The Colorado Biomedical Informatics Training Program is an independent, Ph.D.- granting and postdoctoral training program based in the University of Colorado School of Medicine, with a 10 year track record of innovative and effective training of pre- and post-doctoral fellows for research careers. We are a second-generation teaching program, informed by the experience of the many biomedical informatics training models that have come before us. Our program is designed to produce graduates with depth in both computational methods and biomedicine, an intimate familiarity with the science and technology that synergizes the two, and the skills necessary to pioneer novel computational approaches to significant biomedical questions. We are aware of the difficulty of achieving both breadth and depth in a reasonable amount of time, and believe we have identified a novel approach that is capable of training productive interdisciplinary scientists in a relatively short period. The program is tightly focused on transforming already strong students and recent Ph.D.'s into mature and productive scientists. Our program is structured around a set of four categories of educational goals and objectives: knowledge, communication skills, professional behavior, and self- directed life-long learning. Our graduates demonstrate the knowledge of core concepts and principles of biomedical informatics, and have the ability to apply computation to gain insight into important biomedical problems. Their knowledge includes mastery of the fundamentals of biomedicine, clinical and translational research, statistics and computer science, as well as proficiency in the integration of these fields. Our graduates have contributed to the discovery and dissemination of new knowledge. They demonstrate interpersonal, oral and written skills that enable them to interact productively with scientists from both biomedical and computational domains, to communicate the results of their work in appropriate formats, and to teach others biomedical informatics skills;they effectively bridge the gap between biomedical and computational cultures. Our graduates demonstrate the highest standards of professional integrity and exemplary behavior, as reflected in a commitment to the ethical conduct of research, continuous professional development and thoughtfulness regarding the broader implications of their work. Our graduates demonstrate habits and skills for self-directed and life-long learning, and recognize that biomedical informatics is a rapidly evolving discipline. Our program itself is also undergoing continuous improvement, carefully tracking our efforts and quickly responding to changes in the field and our situation. We are justifiably proud of our outstanding track record as well as our dynamic and adaptive approach to the training of adept, flexible and curious scientists able to comfortably assimilate new ideas and technologies during the course of their professional careers. During the next period, we propose to develop a training track in Clinical Research informatics, to complement our existing training in Translational Informatics. Our training grant supports six predoctoral and three postdoctoral trainees;it is currently supplemented by an ARRA-related award of an additional one predoctoral and three postdoctoral slots. Based on our successful track record, we are requesting that the ARRA supplemental slots be continued, the addition of one predoctoral and one postdoctoral slot, and the creation of four short term diversity-related positions, for a total request of 8 predoctoral, 7 postdoctoral and 4 short term positions.

Public Health Relevance

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National Institute of Health (NIH)
National Library of Medicine (NLM)
Continuing Education Training Grants (T15)
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Special Emphasis Panel (ZLM1-AP-T (01))
Program Officer
Florance, Valerie
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University of Colorado Denver
Schools of Medicine
United States
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Halper-Stromberg, Eitan; Steranka, Jared; Burns, Kathleen H et al. (2014) Visualization and probability-based scoring of structural variants within repetitive sequences. Bioinformatics 30:1514-21
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