The growing importance of integrative modern biomedical research has created a strong demand for investigators who have strong foundations in both the mathematical sciences and biological/medical sciences. The goal of this training program is to recruit and to train students interested in attaining such combined foundations. Trainees are recruited from pre-doctoral students already admitted to academic departments/units and counseled by participating faculty members. Twenty-seven faculty members in over a dozen departments or research units at UCLA will participate in this program. The interests of these faculty represent a broad range of biomedical research activities that bridge mathematical modeling and the biological sciences, with special strength in theoretical biophysics, genetics, medical imaging, neurosciences, pharmacology, and physiology. The emphasis of the training program will be on the early years of trainees'graduate study, providing students an integrated foundation in quantitative methodology, biological training, and research experience in mathematical modeling applications in biology to serve as a gateway to suitable dissertation research topics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Institutional National Research Service Award (T32)
Project #
5T32GM008185-23
Application #
7883165
Study Section
National Institute of General Medical Sciences Initial Review Group (BRT)
Program Officer
Hagan, Ann A
Project Start
1987-07-01
Project End
2013-06-30
Budget Start
2010-07-01
Budget End
2011-06-30
Support Year
23
Fiscal Year
2010
Total Cost
$228,218
Indirect Cost
Name
University of California Los Angeles
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Lee, Calvin K; de Anda, Jaime; Baker, Amy E et al. (2018) Multigenerational memory and adaptive adhesion in early bacterial biofilm communities. Proc Natl Acad Sci U S A 115:4471-4476
Takahashi, Toshiya; Kulkarni, Nikhil Nitin; Lee, Ernest Y et al. (2018) Cathelicidin promotes inflammation by enabling binding of self-RNA to cell surface scavenger receptors. Sci Rep 8:4032
Crawford, Forrest W; Ho, Lam Si Tung; Suchard, Marc A (2018) Computational methods for birth-death processes. Wiley Interdiscip Rev Comput Stat 10:
Lee, Michelle W; Lee, Ernest Y; Wong, Gerard C L (2018) What Can Pleiotropic Proteins in Innate Immunity Teach Us about Bioconjugation and Molecular Design? Bioconjug Chem 29:2127-2139
Lee, Ernest Y; Wong, Gerard C L; Ferguson, Andrew L (2018) Machine learning-enabled discovery and design of membrane-active peptides. Bioorg Med Chem 26:2708-2718
Lee, Ernest Y; Lee, Michelle W; Wong, Gerard C L (2018) Modulation of toll-like receptor signaling by antimicrobial peptides. Semin Cell Dev Biol :
Beichman, Annabel C; Phung, Tanya N; Lohmueller, Kirk E (2017) Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories. G3 (Bethesda) 7:3605-3620
Lee, Ernest Y; Lee, Michelle W; Fulan, Benjamin M et al. (2017) What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning? Interface Focus 7:20160153
Stolzenberg, Ethan; Berry, Deborah; Yang, De et al. (2017) A Role for Neuronal Alpha-Synuclein in Gastrointestinal Immunity. J Innate Immun 9:456-463
de Anda, Jaime; Lee, Ernest Y; Lee, Calvin K et al. (2017) High-Speed ""4D"" Computational Microscopy of Bacterial Surface Motility. ACS Nano 11:9340-9351

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