Biomedical Informatics

Michael Wagner, PhD

Title

Faculty Liaison

Appointment

Associate Professor of Pediatrics, University of Cincinnati College of Medicine

Email

michael.wagner@cchmc.org

Phone

513-636-2935

Fax

513-636-2056

Bio

Michael Wagner, PhD, works on applications of machine learning techniques to bioinformatics problems such as protein structure prediction, disease classification and protein identification. His research lab currently 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), which can solve large-scale support vector regression, support vector machine and linear feasibility problems. Dr. Wagner also is involved in collaborations to perform genome-wide association studies, where his work has concentrated on developing an adequate, rapid data flow infrastructure that includes parallelized genotype calling algorithms.

Credentials

Dipl. Wi-Ing.: Universitaet Karlsruhe, Germany, 1995

MS: Operations Research, Cornell University, Ithaca, New York, 1998.

PhD: Operations Research, Cornell University, Ithaca, New York, 2000.

Research Grants and Contracts

Title: Biomarkers for Amyotrophic Lateral Sclerosis in Active Duty Military
Sponsor: Department of Defense
PI: Millhorn, D
Dates: 01/23/2006 - 01/22/2009

Title: Bayesian Mixture Modeling of Functional Genomics Data
Sponsor: National Institutes of Health
PI: Medvedovic, M
Dates: 07/01/2006 - 06/30/2010

Title: Optimization of Structures and Networks of Proteins
Sponsor: National Institutes of Health
PI: Elber, R
Dates: 06/01/2008 - 05/31/2011

Publications, Most Recent

Jain A, Velayutham P, Wagner M, Butler DL. Accessing the tissue engineering literature: a new paradigm. Tissue Eng Part A. 2008 Mar;14(3):459-60.

McLachlan A, Borchers M, Velayutham P, Wagner M, Limbach PA. Characterizing the reproducibility of a protein profiling method for the analysis of mouse bronchoalveolar lavage fluid. Journal of proteome research. 2006 Nov;5(11):3059-65.

Wagner M, Adamczak R, Porollo A, Meller J. Linear regression models for solvent accessibility prediction in proteins. J Comput Biol. 2005 Apr;12(3):355-69.

Guo M, Wagner M, West C. Outpatient scheduling: a simulation approach. In: Ingalls RG, editor. Proceedings of the 2004 Winter Simulation Conference; 2004 Dec 5-8; Washington, DC: IEEE; 2004. p. 1981-7.

Wagner M, Naik DN, Pothen A, Kasukurti S, Devineni RR, Adam BL, et al. Computational protein biomarker prediction: a case study for prostate cancer. BMC Bioinformatics. 2004 Mar 11;5:26.

Wagner M, Meller J, Elber R. Large-scale linear programming techniques for the design of protein folding potentials. Math Program. 2004;101(2):301-18.

Wagner M, Naik D, Pothen A. Protocols for disease classification from mass spectrometry data. Proteomics. 2003 Sep;3(9):1692-8.

Porollo A, Adamczak R, Wagner M, Meller J. Maximum feasibility approach for consensus classifiers: applications to protein structure prediction. CIRAS; 2003.

Meller J, Wagner M, Elber R. Maximum feasibility guideline in the design and analysis of protein folding potentials. J Comput Chem. 2002;23:111-18.

Wagner M, Todd M. Least-change quasi-Newton updates for equality constrained optimization. Math Program. 2000;87:317-50.

Czyzyk J, Mehrotra S, Wagner M, Wright S. PCx: an interior-point code for linear programming. Optim Methods and Softw. 1999;12:397-430.

Coleman T, Czyzyk J, Sun C, Wagner M, Wright S. pPCx: parallel software for linear programming. Proceedings of the 8th SIAM Conference on Parallel Processing in Scientific Computing; Minneapolis, MN; 1997.