The growing importance of integrative modern biomedical research has created a strong demand for investigators who have the background and training 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, to educate the next generation of bio mathematical researchers with the skill to solve biomedical issues. Trainees are recruited from pre-doctoral students already admitted to academic departments/units and counseled by participating faculty members. Thirty-five faculty members in over a dozen departments or research units at UCLA 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 with the ability to participate in clinical and translational research activities. The emphasis of the trainng 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 and medicine to serve as a gateway to suitable dissertation research topics and future career paths.

Public Health Relevance

The goals of the systems and integrative biology training program at UCLA is to train students to be proficient in both mathematical and biological/medical sciences, in order to help solve sophisticated problems in the increasingly complex world of biomedical research.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Institutional National Research Service Award (T32)
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NIGMS Initial Review Group (TWD)
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Nie, Zhongzhen
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University of California Los Angeles
Schools of Medicine
Los Angeles
United States
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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 :
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
Lee, Ernest Y; Takahashi, Toshiya; Curk, Tine et al. (2017) Crystallinity of Double-Stranded RNA-Antimicrobial Peptide Complexes Modulates Toll-Like Receptor 3-Mediated Inflammation. ACS Nano 11:12145-12155

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