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.
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. ! !
|Ye, Zhan; Mayer, John; Ivacic, Lynn et al. (2015) Phenome-wide association studies (PheWASs) for functional variants. Eur J Hum Genet 23:523-9|
|Turner, Leslie M; White, Michael A; Tautz, Diethard et al. (2014) Genomic networks of hybrid sterility. PLoS Genet 10:e1004162|
|Sherman, Natasha A; Victorine, Anna; Wang, Richard J et al. (2014) Interspecific tests of allelism reveal the evolutionary timing and pattern of accumulation of reproductive isolation mutations. PLoS Genet 10:e1004623|
|Chasman, Deborah; Gancarz, Brandi; Hao, Linhui et al. (2014) Inferring host gene subnetworks involved in viral replication. PLoS Comput Biol 10:e1003626|
|Kim, Won Hwa; Singh, Vikas; Chung, Moo K et al. (2014) Multi-resolutional shape features via non-Euclidean wavelets: applications to statistical analysis of cortical thickness. Neuroimage 93 Pt 1:107-23|
|Eng, Kevin H; Hanlon, Bret M (2014) Discrete mixture modeling to address genetic heterogeneity in time-to-event regression. Bioinformatics 30:1690-7|
|Timm, Collin; Akpinar, Fulya; Yin, John (2014) Quantitative characterization of defective virus emergence by deep sequencing. J Virol 88:2623-32|
|Ithapu, Vamsi; Singh, Vikas; Lindner, Christopher et al. (2014) Extracting and summarizing white matter hyperintensities using supervised segmentation methods in Alzheimer's disease risk and aging studies. Hum Brain Mapp 35:4219-35|
|Hebbring, Scott J (2014) The challenges, advantages and future of phenome-wide association studies. Immunology 141:157-65|
|Shoenbill, Kimberly; Fost, Norman; Tachinardi, Umberto et al. (2014) Genetic data and electronic health records: a discussion of ethical, logistical and technological considerations. J Am Med Inform Assoc 21:171-80|
Showing the most recent 10 out of 121 publications