California State University, Los Angeles proposes to engage in a five-year project for curricular change that will improve the quantitative skills of its biology and biochemistry undergraduates, and prepare them for careers in life science. Students graduating over the next ten years will have the opportunity to make a strong impact on the growing fields of personalized medicine, genetically modified crops, and the war on bioterrorism. The challenge is that biological data are being gathered and characterized at an increasingly rapid pace and the tools for data analysis are complex. For future biologists to contribute to these exciting new fields, a change in the traditional life science curriculum is required. The Dean of the College of Natural and Social Sciences is program director of the project, and will oversee activities of a working group of faculty from the Departments of Biological Sciences, Chemistry and Biochemistry, Physics, Mathematics, and Computer Science. To help equip our students with the skills necessary for their success, we have formulated the following specific goals: (1) improve quantitative skills of life science undergraduate students, (2) integrate the biology and quantitative sciences curricula (physics, math, chemistry, and computer science), (3) prepare students for graduate programs and careers in bioinformatics. To strive toward these goals we propose to accomplish the following specific aims during the project duration: (1) modify the mathematics curriculum for the Bachelor of Science degree in Biology, (2) introduce quantitative teaching modules into biology courses, (3) offer a minor in Bioinformatics for students with cross-disciplinary interests, and (4) create a campus-based Center for Interdisciplinary Quantitative Analysis. Our rationale is that meaningful collaboration between life scientists and quantitative scientists can occur only if there is substantive communication, at a high level, between them. By applying new pedagogical approaches, such as the scientific teaching approach, we expect that students will improve their quantitative skills and better understand the connections between the scientific disciplines.
|Mendoza, Michael; Mandani, Garni; Momand, Jamil (2014) The MDM2 gene family. Biomol Concepts 5:9-19|
|Warner, Wayne A; Sanchez, Ricardo; Dawoodian, Alex et al. (2012) Identification of FDA-approved drugs that computationally bind to MDM2. Chem Biol Drug Des 80:631-7|