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Michael Wagner, PhD, is an associate professor in the Division of Biomedical Informatics at Cincinnati Children’s Research Foundation. Wagner’s current research interests lie in the applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification.
With graduate student Rachana Jain, Wagner is investigating machine learning-based scoring algorithms for peptide mass fingerprinting to better understand how to optimally mine mass spectrometry data to make high-confidence predictions of protein identities. The underlying computational engine for many of these problems is a massively parallel implementation of a linear programming solver (PCx) that can solve large-scale support vector regression, support vector machine and linear feasibility problems.
With Ron Elber, PhD (University of Texas, Austin), and Jarek Meller (University of Cincinnati Environmental Health), Wagner works on applications of optimization-based approaches to protein structure prediction. He is also the lead informatics investigator on the Cincinnati Rheumatic Disease Core Center Grant (Susan Thompson, PhD, PI) and on an NIH contract to build a pediatric reference fMRI database (Scott Holland, PI).
Funding support comes from grants with Elber, Thompson (Cincinnati Children’s Division of Rheumatology) and Holland (Imaging Research Center, Cincinnati Children’s).
Wagner M, Naik D. Analysis of Mass Spectrometry Data in Cancer Proteomics, in Computational Methods in Biomedical Research, Naik D, Khattree R (eds.), Chapman & Hall / CRC. 2007.
Wagner M, Meller J. Machine Learning for Bioinformatics, in Computational Methods in Biomedical Research, Naik D, Khattree R (eds.), Chapman & Hall / CRC. 2007.
Michael Wagner, PhD
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