We seek renewal of our NLM Training Program in Biomedical Informatics (NLMTP), which the NLM has supported for twenty years. The program, evolving as biomedical informatics (BMI) itself has evolved, has consistently produced outstanding trainees. In this renewal, we address new challenges to BMI arising from digital information streaming from innumerable sensors, instruments and simulations, which are outrunning our capacity to accumulate, organize and analyze it. Advances in BMI are needed: 1) to make sense of datasets that may be massive, heterogeneous or even contain errors, 2) to cull from them important insights into fundamental problems of biomedicine and 3) to convey information in ways readily understood by researchers and clinicians. These are fundamental BMI problems, which we will address in the NLMTP renewal. We will emphasize health care/clinical informatics (HC), translational bioinformatics (TB) and clinical research informatics (CR), areas in which our trainees will contribute to progress needed to gain the full wealth of knowledge embedded in genomic, proteomic, genetic, epidemiological, and clinical data and a full return on our substantial investments in health information technology. Our trainees will bring to each of these BMI domains what we call data-driven inference and decision making (DIDM) by which we mean the use computer programs to seek associations in databases whose complexity hides such relations from even expert humans and cognitive informatics and decision making to make such discovered patterns intelligible to humans. Our pre-doctoral trainees will be selected from graduate students who have completed one year of study at one of six participating institutions. NMLTP training will combine DIDM and BMI specific courses and research to engage them with the range of opportunities in HC, TB and CR suggested above. We also will involve pre- and postdoctoral trainees in a set of courses and activities to facilitate their integration into the BMI community. Over many years, our NLMTP has brought computation, mathematics, statistics, simulation and advanced imaging to bear on biomedical problems that were before deemed intractable. Now our researchers are deploying powerful new computational methodologies for data exploration on an unprecedented scale that offer exciting opportunities for the training to prepare a new generation of BMI professionals. We are requesting 9 pre-doctoral and 6 postdoctoral positions for this renewal.

Public Health Relevance

GORRY, G.A. NLM T15 LM007093 Project Narrative - Relevance: We seek renewal of our NLM Training Program in Biomedical Informatics, which over many years has brought computation, mathematics, statistics, simulation and advanced imaging to bear on biomedical problems that were before deemed intractable. Now our program will expand to include powerful new computational methodologies of data-driven inference and decision making, and cognitive informatics, to cull the most important elements from genomic, proteomic, genetic, epidemiological, and clinical data applying to fundamental problems of biomedicine, and to enable a full return on our substantial investments in health information technology. Our 9 pre- and 6 postdoctoral trainees will prepare for careers as biomedical informatics professionals by pursuing coursework and research projects in health care/clinical informatics, translational bioinformatics, and clinical research informatics.

Agency
National Institute of Health (NIH)
Type
Continuing Education Training Grants (T15)
Project #
5T15LM007093-23
Application #
8681514
Study Section
Special Emphasis Panel (ZLM1)
Program Officer
Florance, Valerie
Project Start
Project End
Budget Start
Budget End
Support Year
23
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Rice University
Department
Biostatistics & Other Math Sci
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
City
Houston
State
TX
Country
United States
Zip Code
77005
Whaley, Meagan Lee; Kadipasaoglu, Cihan Mehmet; Cox, Steven James et al. (2016) Modulation of Orthographic Decoding by Frontal Cortex. J Neurosci 36:1173-84
Jones, Stephen L; Ashton, Carol M; Kiehne, Lisa et al. (2016) The Sepsis Early Recognition and Response Initiative (SERRI). Jt Comm J Qual Patient Saf 42:122-38
Wilson, Stephen J; Wilkins, Angela D; Lin, Chih-Hsu et al. (2016) DISCOVERY OF FUNCTIONAL AND DISEASE PATHWAYS BY COMMUNITY DETECTION IN PROTEIN-PROTEIN INTERACTION NETWORKS. Pac Symp Biocomput 22:336-347
Liu, Yanhong; Kheradmand, Farrah; Davis, Caleb F et al. (2016) Focused Analysis of Exome Sequencing Data for Rare Germline Mutations in Familial and Sporadic Lung Cancer. J Thorac Oncol 11:52-61
Chiang, Sharon; Levin, Harvey S; Wilde, Elisabeth et al. (2016) White matter structural connectivity changes correlate with epilepsy duration in temporal lobe epilepsy. Epilepsy Res 120:37-46
Chiang, Sharon; Cassese, Alberto; Guindani, Michele et al. (2016) Time-dependence of graph theory metrics in functional connectivity analysis. Neuroimage 125:601-15
Davis, Caleb F; Ritter, Deborah I; Wheeler, David A et al. (2016) SV-STAT accurately detects structural variation via alignment to reference-based assemblies. Source Code Biol Med 11:8
Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M et al. (2016) UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures. Nucleic Acids Res 44:D308-12
Rusin, Craig G; Acosta, Sebastian I; Shekerdemian, Lara S et al. (2016) Prediction of imminent, severe deterioration of children with parallel circulations using real-time processing of physiologic data. J Thorac Cardiovasc Surg 152:171-7
Peterson, Christine B; Stingo, Francesco C; Vannucci, Marina (2016) Joint Bayesian variable and graph selection for regression models with network-structured predictors. Stat Med 35:1017-31

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