructors based on several criteria. Talented students from institutions where it may be difficult to learn the course material are given special consideration, particularly if their participation will lead to dissemination within their home institutions of the methods taught in the course. Instructors strive to ensure that representative numbers of women and minority scientists are selected for their course, and U.S. citizenship or permanent residency is another important consideration. The course has a good track record of involvement from populations traditionally underrepresented in the mathematical and computational sciences, particularly women. Of particular note, the set of four course instructors for 2012 includes two women who are senior, established researchers in their respective disciplines.
