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Michael Wagner, PhD, is an associate professor in the Division of Biomedical Informatics at Cincinnati Children’s Research Foundation within the University of Cincinnati College of Medicine. 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).
Sroka MC, Vannest J, Maloney TC, Horowitz-Kraus T, Byars AW, et al. Relationship between receptive vocabulary and the neural substrates for story processing in preschoolers. Brain Imaging Behav. 2015 Mar;9(1):43-55.
Kaiser D, Leach J, Vannest J, Schapiro M, Holland S. Unanticipated findings in pediatric neuroimaging research: prevalence of abnormalities and process for reporting and clinical follow-up. Brain Imaging Behav. 2015 Mar;9(1):32-42.
Horowitz-Kraus T, Grainger M, DiFrancesco M, Vannest J, Holland SK. Right is not always wrong: DTI and fMRI evidence for the reliance of reading comprehension on language-comprehension networks in the right hemisphere. Brain Imaging Behav. 2015 Mar;9(1):19-31.
Schmithorst VJ, Vannest J, Lee G, Hernandez-Garcia L, Plante E, et al. Evidence that neurovascular coupling underlying the BOLD effect increases with age during childhood. Hum Brain Mapp. 2015 Jan;36(1):1-15.
Vannest J, Rajagopal A, Cicchino ND, Franks-Henry J, Simpson SM, et al. Factors determining success of awake and asleep magnetic resonance imaging scans in nonsedated children. Neuropediatrics. 2014 Dec;45(6):370-7.
Biesiada J, Chidambaran V, Wagner M, Zhang X, Martin LJ, et al. Genetic risk signatures of opioid-induced respiratory depression following pediatric tonsillectomy. Pharmacogenomics. 2014 Nov;15(14):1749-1762.
Patel ZH, Kottyan LC, Lazaro S, Williams MS, Ledbetter DH, et al. The struggle to find reliable results in exome sequencing data: filtering out Mendelian errors. Front Genet. 2014 Feb 12;5:16.
Morrow AL, Lagomarcino AJ, Schibler KR, Taft DH, Yu Z, et al. Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants. Microbiome. 2013 Apr 16;1(1):13.
Namjou B, Keddache M, Marsolo K, Wagner M, Lingren T, et al. EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children. Front G. 2013 Dec 3;4:268.
Thompson SD, Marion MC, Sudman M, Ryan M, Tsoras M, et al. Genome-wide association analysis of juvenile idiopathic arthritis identifies a new susceptibility locus at chromosomal region 3q13. Arthritis Rheum. 2012 Aug;64(8):2781-91.
Huang SH, Mo D, Meller J, Wagner M. Identifying a small set of marker genes using minimum expected cost of misclassification. Artif Intell Med. 2012 May;55(1):51-9.
Data Storage and Access Management. (2012). In Kouril M, Hunt N, Wagner M (Ed.), Pediatric Biomedical Informatics: Computer Applications in Pediatric Research (pp 43-61). New York: Springer.
From SNP Genotyping to Improved Pediatric Healthcare. (2012). In Biesiada J, Sadhasivam S, Wagner M, Meller J (Ed.), Pediatric Biomedical Informatics: Computer Applications in Pediatric Research (pp 359-378). New York: Springer.
Thompson SD, Sudman M, Ramos PS, Marion MC, Ryan M, et al. The susceptibility loci juvenile idiopathic arthritis shares with other autoimmune diseases extend to PTPN2, COG6, and ANGPT1. Arthritis Rheum. 2010 Nov;62(11):3265-76.
Freudenberg JM, Sivaganesan S, Wagner M, Medvedovic M. A semi-parametric Bayesian model for unsupervised differential co-expression analysis. BMC Bioinformatics. 2010 May 7;11:234.
Jain R, Wagner M. Kolmogorov-Smirnov scores and intrinsic mass tolerances for peptide mass fingerprinting. J Proteome Res. 2010 Feb 5;9(2):737-42.
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.
Analysis of Mass Spectrometry Data in Cancer Proteomics. (2008). In M Wagner, DN Naik, (Ed.), Computational Methods in Biomedical Research. Boca Raton, FL: Chapman & Hall.
Machine Learning Techniques for Bioinformatics: Fundamentals and Applications. (2008). In M Wagner, J Meller (Ed.), Computational Methods in Biomedical Research (pp. 45-76). Boca Raton, FL: Chapman & Hall.
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. J Proteome Res. 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.
Wagner M, Naik DN, Pothen A, Kasukurti S, Devineni RR, et al. Computational protein biomarker prediction: a case study for prostate cancer. BMC Bioinformatics. 2004 Mar 11;5:26.
McConnell KB, Wagner M, Urbina E, Daniels S, Helmicki A, et al. Central aortic pressure wave changes with sleep stage and disordered breathing in children estimated by application of an arterial transfer function to peripheral blood pressure. Conf Proc IEEE Eng Med Biol Soc. 2004;5:3864-6.
Wagner M, Meller J, Elber R. Large-Scale Linear Programming Techniques for the Design of Protein Folding Potentials. Math Program B. 2004; 101(2):301-318.
Wagner M, Naik D, Pothen A. Protocols for disease classification from mass spectrometry data. Proteomics. 2003 Sep;3(9):1692-8.
Meller J, Wagner M, Elber R. Maximum feasibility guideline in the design and analysis of protein folding potentials. J Comput Chem. 2002 Jan 15;23(1):111-8.
Wagner M, Todd MJ. Least-change Quasi-Newton Updates for Equality-Constrained Optimization. Math Program. 2000; 87:317-350.
Czyzyk J, Mehrotra S, Wagner M, Wright S. PCx: An Interior-Point Code for Linear Programming. Optimization methods & software. 1999; 12:397-430.
Michael Wagner, PhD
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