We seek renewal of our NLM Training Program in Biomedical Informatics and Data Science (NLMTP), which for 24 years has consistently produced outstanding trainees as the program has evolved along with Biomedical Informatics (BMI) itself, successfully bringing computation, mathematics, statistics, modeling, data- driven inference and decision-making and advances in cognitive informatics to bear on biomedical problems. With this renewal we will further expand our program to explore and exploit the synergies between BMI and Data Science (DS). Our training program will equip trainees with not only the current DS methodology, computational approaches, and statistical methods to solve BMI problems, but also solid and broad BMI foundations, enabling them to develop novel methodologies for attacking problems currently beyond our reach. Recent advances in BMI also bring to the forefront important issues that will be emphasized in our NLMTP including the need for effective communication of biomedical information to interdisciplinary audiences of clinicians, researchers and patients. We are well prepared to train graduate students and postdocs to meet BMI challenges. Our 40 training faculty are an integral part of the Texas Medical Center and have exemplary training and research records. They have trained 194 predocs and 206 postdocs over the past 10 years, and continue to be active, with 167 predocs and 93 postdocs currently in their labs. To date our faculty have disseminated their research in more than 812 publications with their predocs, and 1,736 with their postdocs. Our predoctoral trainees will have completed one year of study and have joined a lab at one of six NLMTP participating institutions before joining the NLMTP. Our postdoctoral trainees will be selected through national recruiting and from the labs of our training faculty at those institutions. NLMTP training will combine core courses and elective courses, training in the reproducibility of research, professional/career development activities, monthly meetings with experts, and interdisciplinary co-mentored research projects to engage our 9 pre- and 6 postdoctoral trainees with a range of opportunities in health care/clinical informatics, translational bioinformatics, and clinical research informatics to prepare them for a wide range of careers as the new generation of BMI professionals.

Public Health Relevance

/RELEVANCE Our NLM Training Program in Biomedical Informatics (BMI) and Data Science (DS) has, over many years, successfully brought computation, mathematics, statistics, cognitive informatics and data-driven inference and decision-making to bear on biomedical problems. Now our program will further expand to emphasize the synergies between BMI and DS, expose trainees to the multiple facets of BMI and train in communication skills with the goal of producing professionals who are not limited by a certain technique or discipline but are equipped to cross traditional boundaries with their approaches, use a range of tools and can create new ones as needed to bear on important BMI problems. Our trainees will be well prepared for a wide range of BMI careers by pursuing coursework, training in the reproducibility of research, professional/career development activities and co-mentored research projects in health care/clinical informatics, translational bioinformatics and clinical research informatics, thereby significantly impacting human health.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Continuing Education Training Grants (T15)
Project #
2T15LM007093-26
Application #
9264362
Study Section
Special Emphasis Panel (ZLM1)
Program Officer
Florance, Valerie
Project Start
1992-07-01
Project End
2022-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
26
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Rice University
Department
Biostatistics & Other Math Sci
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005
Call, Lee; Stoll, Barbara; Oosterloo, Berthe et al. (2018) Metabolomic signatures distinguish the impact of formula carbohydrates on disease outcome in a preterm piglet model of NEC. Microbiome 6:111
Emerson, Charlene H; Lopez, Christopher R; Ribes-Zamora, Albert et al. (2018) Ku DNA End-Binding Activity Promotes Repair Fidelity and Influences End-Processing During Nonhomologous End-Joining in Saccharomyces cerevisiae. Genetics 209:115-128
Roh, Soung-Hun; Stam, Nicholas J; Hryc, Corey F et al. (2018) The 3.5-Å CryoEM Structure of Nanodisc-Reconstituted Yeast Vacuolar ATPase Vo Proton Channel. Mol Cell 69:993-1004.e3
Hendryx, Emily P; Rivière, Béatrice M; Sorensen, Danny C et al. (2018) Finding representative electrocardiogram beat morphologies with CUR. J Biomed Inform 77:97-110
Chen, Han; Li, Chunyan; Zhou, Zhicheng et al. (2018) Fast-Evolving Human-Specific Neural Enhancers Are Associated with Aging-Related Diseases. Cell Syst 6:604-611.e4
Chen, Han; Li, Chunyan; Peng, Xinxin et al. (2018) A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples. Cell 173:386-399.e12
Chiang, Sharon; Vankov, Emilian R; Yeh, Hsiang J et al. (2018) Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity. PLoS One 13:e0190220
Magnotti, John F; Beauchamp, Michael S (2017) A Causal Inference Model Explains Perception of the McGurk Effect and Other Incongruent Audiovisual Speech. PLoS Comput Biol 13:e1005229
Rosengarten, Rafael D; Santhanam, Balaji; Kokosar, Janez et al. (2017) The Long Noncoding RNA Transcriptome of Dictyostelium discoideum Development. G3 (Bethesda) 7:387-398
Wilson, Stephen J; Wilkins, Angela D; Lin, Chih-Hsu et al. (2017) DISCOVERY OF FUNCTIONAL AND DISEASE PATHWAYS BY COMMUNITY DETECTION IN PROTEIN-PROTEIN INTERACTION NETWORKS. Pac Symp Biocomput 22:336-347

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