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Award Abstract # 0827278
UBM-Group: Interdisciplinary Training for Undergraduates in Mathematics and Biology at SDSU
| NSF Org: | DMS Division Of Mathematical Sciences |
| Recipient: | |
| Initial Amendment Date: | September 16, 2008 |
| Latest Amendment Date: | September 16, 2008 |
| Award Number: | 0827278 |
| Award Instrument: | Standard Grant |
| Program Manager: | Mary Ann Horn DMS Division Of Mathematical Sciences MPS Direct For Mathematical & Physical Scien |
| Start Date: | September 15, 2008 |
| End Date: | August 31, 2012(Estimated) |
| Total Intended Award Amount: | $239,625.00 |
| Total Awarded Amount to Date: | $239,625.00 |
| Funds Obligated to Date: | |
| History of Investigator: |
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| Recipient Sponsored Research Office: | 5250 CAMPANILE DR SAN DIEGO CA US 92182-1901 (619)594-5731 |
| Sponsor Congressional District: | |
| Primary Place of Performance: | 5300 Campanile Drive San Diego CA US 92115-1338 |
| Primary Place of Performance Congressional District: | |
| Unique Entity Identifier (UEI): | |
| Parent UEI: | |
| NSF Program(s): | STEP-STEM Talent Expansn Pgm, UBM |
| Primary Program Source: | 04000809DBNSF Education & Human Resource |
| Program Reference Code(s): | |
| Program Element Code(s): | |
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.049 |
ABSTRACT UMB will serve as a model for development of an undergraduate interdisciplinary program to feed our existing graduate programs in Computational Science. A Discovery Team model will integrate collaborative research efforts between faculty members from Mathematics/Computer Science and the Biology Departments for both undergraduate and predoctoral interdisciplinary training in its New Interdisciplinary Workforce program. This Mathematics-Biology Partnership model can be disseminated effectively to institutions nationwide. The project represents a departure from previous efforts to involve undergraduates in research. Biology faculty will benefit from the quantitative analyses of their research projects , while faculty in math, statistics and computer sciences will have wider-ranging applications for their existing mathematical/computer toolkits, as well as the challenge of new problems for new toolkits. Motivation for mathematics majors will come from the expanded range of problem and project options they can address as they decide their career paths in applied mathematics; biology majors will master new skill sets as they pursue bioinformatics and mathematical modeling applications in fast-growing career areas of federal strategic interest in the biotechnology, pharmaceutical, biofuels, environmental, and other human health-related industries. Research projects will use quantitative and computational tools to investigate mechanisms underlying processes in physiology, microbiology, genetics, ecology, bioinformatics, and cell and molecular biology. The SDSU UMB program will also address the national disparity of minorities in science and mathematics by recruiting, retaining, training and graduating its students to ensure competitiveness for graduate program acceptance in the emerging areas of mathematical biology. Diverse Issues in Higher Education ranks SDSU as No. 10 for the number of bachelor's degrees awarded to ethnic minorities (28.4% of the undergraduates at SDSU are from underrepresented groups, including African American, Hispanic, Native American, Pacific Islanders, or students with disabilities). The modest number of students involved will allow the SDSU UMB program to employ one-on-one mentoring and year-round monitoring of each student's success from program entry to graduation.
The San Diego State University (SDSU) Undergraduates in Mathematics and Biology (UMB) program will increase the number of undergraduates who pursue a graduate degree in interdisciplinary mathematical biology, health related fields, environment or global change, nanomaterials, and civil infrastructure (e.g., ultrasensitive sensors), and using high-performance computing, modeling, and state-of-the-art quantitative analytical tools. The project will have five major components designed to prepare undergraduates in mathematics or biological sciences (biology, microbiology) majors for interdisciplinary math-science graduate school acceptance: (1) mentoring by a team of faculty members from biology and mathematics, including monitoring and advising on academic performance and career options, (2) immersion in an interdisciplinary research project, (3) training in critical thinking skills and problem solving, (4) academic enrichment for core courses, and (5) skill set building. Each year, the UMB will identify a pool of eight qualified applicants who are talented sophom*ores or community college transfer students with a strong interest in interdisciplinary math and biology. Students will be recruited from the existing SDSU science pipeline - the pool of pre-biology, biology, pre-mathematics and mathematics majors, and transfer students from the surrounding community colleges, particularly those trained through our "Bridges to the Baccalaureate" program. This composite pool of students will be tutored in core mathematics and biology courses, will participate in various workshops, including effective research problem design, research ethics, and technical writing and scientific literature reading skills. All of these activities will engage the eight students who are the core of the UMB program, and who will receive a stipend for their participation. Other (unfunded) mathematics and biology undergraduate students interested in the content of specific modules will be welcome to attend, as space permits.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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Yue M, Rankin SC, Blanchet RT, Nulton JD, Edrwards RA, Schifferli DM "Diversification of the Salmonella fimbriae: a model of macro- and microevolution" PLoS ONE , v.7 , 2012 , p.e38596 10.1371/journal.pone.0038596
Seguritan V; Alves N Jr; Arnoult M; Raymond A; Lorimer D; Burgin AB Jr.; Salamon P; Segall AM "Artificial neural networks trained to detect viral and phage structural proteins" PLoS COmputational Biology , v.8 , 2012 , p.e1002657
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