The Stanford Biomedical Informatics (BMI, formerly named Medical Information Sciences) training program continues to offer MS and Ph.D. degrees to students with an intensive training that prepares them for careers in research. The formal course curriculum trains them in a five part curriculum that features (1) core biomedical informatics, (2) domain biology or medicine (3) computer science, (4) probability and statistics, and (5) ethical, legal, and social issues. The curriculum has evolved over 18 years to offer general training in biomedical informatics, appropriate for students whose research subsequently focuses in clinical informatics and/or bioinformatics. Stanford's research milieu also continues to provide excellent opportunities for basic informatics research. Currently, we are in the 17th year as an NLM-supported training program, with 96 trainees. We have had a total of 65 graduates, 40 of whom were NLM-supported at some period. In this proposal, we request continuing support for the training of ten pre-doctoral and six post-doctoral candidates per year, representing a small shift in balance in response to our applicant pool. Most training slots will be used for BMI degree candidates, although we will take advantage of program flexibility to fund post-MD or Ph.D. candidates who are not BMI degree candidates. We are currently receiving more than 120 applications for 4-8 total spots in our program (a subset of which are NLM supported). We propose to continue our successful training program in the next five years, with a refined curriculum (recently generalized to allow informatics training in all areas of biomedicine), an expanded executive committee with greater representation of bioinformatics, an increased presence and leadership in general biomedical computation on campus at Stanford, and a continuing plan for increased affirmative action recruitment of women and minority students. The BMI program will therefore continue to produce leaders in academic and industrial biomedical informatics, and will continue to respond to the changing landscape of biomedical research in an information age.
| Zhang, Weiruo; Bouchard, Gina; Yu, Alice et al. (2018) GFPT2-Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung Adenocarcinoma. Cancer Res 78:3445-3457 |
| Liu, Boxiang; Pjanic, Milos; Wang, Ting et al. (2018) Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci. Am J Hum Genet 103:377-388 |
| Schuler, Alejandro; Callahan, Alison; Jung, Kenneth et al. (2018) Performing an Informatics Consult: Methods and Challenges. J Am Coll Radiol 15:563-568 |
| Banovich, Nicholas E; Li, Yang I; Raj, Anil et al. (2018) Impact of regulatory variation across human iPSCs and differentiated cells. Genome Res 28:122-131 |
| Hollingsworth, Scott A; Dror, Ron O (2018) Molecular Dynamics Simulation for All. Neuron 99:1129-1143 |
| Huang, Edmond Y; To, Milton; Tran, Erica et al. (2018) A VCP inhibitor substrate trapping approach (VISTA) enables proteomic profiling of endogenous ERAD substrates. Mol Biol Cell 29:1021-1030 |
| Latorraca, Naomi R; Wang, Jason K; Bauer, Brian et al. (2018) Molecular mechanism of GPCR-mediated arrestin activation. Nature 557:452-456 |
| Sweeney, Timothy E; Azad, Tej D; Donato, Michele et al. (2018) Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med 46:915-925 |
| Koh, Andrew S; Miller, Erik L; Buenrostro, Jason D et al. (2018) Rapid chromatin repression by Aire provides precise control of immune tolerance. Nat Immunol 19:162-172 |
| Marafino, Ben J; Dudley, R Adams; Shah, Nigam H et al. (2018) Accurate and interpretable intensive care risk adjustment for fused clinical data with generalized additive models. AMIA Jt Summits Transl Sci Proc 2017:166-175 |
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