The University of Wisconsin's (UW) Computation and Informatics in Biology and Medicine Training Program (CIBM) is proposing to help train the next generation of computational scientists in health and disease research. We will extend our prior collaboration with the Marshfield Clinical Research Foundation to also fully integrate our program with UW's Institute for Clinical and Translational Research (ICTR). The interplay between computational and statistical methods and the biomedical sciences continues to expand rapidly. Both computer modeling and informatics now play a key role in both biology and medicine, and our researchers have been developing novel state-of-the-art algorithms for the analysis of molecular and clinical research data. The organizations involved in CIBM are strong. UW has a total externally funded research portfolio of $1B/year and is a leading research university. A good fraction of this research is in the biomedical sciences and related areas, and a number of departments involved in CIBM are regularly in the 'top ten' lists in various polls, including Computer Sciences, Genetics, Biochemistry, Statistics, Chemical and Biological Engineering, and others. We will continue to build on these strengths as we move more to health and disease-related research training. The strength of CIBM has been to bring strong algorithmic thinking from computer scientists, statisticians, and informaticists to projects and domains where challenging problems lie. We will continue to use this model going forward. We have demonstrated strong success in recruiting and training graduate students and postdoctoral fellows. This is evidenced by the number of new faculty we have produced in the biomedical informatics area, the development of new externally funded multi-disciplinary research projects, and our involvement in minority recruitment and placement. To buttress these new training endeavors we have added new members to our CIBM management committee, including Prof. Eneida Mendonga, a new faculty member in Clinical Research Informatics at UW's ICTR, and Dr. Amit Acharya, a dental informaticist from the Marshfield Clinic. Our curriculum now includes courses closely connected to clinical and translational research, and we propose to include new opportunities for postdoctoral dental informatics research. The program will be well positioned to serve the country with highly trained researchers in biomedical informatics.

Public Health Relevance

As more information becomes available on medical outcomes and on genetic factors in health and disease it becomes more imperative to properly collect, store, and analyze these data to improve clinical practices. Researchers and faculty are needed that are expert in the areas of computer science and information management as they apply to translational research. We are proposing a continuation of UW's Computation and Informatics in Biology and Medicine Training Program to help achieve this mission.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Continuing Education Training Grants (T15)
Project #
4T15LM007359-15
Application #
9087330
Study Section
Special Emphasis Panel (ZLM1)
Program Officer
Florance, Valerie
Project Start
2002-07-01
Project End
2017-06-30
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
15
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Biochemistry
Type
Earth Sciences/Resources
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Overmyer, Katherine A; Tyanova, Stefka; Hebert, Alex S et al. (2018) Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice. Nat Protoc 13:293-306
Huang, Xiayuan; Elston, Robert C; Rosa, Guilherme J et al. (2018) Applying family analyses to electronic health records to facilitate genetic research. Bioinformatics 34:635-642
Schaffer, Leah V; Rensvold, Jarred W; Shortreed, Michael R et al. (2018) Identification and Quantification of Murine Mitochondrial Proteoforms Using an Integrated Top-Down and Intact-Mass Strategy. J Proteome Res 17:3526-3536
Schaffer, Leah V; Shortreed, Michael R; Cesnik, Anthony J et al. (2018) Expanding Proteoform Identifications in Top-Down Proteomic Analyses by Constructing Proteoform Families. Anal Chem 90:1325-1333
Cesnik, Anthony J; Shortreed, Michael R; Schaffer, Leah V et al. (2018) Proteoform Suite: Software for Constructing, Quantifying, and Visualizing Proteoform Families. J Proteome Res 17:568-578
Romano, Kymberleigh A; Dill-McFarland, Kimberly A; Kasahara, Kazuyuki et al. (2018) Fecal Aliquot Straw Technique (FAST) allows for easy and reproducible subsampling: assessing interpersonal variation in trimethylamine-N-oxide (TMAO) accumulation. Microbiome 6:91
Hong, Jaeyoung; Hatchell, Kathryn E; Bradfield, Jonathan P et al. (2018) Transethnic Evaluation Identifies Low-Frequency Loci Associated With 25-Hydroxyvitamin D Concentrations. J Clin Endocrinol Metab 103:1380-1392
Darst, Burcu; Engelman, Corinne D; Tian, Ye et al. (2018) Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20. BMC Genet 19:76
Bastarache, Lisa; Hughey, Jacob J; Hebbring, Scott et al. (2018) Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359:1233-1239
Engelman, Corinne D; Darst, Burcu F; Bilgel, Murat et al. (2018) The effect of rare variants in TREM2 and PLD3 on longitudinal cognitive function in the Wisconsin Registry for Alzheimer's Prevention. Neurobiol Aging 66:177.e1-177.e5

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