391 Joshi Research Center
3640 Colonel Glenn Hwy
Dayton, OH 45435-0001
Phone:  (937) 775-5110
Fax: (937) 775-5133

Michael L. Raymer graduated in 1991 from Colorado State University with a B.S. degree in Computer Science. For the following two years, he worked at the Los Alamos National Laboratory, first as a research assistant, and later as a technical staff member. In 1993 he left Los Alamos to pursue graduate studies at Michigan State University, where he obtained an M.S. Degree in Computer Science in 1995, and a Ph.D. Degree in Computer Science and Engineering in 2000. His dissertation work was directed at developing algorithms to analyze and predict interactions between proteins and water molecules. He is currently an associate professor of computer science and engineering at Wright State University, a member of the faculty of the Biomedical Sciences Program, and co-founder and Senior Systems Engineer for Forensic Bioinformatic Services, Inc. Michael's research group at Wright State (the Bioinformatics Research Group, or BiRG) develops algorithms that identify patterns in biological data sets, and exploit these patterns to predict the behavior of biological systems. Many of these research projects are oriented towards improving the process of pharmaceutical drug discovery. A leader in bioinformatics education, he is the principal coordinator of the undergraduate program in bioinformatics at Wright State University, one of the first such programs in the nation to be funded by the National Science Foundation. He is co-author of the textbook Fundamental Concepts of Bioinformatics, the first undergraduate textbook in bioinformatics, available from Benjamin Cummings publishers. Since joining the faculty at Wright State, Michael and his students have published more than 45 peer-reviewed papers, and have been cited more than 500 times.

Details:

• Courses
• Full CV
• Forensic Bioinformatics Services

• A Genetic Optimization Approach for Isolating Translational Efficiency Bias
• Automated Isolation of Translational Efficiency Bias that Resists the Confounding Effect of GC(AT)-Content
• Improving Remote Homology Detection Using Sequence Properties and Position Specific Scoring Matrices
• A comparison of codon usage trends in prokaryotes
• Characterization of 1H NMR spectroscopic data and the generation of synthetic validation sets
• A web-based framework for the distribution of bioinformatics techniques: Orthogonal projection on latent structures and principal component analysis implemented as RESTful web services
• Do amino acid biosynthetic costs constrain protein evolution in Saccharomyces cerevisiae?
• Gaussian binning: a new kernel-based method for processing NMR spectroscopic data for metabolomics
• Gaussian binning for processing NMR spectroscopic data for metabolomics
• Comparison of Statistical Techniques for the Analysis of Metabolic Toxicological Data Derived from NMR Spectroscopy
• A Proposed Statistical Protocol for the Analysis of Metabolic Toxicological Data Derived from NMR Spectroscopy
• A Multi-Objective Genetic Algorithm that Employs a Hybrid Approach for Isolating Codon Usage Bias Indicative of Translational Efficiency
• A National Model for Engineering Mathematics Education
• ALU elements as time series genomic data
• Protein structure probing through limited proteolysis
• Redefining Engineering Mathematics Education at Wright State University
• Was the Shawnee War Chief Blue Jacket a Caucasian?
• An Investigation of Codon Usage Bias Including Visualization and Quantification in Organisms Exhibiting Multiple Biases
• Isolation and visualization of codon usage biases
• Amino Acid Cost and Codon-Usage Biases in 6 Prokaryotic Genomes: A Whole-Genome Analysis
• Assessing the Implications for Close Relatives in the Event of Similar but Nonmatching DNA Profiles
• Book Review: Evolutionary Computation in Bioinformatics
• The Wright State Model for Engineering Mathematics Education: A Nationwide Adoption, Assessment and Evaluation
• Balanced Accuracy for Feature Subset Selection with Genetic Algorithms
• Work in progress - the WSU model for engineering mathematics education
• The WSU Model for Engineering Mathematics Education
• Stochastic model of protease-ligand reactions
• GA-facilitated classifier optimization with varying similarity measures
• Empirical Analysis of the STR profiles resulting from conceptual mixtures
• Systematic differences in electropherogram peak heights reported by different version of the Genescan® software
• Bioinformatics: Where Biology meets Computer Science
• Commentary on: Budowle B, Shea B, Niezgoda S, Chakraborty R. CODIS STR loci data from 41 sample populations. J. Forensic Sci 2001; 46:453-489
• Rethinking Engineering Mathematics Education: A Model for Increased Retention, Motivation and Success in Engineering.
• GA-Facilitated Knowledge Discovery and Pattern Recognition Optimization Applied to the Biochemistry of Protein Solvation
• On the Relative Efficacies of *cGA Variants for Intrinsic Evolvable Hardware: Population, Mutation, and Random Immigrants
• Knowledge Discovery in Large Biological Data Sets Using Hybrid Classifier/Evolutionary Algorithms
• Indexing Genomic Databases
• Evaluating forensic DNA evidence: Essential elements of a competent defense review
• Knowledge Discovery in Biological Datasets Using a Hybrid Bayes Classifier/Evolutionary Algorithm
• Crossing the interdisciplinary barrier: A baccalaureate computer science option in bioinformatics
• Antidiabetic and antimalarial biguanide drugs are metal-interactive antiproteolytic agents
• Identifying patterns in DNA change
• Breaking open the black box: How to review the electronic data
• An interdisciplinary undergraduate bioinformatics curriculum for biological scientists
• GA-facilitated cosine classifier optimization with application to the biochemistry of protein-water interactions
• A Proposed Undergraduate Bioinformatics Curriculum for Computer Scientists
• Knowledge Discovery in Biological Datasets Using a Hybrid Bayes Classifier/Evolutionary Algorithm
• PocketMol: A Molecular Visualization Tool for the PocketPC
• Profile Combinatorics for Fragment Selection in Comparative Protein Structure Modeling
• Dimensionality Reduction Using Genetic Algorithms
• Predicting Conserved Water-Mediated and Polar Ligand Interactions in Proteins Using a K-nearest-neighbors Genetic Algorithm
• Simultaneous Feature Scaling and Selection Using a Genetic Algorithm
• Genetic Programming for Improved Data Mining – Application to the Biochemistry of Protein Interactions

• Identification of Biomarkers of Toxicity and Downstream Outcomes
• Forensic DNA analysis and statistical interpretation
• Characterization and Analysis of Codon Usage Bias
• Protein modification reactivity analysis (MRAN)