Michael L. Raymer, Ph.D.

Wright State University Professor, Department of Computer Science and Engineering
Wright State University
Dayton, OH 45435-0001
http://birg.cs.wright.edu/mraymer

Brief Bio

Michael L. Raymer graduated in 1991 from Colorado State University with a B.S. degree in Computer Science. He earned an M.S. degree in Computer Science from Michigan State University in 1995 and a Ph.D. degree in Computer Science from Michigan State University in 2000. While at Michigan State, his research crossed the boundaries between computer science and biochemistry. He worked in the Protein Structural Analysis and Design Laboratory, directed by Dr. Leslie Kuhn, and also in the Genetic Algorithms Research and Applications laboratory, directed by Dr. Bill Punch and Dr. Erik Goodman. His work in both labs was directed at developing machine learning algorithms to analyze and predict interactions between proteins and water molecules. He currently holds the rank of Professor in the Department of Computer Science and Engineering at Wright State University and is a member of the faculty of the Biomedical Sciences Ph.D. program and the Environmental Sciences Ph.D. program. In his career at Wright State, Dr. Raymer has served the university in the positions of Graduate Program Director, Associate Chair, Interim Chair, Department Chair, Associate Dean, and Interim Dean. Dr. Raymer co-developed the undergraduate program in bioinformatics at Wright State University, the first such program 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. Dr. Raymer's research interests include machine learning, deep learning, topological data analysis, dimensionality reduction, feature engineering, and pattern recognition. Michael and his students have published more than 80 peer-reviewed papers, and have been cited more than 3400 times, including a citation by Justice Samuel Alito in a ruling of the United States Supreme Court related to the use of DNA evidence in the courtroom. His H-index is currently 26. Additionally, Dr. Raymer provides consulting services in the areas of machine learning and data science, and is co-founder and Senior Systems Engineer for Forensic Bioinformatic Services, Inc. (FBS).

Education

Institution Major, Degree Year
Michigan State University Computer Science, Ph.D. 2000
Michigan State University Computer Science, M.S. 1995
Colorado State University Computer Science, B.S. 1991

Academic Experience

Institution Position Dates
Wright State University Interim Dean, College of Engineering and Computer Science 2022–2023
Wright State University Chair, Department of Computer Science and Engineering 2021–2023
Wright State University Interim Chair, Department of Computer Science and Engineering 2021
Wright State University Associate Chair, Department of Computer Science and Engineering 2020–2021
Wright State University Graduate Program Director, Department of Computer Science and Engineering 2015–2020
Wright State University Associate Dean for Research and Graduate Studies, College of Engineering and Computer Science 2013–2015
Wright State University Professor, Department of Computer Science and Engineering 2013–
Wright State University Full member of the Biomedical Sciences Ph.D. Program 2003–
Wright State University Full member of the Environmental Sciences Ph.D. Program 2005–
Wright State University Full member of the Graduate Faculty 2001–
Wright State University Associate Professor, Department of Computer Science and Engineering 2006–2013
Wright State University Assistant Professor, Department of Computer Science and Engineering 2000–2006
Michigan State University Graduate Research Assistant, Department of Biochemistry 1994–2000
Michigan State University Graduate Research Assistant, Department of Computer Science 1993–1994

Professional and Academic Honors

Title of Award Granting Organization Date
Trustees' Award Wright State University 2022
Robert J. Kegerreis Distinguished Professor of Teaching Wright State University 2020-2023
Excellence in Teaching Award College of Engineering and Computer Science, Wright State University 2015-2016
Outstanding Teaching Nominee College of Engineering and Computer Science, Wright State University 2014-2015
Outstanding Engineers and Scientists Award Affiliate Societies Council of Dayton 2013
Outstanding Service College of Engineering and Computer Science, Wright State University 2012-2013
Outstanding Faculty Member College of Engineering and Computer Science, Wright State University 2009-2010
Excellence in Teaching Award College of Engineering and Computer Science, Wright State University 2008-2009
Early Career Achievement Award College of Engineering and Computer Science, Wright State University 2002-2003
Outstanding Teaching Nominee College of Engineering and Computer Science, Wright State University 2002-2003
Outstanding Teaching Nominee College of Engineering and Computer Science, Wright State University 2001-2002
Outstanding Teaching Nominee College of Engineering and Computer Science, Wright State University 2000-2001
Ohio Teaching Excellence Program Wright State University 2002-2003
Finn Wold Travel Award The Protein Society 1998
Student Travel Grant American Crystallographic Association 1995
DeVlieg Fellowship Michigan State University 1993
Distinguished Performance Award Los Alamos National Laboratory 1992
Summa Cum Laude Colorado State University 1991
Mohilner Scholarship Colorado State University 1990
President’s Scholarship Colorado State University 1987
Boettcher Foundation Scholarship The Boettcher Foundation 1987-1991

Professional Memberships

Association Date
International Society for Computational Biology 2008–
IEEE Computer Society 2002–
Phi Beta Kappa National Honor Society 1991–

Other Professional Experience

Organization Position Dates
Los Alamos National Laboratory Technical Staff Member 1992–1996
Los Alamos National Laboratory Staff Research Assistant 1991–1992
Reynolds Electrical and Engineering Company Programmer 1990

External Grants and Contracts

Printed Scholarship

Books and Book Chapters

  1. Doom, T., Gallagher, J. C., Raymer, M., and Timmerman, K. (2019). The Rising TIDE of Wright State University: Context, Connections, and Consequences. In K. Mack, K. Winter, and M. Soto (Eds.), Culturally Responsive Strategies for Reforming STEM Higher Education (First ed., pp. 201–216). Bingley, UK: Emerald Publishing.
  2. D. Krane and M. Raymer (2003), Fundamental Concepts in Bioinformatics, Benjamin Cummings, Jan. 2003. ISBN 0-8053-4633-3

Technical Articles in Peer-Reviewed Journals

  1. Cara Leigh Widmer, Md Kamruzzaman Sarker, Srikanth Nadella, Joshua Fiechter, Ion Juvina, Brandon Minnery, Pascal Hitzler, Joshua Schwartz, Michael Raymer (2023). “Towards human-compatible XAI: Explaining data differentials with concept induction over background knowledge” Journal of Web Semantics, Volume 79, 2023, 100807, ISSN 1570-8268, https://doi.org/10.1016/j.websem.2023.100807.
  2. Yap, X. H., Raymer, M. L. (2022). “Toxicity Prediction using Locally-Sensitive Deep Learner” Computational Toxicology, 21, 100210. https://doi.org/10.1016/j.comtox.2021.100210
  3. Yap, X. H., Raymer, M. L. (2021. “Multi-label Classification and Label Dependence in in Silco Toxicity Prediction” Toxicology in Vitro, 74, p. 105157. https://doi.org/10.1016/j.tiv.2021.105157
  4. Yoo, S., Shi, Z., Wen, B., Kho, S., Pan, R., Feng, H., Chen, H., Carlsson, A., Edén, P., Ma, W., Raymer, M., Maier, E. J., Tezak, Z., Johanson, E., Hinton, D., Rodriguez, H., Zhu, J., Boja, E., Wang, P., & Zhang, B. (2021). “A community effort to identify and correct mislabeled samples in proteogenomic studies.” Patterns, 2(5), 100245. https://doi.org/10.1016/j.patter.2021.100245
  5. Sibomana, I., Foose, D. P., Raymer, M. L., Reo, N. V, Karl, J. P., Berryman, C. E., Young, A. J., Pasiakos, S. M., & Mauzy, C. A. (2021). “Urinary Metabolites as Predictors of Acute Mountain Sickness Severity” Frontiers in Physiology, 12, pp. 1502-1512. https://www.frontiersin.org/article/10.3389/fphys.2021.709804
  6. Maack, R. G. C., Raymer, M. L., Wischgoll, T., Hagen, H., & Gillmann, C. (2021). “A framework for uncertainty-aware visual analytics of proteins.” Computers & Graphics, 98, 293–305. https://doi.org/10.1016/j.cag.2021.05.011
  7. S. Sakaram, M. Craig, N. Hill, A. Aljagthmi, C. Garrido, O. Paliy, M. Bottomley, M. Raymer and M. Kadakia, (2018). “Identifcation of novel ΔNp63α-regulated miRNAs using an optimized small RNA-Seq analysis pipeline.” Nature Scientific Reports, 8(10069) DOI:10.1038/s41598-018-28168-5
  8. I. Sibomana, N. J. DelRaso, D. Mattie, M. Raymer, & N. Reo, (2017). “Furosemide enhances the sensitivity of urinary metabolomics for assessment of kidney function.” Metabolomics, 13(3), 24. https://doi.org/10.1007/s11306-017-1162-6
  9. DelRaso, N., Harville, D., Chamberlain, M., Anderson, P., Sibomana, I., Raymer, M., & Reo, N. (2016). “Urinary Metabolite Profiles May be Predictive of Cognitive Performance under Conditions of Acute Sleep Deprivation.” Current Metabolomics, 4(1), 63–77. April, 2016.
  10. Shankar, V., Homer, D., Rigsbee, L., Khamis, H. J., Michail, S., Raymer, M., Paliy, O. (2015). “The networks of human gut microbe-metabolite associations are different between health and irritable bowel syndrome.” The ISME Journal. 9:1899-1903, http://doi.org/10.1038/ismej.2014.258. August, 2015. Impact factor: 9.267.
  11. Shankar, V., Agans, R., Holmes, B., Raymer, M., & Paliy, O. (2013). “Do gut microbial communities differ in pediatric IBS and health?” Gut Microbes, 4(4), pp. 347-352. doi:10.4161/gmic.24827
  12. Ferguson, C. D., Blum, M. J., Raymer, M. L., Eackles, M. S., & Krane, D. E. (2013). “Population structure , multiple paternity , and long-distance transport of spermatozoa in the freshwater mussel Lampsilis cardium (Bivalvia : Unionidae).” Freshwater Science, 32(1), pp. 267-282. doi:10.1899/12-028.1
  13. Raiford, D. W., Heizer, E. M., Miller, R. V., Doom, T. E., Raymer, M. L., & Krane, D. E. (2012). “Metabolic and Translational Efficiency in Microbial Organisms,” Journal of molecular evolution. Vol. 74, no. 3, pp. 206-212, doi:10.1007/s00239-012-9500-9.
  14. D. Paoletti, D. Krane, T. Doom, and M. Raymer (2012), “Inferring the Number of Contributors to Mixed DNA Profiles.” IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). Vol. 9, no. 1, Jan.-Feb 2012, 113-122, doi: 10.1109/TCBB.2011.76.
  15. E. Heizer, M. Raymer and D. Krane (2011). “Amino Acid Biosynthetic Cost and Protein Conservation,” Journal of Molecular Evolution, vol. 72, nos 5-6, June 2011, pp. 466-473, DOI: 10.1007/s00239-011-9445-4.
  16. D. Raiford, D. Krane, T. Doom, M. Raymer (2011), "A Genetic Optimization Approach for Isolating Translational Efficiency Bias," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 2, pp. 342-352, Mar./Apr. 2011, doi:10.1109/TCBB.2009.24.
  17. P. Anderson, S. Sahoo, A. Manjunatha, A. Ranabahu, N. Delraso, N. Reo, A. Sheth and M. Raymer (2011). “Dynamic Adaptive Binning: An improved quantification technique for NMR spectroscopic data.” Metabolomics. vol. 7, no. 2, 179-190, DOI: 10.1007/s11306-010-0242-7.
  18. D. Mahle, P. Anderson, N. DelRaso, M. Raymer, A. Neuforth, and N. Reo (2011). “A Generalized Model for Metabolomic Analysis: Application to Dose and Time Dependent Toxicity.” Metabolomics, vol. 7, no. 2, 206-216, doi:10.1007/s11306-010-0246-3.
  19. D. Raiford, D. Krane, T. Doom, M. Raymer (2010), "Automated Isolation of Translational Efficiency Bias That Resists the Confounding Effect of GC(AT)-Content," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 2, pp. 238-250, Apr.-June 2010, doi:10.1109/TCBB.2008.65
  20. P. Anderson, M. Raymer, B. Kelly, N. Reo, N. DelRaso, & T. Doom (2009). “Characterization of 1H NMR spectroscopic data and the generation of synthetic validation sets,” Bioinformatics,25, Nov 15, 2009, 2992-3000.
  21. P. Anderson, N. Reo, N. DelRaso, T. Doom, and M. Raymer (2008), “Gaussian binning: A new kernel-based method for processing NMR spectroscopic data for metabolomics,” Metabolomics, 4:3, September, 2008.
  22. D. Raiford, E. Heizer, R. Miller, H. Akashi, M. Raymer, and D. Krane (2008), “Do amino acid biosynthetic costs constrain protein evolution in Saccharomyces cerevisiae?” Journal of Molecular Evolution, 67:6, 621-30, December, 2008.
  23. C. Rowland, R. V. Van Trees, M. Taylor, M. Raymer and D. Krane (2006), “Was the Shawnee War Chief Blue Jacket a Caucasian?” Ohio Journal of Science, 106:4, 2006.
  24. E. Heizer, D. Raiford, M. Raymer, T. Doom, R. Miller and D. Krane (2006), “Amino Acid Cost and Codon Usage Biases in Six Prokaryotic Genomes: A Whole Genome Analysis.” Molecular Biology and Evolution, June 2006, 23:9, 1670–1680.
  25. D. Paoletti, T. Doom, M. Raymer, and D. Krane. “Assesing the implications for close relatives in the event of similar but non-matching DNA profiles.” Jurimetrics , 46:2, Winter, 2006, 161–175.
  26. D. Paoletti, T. Doom, C. Krane, M. Raymer, and D. Krane (2005), “Empirical Analysis of the STR profiles resulting from conceptual mixtures.” Journal of Forensic Sciences, 50:6, November 2005, 1361–1366.
  27. J. Gilder, S. Ford, T. Doom, M. Raymer, and D. Krane (2004), “Systematic differences in electropherogram peak heights reported by different version of the Genescan® software.” Journal of Forensic Science, 49:1, January 2004, 92–85.
  28. D. Sweeney, M. Raymer, and T. Lockwood (2003), “Antidiabetic and antimalarial biguanide drugs are metal-interactive antiproteolytic agents.” Biochemical Pharmacology, 66:4, 663-677.
  29. T. Doom, M. Raymer, D. Krane, and O. Garcia (2003), “Crossing the interdisciplinary barrier: A baccalaureate computer science option in bioinformatics.” IEEE Transactions on Education, 46:3, 387–393, August, 2003.
  30. M. Raymer, T. Doom, A. Kuhn, and W. Punch (2003), “Knowledge Discovery in Biological Datasets Using a Hybrid Bayes Classifier/Evolutionary Algorithm.” IEEE Transactions on Systems, Man, and Cybernetics, 33:5, 802–813, October, 2003.
  31. M. Raymer, W. Punch, E. Goodman, L. Kuhn, and A. Jain (2000), “Dimensionality Reduction Using Genetic Algorithms.” IEEE Transactions on Evolutionary Computation, 4, 164–171.
  32. M. Raymer, P. Sanschagrin, W. Punch, S. Venkataraman, E. Goodman, and L. Kuhn (1997), “Predicting Conserved Water-Mediated and Polar Ligand Interactions in Proteins Using a K-nearest-neighbors Genetic Algorithm.” Journal of Molecular Biology, 265, 445–464.

Papers Published in Peer-Reviewed Conference Proceedings

  1. J. W. Ross, M. L. Raymer, B. D. Rigling and V. J. Velten (2022), “Template Matching Study on Synthetic Aperture RADAR and Synthetic Aperture LADAR Imagery,” 2022 IEEE Research and Applications of Photonics in Defense Conference (RAPID), pp. 1-2, doi: 10.1109/RAPID54472.2022.9911590.
  2. Alambo, A., Banerjee, T., Krishnaprasad, T., Raymer, M. (2022), “Entity-driven Fact-aware Abstractive Summarization of Biomedical Literature” Accepted to the 26th International Conference on Pattern Recognition (ICPR) 2022, Montreal, Quebec.
  3. Alambo, A., Lohstroh, C., Madaus, E., Padhee, S., Foster, B., Banerjee, T., Thirunarayan, K., & Raymer, M. (2020). “Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles.” 2020 IEEE International Conference on Big Data (Big Data), 591–596. https://doi.org/10.1109/BigData50022.2020.9378403
  4. Md K. Sarker, J. Schwartz, P. Hitzler, L. Zhou, S. Nadella, B. Minnery, I. Juvina, M. L. Raymer, W. R. Aue (2020), “Wikipedia Knowledge Graph for Explainable AI.” In: B. Villazón-Terrazas, F. Ortiz-Rodríguez, S. M. Tiwari, S. K. Shandilya (eds.), Knowledge Graphs and Semantic Web. Second Iberoamerican Conference and First Indo-American Conference, KGSWC 2020, Mérida, Mexico, November 26–27, 2020, Communications in Computer and Information Science, 1232, Springer, Heidelberg, 2020, pp. 72-87.
  5. Z. A. Daniels, L. D. Frank, C. J. Menart, M. Raymer, P. Hitzler, “A framework for explainable deep neural models using external knowledge graphs.” Proc. SPIE 11413, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II, 114131C (21 April 2020); https://doi.org/10.1117/12.2558083
  6. H. Yalamanchili, S. J. Kho, and M. Raymer, “Latent Dirichlet Allocation for Classification using Gene Expression Data”. Proceedings of the IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE 17). DOI 10.1109/BIBE.2017.00014
  7. Kho, S. J., Yalamanchili, H., M. Raymer and A. Sheth, “A Novel Approach for Classifying Gene Expression Data using Topic Modeling”. Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB '17), Boston, Massachusetts, August 20 - 23, 2017. https://doi.org/10.1145/3107411.3107483
  8. N. Xie, M. Sarker, D. Doran, P. Hitzler and M. Raymer, “Relating Input Concepts to Convolutional Neural Network Decisions”. Advances in Neural Information Processing Systems 30 (NIPS 2017). Long Beach, CA, Dec. 04-09, 2017. http://www.interpretable-ml.org/nips2017workshop/papers/11.pdf
  9. M. Sarker, N. Xie, D. Doran, M. Raymer, and P. Hitzler, “Explaining Trained Neural Networks with Semantic Web Technologies: First Steps.”, Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2017), London, UK, July 17-18, 2017. http://ceur-ws.org/Vol-2003/NeSy17_paper4.pdf
  10. O. Mendoza-Schrock, M. Rizki, M. Raymer, and V. Velten. “Manifold Transfer Subspace Learning (MTSL) for High Dimensional Data-Applications to Handwritten Digits and Health Informatics.” Proceedings of The 21th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'17) Las Vegas (NV), July 17-20, 2017.
  11. K. Timmerman, M. Raymer, J. Gallagher, and T. Doom. “Educational methods for inverted-lecture Computer Science classrooms to overcome common barriers to STEM student success.” Proceedings of the 2016 IEEE Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT) Conference, Atlanta (GA), August 2016.
  12. O. Mendoza-Schrock, M. M. Rizki, E. G. Zelnio, V. J. Velten, F. D. Garber, M. L. Raymer, J. C. Gallagher, “Exploring EO Vehicle Recognition Performance using Manifolds as a Function of Lighting Condition Variability.” Proc. SPIE DSS 111 Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V. April 2015.
  13. T. Doom, K. Timmerman, and M. Raymer. ”Infrastructure for continuous assessment of retained relevant knowledge.“ Proceedings of the 2013 American Society for Engineering Education (ASEE) North Central Conference, Columbus, OH. April 2013.
  14. Mendoza-Schrock, Olga and M.L. Raymer (2012) "Exploring the CAESAR database using
    dimensionality reduction techniques." In Proc. SPIE 8402, Evolutionary and
    Bio-Inspired Computation: Theory and Applications     VI, 84020M, May 2012.
  15. P. Anderson, A Ranabahu, D. Mahle, N. Reo, M. Raymer, A. Sheth, and N. DelRaso (2012) “Localized Deconvolution: Characterizing NMR-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution.” In The 2012 International Conference on Bioinformatics and Computational Biology (BIOCOMP ’12), Las Vegas, NV. July 16-19, 2012.
  16. P. Anderson, A. Manjunatha, A. H. Ranabahu, N. DelRaso, N. Reo, A. Sheth and Michael Raymer (2010), “Cloud-based Map-Reduce Architecture for Nuclear Magnetic Resonance based Metabolomics,” Proceedings of the 7th Microsoft Research eScience Workshop, 2010.
  17. Kotamarti, R. M., Raiford, D. W., Raymer, M. L., & Dunham, M. H. (2009). A Data Mining Approach to Predicting Phylum for Microbial Organisms Using Genome-Wide Sequence Data. IEEE International Symposium on Bioinformatics and Bioengineering, 2009. (BIBE 2009). June 22-24, 2009. Taichung, Taiwan. 161–167. doi:http://doi.ieeecomputersociety.org/10.1109/BIBE.2009.14
  18. Cooper, G. and Raymer, M. (2009), “Improving Remote Homology Detection Using Sequence Properties and Position Specific Scoring Matrices,” The 2009 International Conference on Bioinformatics and Computational Biology (BIOCOMP ’09), Las Vegas, NV. July 13-16, 2009. Acceptance rate: 27%
  19. Klingbeil, N., Rattan, K., Raymer, M., Reynolds, D. and Mercer, R. (2009), “The Wright State Model for Engineering Mathematics Education: A Nationwide Adoption, Assessment and Evaluation.” Proceedings 2009 ASEE Annual Conference & Exposition, Austin, TX, June, 2009.
  20. Anderson, P., Maynard, C., Hodson, N., Kelly, B., Reo, N., DelRaso, N. et al (2009), “A web-based framework for the distribution of bioinformatics techniques: Orthogonal projection on latent structures and principal component analysis implemented as RESTful web services,” In Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2009. Cleveland, OH.
  21. Hanes, A., Raymer, M., Doom, T. & Krane, D (2009), “A comparison of codon usage trends in prokaryotes,” In Proceedings of Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2009. Cleveland, OH.
  22. Klingbeil, N., Rattan, K., Raymer, M., Reynolds, D., Mercer, R., Kukreti, A. and Randolph, B., 2008, “The WSU Model for Engineering Mathematics Education: A Multiyear Assessment and Expansion to Collaborating Institutions,” Proceedings 2008 ASEE Annual Conference & Exposition, Pittsburgh, PA, June, 2008.
  23. Klingbeil, N., Rattan, K., Raymer, M., Reynolds, D., Mercer, R., Kukreti, A. and Randolph, B., 2007, “A National Model for Engineering Mathematics Education,” Proceedings 2007 ASEE Annual Conference & Exposition, Honolulu, HI, June, 2007.
  24. Kelly, B. J., Anderson, P. E., Reo, N. V., DelRaso, N. J. , Doom, T. E., and Raymer, M. L. (2007). “A proposed statistical protocol for the analysis of metabolic toxicological data derived from NMR spectroscopy.” In Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2007), volume II, pages 1414-1418, Cambridge - Boston, Massachusetts, USA IEEE Computer Society.
  25. Raiford, D. W., Krane, D. E., Doom, T. E., and Raymer, M. L. (2007). “A multi-objective genetic algorithm that employs a hybrid approach for isolating codon usage bias indicative of translational efficiency.” In Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2007), volume I, pages 278–285, Cambridge - Boston, Massachusetts, USA (Conference Center at Harvard Medical School). IEEE Computer Society.
  26. B.J. Kelly, P.E. Anderson, N.V. Reo, N.J. DelRaso, T.E. Doom, and M.L. Raymer. “Comparison of Statistical Techniques for the Analysis of Metabolic Toxicological Data Derived from NMR Spectroscopy.” Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2007, Miami University, Oxford, OH, July 9-11, 2007.
  27. D. Raiford, D. Krane, T. Doom, and M. Raymer (2006), “Isolation and visualization of codon usage biases.” In Proceedings of the 6th IEEE Symposium on Bioinformatics and Bioengineering (BIBE 2006), Washington D.C., October 2006, 179–182.
  28. D. Raiford, M. Raymer, E. Heizer, and D. Krane (2006), “An Investigation of Codon Usage Bias Including Visualization and Quantification in Organisms Exhibiting Multiple Biases.” Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2006, Athens, OH. June 2006.
  29. S. Ramachandran, T. Doom, M. Raymer, and D. Krane. “ALU elements as time series genomic data.” Proceedings of Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2006, Athens, OH. June 2006.
  30. Klingbeil, N.W., Mercer, R.E., Rattan, K.S., Raymer M.L. and Reynolds, D.B., 2006, “Redefining Engineering Mathematics Education at Wright State University,” Proceedings 2006 ASEE Annual Conference & Exposition, Chicago, IL, June 2006.
  31. P. Anderson, D. Raiford, D. Sweeney, T. Doom and M. Raymer (2005), “A Stochastic Model of Protease-Ligand Reactions.” Proceedings of the IEEE Symposium on Bioinformatics and Bioengineering (BIBE 2005), October 2005, 306–310.
  32. N. Klingbeil, R. Mercer, K. Rattan, M. Raymer, D. Reynolds (2005), “The WSU Model for Engineering Mathematics Education.” ASEE Annual Conference Proceedings, Portland, Oregon.
  33. N. Klingbeil, R. Mercer, K. Rattan, M. Raymer, D. Reynolds (2005), “Work in progress – The WSU model for engineering mathematics education.” 35th ASEE/IEEE Frontiers in Education Conference, Indianapolis, IN.
  34. M. Peterson, T. Doom, M. Raymer (2005), “GA-Facilitated KNN Classifier Optimization with Varying Similarity Measures.” Proceedings of the 2005 IEEE Congress on Evolutionary Computation (CEC 2005), 3, 2506–2513.
  35. M. Peterson, M. Raymer, G. Lamont (2005), “Balanced Accuracy for Feature Subset Selection with Genetic Algorithms.” Proceedings of the 2005 IEEE Congress on Evolutionary Computation (CEC 2005), 3, 2514–2521.
  36. N. Klingbeil, R. Mercer, K. Rattan, M. Raymer and D. Reynolds (2005), “Redefining Engineering Mathematics Education at Wright State University.” Proceedings of the 2005 ASEE North Central Conference, Ada, OH, April 2005. Winner: Overall Best Paper Award.
  37. M. Raymer, M. Peterson and T. Doom (2004), “Knowledge Discovery in Large Biological Data Sets Using Hybrid Classifier/Evolutionary Algorithms.” Proceedings the 36th Symposium on the Interface: Computational Biology and Bioinformatics, Baltimore, MD, May 26 – 29, 2004.
  38. G. Kramer, J. Gallagher, and M. Raymer (2004), “On the Relative Efficacies of *cGA Variants for Intrinsic Evolvable Hardware: Population, Mutation, and Random Immigrants.” in Proc 2004 NASA/DoD Conference on Evolvable Hardware. IEEE Press, 2004.
  39. N. Klingbeil, R. Mercer, K. Rattan, M. Raymer, and D. Reynolds (2004), “Rethinking Engineering Mathematics Education: A Model for Increased Retention, Motivation and Success in Engineering.” ASEE Annual Conference Proceedings, Salt Lake City (UT), pp. 12169-12180, June 2004.
  40. M. Peterson, T. Doom, and M. Raymer (2004), “GA-facilitated knowledge discovery and pattern recognition optimization applied to the biochemistry of protein solvation.” Proceedings of ACM Genetic and Evolutionary Computation Conference (GECCO) 2004, Seattle (WA), pp. 426-437, June 2004.
  41. G. Cooper, M. Raymer, T. Doom, D. Krane, and N. Futamura (2004), “Indexing genomic databases.” Proceedings of 2004 IEEE international symposium on Bioinformatics and Bioengineering (BIBE) , Taichung (Taiwan), pp. 587-591, May 2004.
  42. J. Gilder, D. Krane, T. Doom and M. Raymer (2003), “Identifying patterns in DNA change.” Proceedings of the 2003 Midwest Artificial Intelligence and Cognitive Science Conference (MAICS 2003), 34, 78–84.
  43. M. Peterson, T. Doom, and M. Raymer (2002), “GA-facilitated cosine classifier optimization with application to the biochemistry of protein-water interactions.” International Conference on High Performance Computing, (HPC-Asia 2002), Banglore (India), December 2002.
  44. T. Doom, M. Raymer, D. Krane, and O. Garcia (2002), “A Proposed Undergraduate Bioinformatics Curriculum for Computer Scientists.” Proceedings of the ACM Special Interest Group on Computer Science Education (SIGCSE 2002), Covington, KY, February, 2002.
  45. M. Raymer, A. Kuhn, and W. Punch (2001), “Knowledge Discovery in Biological Datasets Using a Hybrid Bayes Classifier/Evolutionary Algorithm.” Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001), 236–245.
  46. D. Sweeney, G. Alter, M. Raymer, and T. Doom (2001), “Profile Combinatorics for Fragment Selection in Comparative Protein Structure Modeling.” Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001), 271–278.
  47. J. Gilder, M. Raymer, and T. Doom (2001), “PocketMol: A Molecular Visualization Tool for the PocketPC.” Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bio-engineering (BIBE 2001), 11–14.
  48. M. Raymer, W. Punch, E. Goodman, P. Sanschagrin, and L. Kuhn (1997), “Simultaneous Feature Scaling and Selection Using a Genetic Algorithm.” in Proceedings of the Seventh International Conference on Genetic Algorithms (T. Bäck, ed.), Morgan Kaufmann Publishers, San Francisco, pp. 561–567.
  49. M. Raymer, W. Punch, E. Goodman, and L. Kuhn (1996), “Genetic Programming for Improved Data Mining – Application to the Biochemistry of Protein Interactions.” in Genetic Programming 1996: Proceedings (J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, eds.), MIT Press, Cambridge, MA, pp. 275–381.

Articles in Magazines, Letters, Book Reviews, Abstracts, and Other Publications

  1. H. B. Yalamanchili, M. L. Raymer and M. P. Markey (2015). “Application of semi-supervise learning in Genome Wide Association Studies (GWAS) for melanoma.” Abstract and poster at the Great Lakes Bioinformatics Conference (GLBIO) 2015, May 18 — 20, 2015. West Lafayette, IN.
  2. K. Timmerman, T. Doom, M. Raymer, and J. Gallagher (2015). “Educational methods for inverted-lecture computer science classrooms to overcome common barriers to STEM student success.” Ohio-PKAL First Annual Conference – Increasing STEM Student Success in Higher Education, May 16, 2015. Westerville, OH.
  3. N. Reo, I. Sibomana, N. DelRaso, M. Raymer and D. Harville (2014). “Metabolomics Approach for Identifying Urinary Markers of Cognitive Performance under Conditions of Sleep Deprivation-Induced Fatigue.” Proc. of the 4th Midwestern Cognitive Science Conference, May 30-31, 2014. Dayton, OH.
  4. D. E. Krane, V. Bahn, D. Balding, B. Barlow, H. Cash, B. L. Desportes, P. D’Eustachio, K. Devlin, T. E. Doom, I. Dror, S. Ford, C. Funk, J. Gilder, G. Hampikian, K. Inman, A. Jamieson, P. E. Kent, R. Koppl, I. Kornfield, S. Krimsky, J. Mnookin, L. Mueller, E. Murphy, D. R. Paoletti, D. A. Petrov, M. Raymer, D. M. Risinger, A. Roth, N. Rudin, W. Shields, J. A. Siegel, M. Slatkin, Y. S. Song, T. Speed, C. Spiegelman, P. Sullivan, A. R. Swienton, T. Tarpey, W. C. Thompson, E. Ungvarsky, and S. Zabell (2009) “Time for DNA Disclosure,” Science 18 December 2009 326: 1631-1632 [DOI: 10.1126/science.326.5960.1631]
  5. P. Anderson, N. Reo, N. DelRaso, and M. Raymer (2008). “Gaussian binning for processing NMR spectroscopic data for metabolomics.” U.S. Army Center for Health Promotion and Preventive Medicine 11th Annual Force Health Protection Conference, August 9-11, 2008. Albuquerque, NM.
  6. N. Reo, A. Neuforth, W. Couch, M. Raymer, P. Anderson, D. Mahle, and N. DelRaso (2007). “A time and dose response metabonomics study of d-serine toxicity in rats.” Society of Toxicology 47th annual meeting, March 16–20, 2008.
  7. P. Anderson, L. Mitchell, D. Sweeney, T. Christian, M. Raymer, and G. Alter, “Protein Structure Probing through Chemical Modification”, Poster and abstract: Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2006, June 2006.
  8. M. Raymer (2005), “Book Review: Evolutionary Computation in Bioinformatics.” Genetic Programming and Evolvable Machines, 6, 229-230.
  9. M. Peterson, T. Doom, and M. Raymer (2005), “GA-facilitated classifier optimization with varying similarity measures.” Proceedings of ACM Genetic and Evolutionary Computation Conference (GECCO) 2005, April 2005.
  10. D. Krane, T. Doom, L. Mueller, M. Raymer, W. Shields and W. Thompson (2004), “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.” Journal of Forensic Science, Dec. 2004.
  11. T. Doom, M. Raymer, and D. Krane (2004), “Bioinformatics: Where Biology meets Computer Science.” IEEE Potentials, 23:1, 24–27, February/March, 2004.
  12. D. Krane, M. Raymer, and T. Doom (2003), “An interdisciplinary undergraduate bioinformatics curriculum for biological scientists.” Journal of College Science Teaching, XXXII:296.
  13. W. Thompson, S. Ford, T. Doom, M. Raymer, and D. Krane (2003), “Evaluating forensic DNA evidence: Breaking open the black box (how to review electronic data).” The Champion, (XXVII:3), 25-28.
  14. W. Thompson, S. Ford, T. Doom, M. Raymer, and D. Krane (2003), “Evaluating forensic DNA evidence: Essential elements of a competent defense review.” The Champion, (XXVII:2), 16-25. – Cited by Justice Samuel Alito in United States Supreme Court ruling DISTRICT ATTORNEY’S OFFICE FOR THE THIRD JUDICIAL DISTRICT ET AL. v. OSBORNE. Justice Alito cites this paper to support the idea that the extreme sensitivity of modern DNA tests makes forensic DNA evidence highly subject to contamination.
  15. J. Gilder, M. Raymer, and T. Doom. “PocketMol: A Molecular Visualization Program for the Pocket PC.” Abstract and poster at the Symposium on Bioinformatics for Drug-Development, Toledo (OH), November 2001.
  16. M. Peterson, M. Raymer, and T. Doom. “Prediction Enhancement of Protein-Water Binding Conservation through Evolutionary Computation.” Abstract and poster at the Symposium on Bioinformatics for Drug-Development, Toledo (OH), November 2001.
  17. D. Sweeney, T. Doom, and M. Raymer. “Profile Combinatorics for Fragment Selection in Comparative Protein Structure Modeling.” Abstract and poster at the Symposium on Bioinformatics for Drug-Development, Toledo (OH), November 2001.

Theses and Dissertations Directed

  1. Topological Analysis of Averaged Sentence Embeddings, Wesley Holmes, M.S. Thesis, 2020.
  2. Chemical Probing and Limited Proteolysis Toward Biomolecular Structure Determination with RAVE, the Reactivity Analysis and Validation Environment, Deacon Sweeney, Ph.D. Dissertation, BMS Ph.D. Program (co-advisor), August 2011.
  3. Measuring Uncertainty of Protein Secondary Structure, Alan Herner, Ph.D. Dissertation, 2011.
  4. Algorithmic Techniques Employed in the Quantification and Characterization of Nuclear Magnetic Resonance Spectroscopic Data, Paul Anderson, Ph.D. Dissertation, 2010.
  5. Improving Remote Homology Detection Using a Sequence Property Approach, Gina Cooper, Ph.D. Dissertation, 2009.
  6. What Machines Understand about Personality Words after Reading the News, Eric Moyer, M.S. Thesis, 2014.
  7. Investigation and quantification of codon usage bias trends in prokaryote, Amanda Hanes, M.S. Thesis, Spring 2009.
  8. Computational Analysis of Metabolomic Toxicological Data Derived from NMR Spectroscopy, Ben Kelly, M.S. Thesis, Spring 2009.
  9. Algorithmic Techniques Employed in the Isolation of Codon Usage Biases in Prokaryotic Genomes, Douglas W. Raiford III, Ph.D. Dissertation, Spring 2008.
  10. Evolutionary Methodology for Optimization of Image Transforms Subject to Quantization Noise, Michael Peterson, Ph.D. Dissertation, Spring 2008.
  11. Computational methods for the objective review of forensic DNA testing results, Jason R. Gilder, Ph.D. Dissertation, Summer 2007.
  12. A computational framework for analyzing chemical modification and limited proteolysis experiments for high confidence protein structure determination, Paul Anderson, M.S. Thesis, Fall 2006.
  13. Multivariate Analysis of Prokaryotic Amino Acid Usage Bias: A Computational Method for Understanding Building Block Selection in Primitive Organisms, Doug Raford, M.S. Thesis, Summer, 2005.
  14. Male-driven substitutional evolution in humans, Balasubramanian Abiramikumar, M.S. Thesis, Summer, 2004.
  15. Application of alternative regression methods to quantitative structure-based analysis of drug binding affinity, Prashanth Athri, M.S. Thesis, Fall, 2003.
  16. Developing an expert system and discovering new standards for forensic DNA analysis, Jason Gilder, M.S. thesis, Spring, 2003.
  17. EC-Facilitated cosine-based knn classifier optimization as applied to protein solvation, Michael Peterson, M.S. thesis, Spring, 2003.
  18. Statistical boundaries for recognizing positive selection in mammalian orders using nucleotide substitution rates, Sundeep Anand, M.S. Thesis, Spring, 2003.

Other Scholarship

Patents and Licensing Agreements

  1. T. Doom, M. Raymer, O. Garcia, D. Krane (inventors). Exclusive license agreement with Forensic Bioinformatic Services, Inc. (licensee) for the use of the Genophiler software and related technology developed at Wright State University, July 19, 2002.

Selected Workshops, Seminars, Panels, and Invited Presentations

  1. Moyer, E. & Raymer, M. L. (2013). Improving automatic peak parameter determination in crowded NMR spectra by using summit-focused parameter initialization. American Chemical Society & Society for Applied Spectroscopy, Dayton Chapter, Annual Collaborative Research Exposition. Dayton, OH, March 12, 2013. Winner: Best Student Poster Award.
  2. Rovito, T., Mendoza-Schrock, O., & Raymer, M. L. (2012). Exploring Manifold Learning Techniques Using the CAESAR Database. SPIE Defense, Security & Sensing. Baltimore, MD, April 23-27, 2012.
  3. M. L. Raymer (2009), “Beyond CSI: The science and non-science of forensic DNA analysis and interpretation.” Invited talk for the Ohio University Distinguished Lecturers in Bioinformatics Series. Athens, OH, April 2010.
  4. M. L. Raymer (2009), “Beyond CSI: The science and non-science of forensic DNA analysis and interpretation.” Invited tutorial for the Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2009. Cleveland, OH, June 15-17, 2009.
  5. M. L. Raymer (2008), “Introduction to Bioinformatics.” Invited seminar for the Miami University Workshop on Algorithms and Data Analysis for Bioinformatics. Miami University, Oxford OH, May 14-15, 2008.
  6. M. L. Raymer (2008), “Fundamental Concepts of Bioinformatics.” Invited tutorial for the Ohio Collaborative Conference on Bioinformatics (OCCBIO), University of Toledo, Ohio, July 2008.
  7. S. Sahoo, M. Raymer, C. Henson, A. Sheth and W. York (2008) Ontology driven Semantic Provenance for Heterogeneous Bionomics Experimental Data. Oral presentation at the Ohio Collaborative Conference on Bioinformatics (OCCBIO), University of Toledo, OH, July 2008.
  8. D. Homer, M. Raymer and N. V. Reo (2008), "Statistical Population Thresholding: A novel non-linear thresholding method for peak and baseline selection in biological spectra containing thermally generated noise." WSU Biomedical Sciences Program Research Retreat, D. H . Ponitz Sinclair Center, Sinclair Community College, Dayton, OH. May 19, 2008. (Platform presentation).
  9. M. L. Raymer (2007), “Charting the winds of evolutionary change: Bioinformatics methods
    for identifying bias in prokaryotic codon usage.” Invited talk for Indiana University Southeast, College of Natural Sciences. November, 2007.
  10. M. L. Raymer (2007), “CSI Revisited: The Science of Forensic DNA Analysis.” Invited talk for the IEEE Computer Society, Dayton Chapter. August 2007. Dayton, OH.
  11. M. L. Raymer (2007), “Fundamental Concepts of Bioinformatics.” Invited tutorial for the Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2007, Miami University, Oxford, OH. July 9-11, 2007.
  12. Klingbeil, N.W., Mercer, R.E., Rattan, K.S., Raymer M.L. and Reynolds, D.B. (2007), "Engineering Mathematics Education at Wright State University: A Model for Increasing Student Success in Engineering," Dayton Engineering Sciences Symposium, October, 2007.
  13. Klingbeil, N.W., Mercer, R.E., Rattan, K.S., Raymer M.L. and Reynolds, D.B., (2007) "The Wright State Model for Engineering Mathematics Education: Uncorking the First-Year Bottleneck," A Dialogue on Engineering Education II: The Role of the First Year, ASEE First Year Engineering Workshop, Notre Dame, IN, July 2007.
  14. Klingbeil, N.W., Mercer, R.E., Rattan, K.S., Raymer M.L. and Reynolds, D.B. (2007), "A National Model for Engineering Mathematics Education," ASEE Southeastern Section Conference, Louisville, KY, April 2007.
  15. Klingbeil, N.W., Mercer, R.E., Rattan, K.S., Raymer M.L. and Reynolds, D.B. (2007), "Engineering Mathematics Education at Wright State University: Uncorking the First-Year Bottleneck," 26th Annual Conference on the First-Year Experience, National Resource Center for the First-Year Experience & Students in Transition, Addison, TX, February 2007.
  16. D. A. Mahle, N. J. DelRaso, M. L. Raymer, A. E. Neuforth, M. Westrick and N. V. Reo (2006), “Combined Urine and Plasma Metabolomic Analysis of α-Napthylisothiocyanate (ANIT) Liver Toxicity in the Rat.” Presented at 2nd Annual Meeting of the Metabolomic Society, Boston, MA, June 2006.
  17. M. L. Raymer, G. Alter, P. Anderson, D. Sweeney and L. Mitchell (2006), “Computational and Experimental Methods for High Confidence Protein Structure Prediction.” Invited presentation for the Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2006, Athens, OH. June 2006.
  18. M. L. Raymer (2006), “Fundamental Concepts of Bioinformatics.” Invited tutorial for the Ohio Collaborative Conference on Bioinformatics (OCCBIO) 2006, Athens, OH. June 2006.
  19. M. L. Raymer (2005), “Beyond CSI: The Science and Engineering of Forensic DNA Analysis and Interpretation”, Invited presentation for the Dayton, OH chapter of the IEEE, July 2005.
  20. M. L. Raymer, M. Peterson and T. E. Doom (2004), “Knowledge Discovery in Large Biological Data Sets Using Hybrid Classifier/Evolutionary Algorithms.” Invited presentation at the 36th Symposium on the Interface: Computational Biology and Bioinformatics, Baltimore, MD, May 26 – 29, 2004.
  21. J. R. Gilder, S. Ford, M. Raymer, T. E. Doom and D. E. Krane (2003), “Differences in electropherogram peak heights reported by different versions of the Genescan(R) software.” 14th International Symposium on Human Identification. Promega. Phoenix, AZ. September 29 - October 2, 2003.
  22. M. Raymer, D. Krane and T. Doom (2003), NSF workshop on incorporating genomics into the undergraduate curriculum II. Invited talk, Wheaton College, Norton, MA., June 2003.
  23. M. Raymer, D. Krane, and T. Doom (2002), NSF workshop on incorporating genomics into the undergraduate curriculum. Invited talk, Wheaton College, Norton, MA., June 2002.
  24. M. Raymer (2002), “Visualization in Bioinformatics.” Invited presentation for the Ohio Supercomputing Center/Wright State University Summer Institute for Advanced Computation, Dayton, OH.
  25. M. Peterson, M. Raymer, and T. Doom (2001), “Prediction Enhancement of Protein-Water Binding Conservation through Evolutionary Computation.” Presented at the Symposium on Bioinformatics for Drug Development, Toledo, OH, November 16–17, 2001.
  26. J. Gilder, M. Raymer, and T. Doom (2001), “PocketMol: A Molecular Visualization Program for the Pocket PC.” Presented at the Symposium on Bioinformatics for Drug Development, Toledo, OH, November 16–17, 2001.
  27. D. Sweeney, M. Raymer, and T. Doom (2001), “Profile Combinatorics for Fragment Selection in Comparative Protein Structure Modeling.” Presented at the Symposium on Bioinformatics for Drug Development, Toledo, OH, November 16–17, 2001.
  28. M. Raymer (2001), “Computational Biology for Drug Design: Understanding how proteins and waters interact.” Invited talk for the Ohio Supercomputing Center’s Summer Institute for Advanced Computation, Dayton, OH, August, 2001.
  29. M. Raymer (2001), “Molecular graphics: visualization of proteins.” Invited talk for the Ohio Supercomputing Center’s Summer Institute for Advanced Computation, Dayton, OH, August, 2001.
  30. M. L. Raymer (2000), “An Overview of Bioinformatics and Computational Biology.” Invited presentation for the Statewide Users’ Group of the Ohio Supercomputer Center, Cincinnati, OH, November 2000.
  31. L. A. Kuhn, V. Schnecke, M. L. Raymer, and P. C. Sanschagrin (1999), “How proteins fold, flex, and bind other molecules.” Workshop on Computational and Theoretical Biology, Michigan State University, April, 1999.
  32. M. L. Raymer, D. Holstius, P. C. Sanschagrin, L. A. Kuhn (1998), “Identifying the Determinants of Conserved Protein Solvation.” Presentation at Protein Society Symposium, San Diego, CA, July 1998.
  33. M. L. Raymer, P. C. Sanschagrin, W. F. Punch, E. D. Goodman, and L. A. Kuhn (1998), “Elucidating the Determinants of Conserved Protein Surface Solvation Using a Genetic Algorithm and Nearest Neighbor Classifier.” Presentation at UCSF/MDI Conference on Molecular Recognition in Drug Design: Docking and Scoring, San Francisco, California, February 1998.
  34. M. L. Raymer, W. F. Punch, E. D. Goodman, P. C. Sanschagrin, and L. A. Kuhn (1997), “Simultaneous Feature Extraction and Selection Using a Masking Genetic Algorithm.” Presentation at the Seventh International Conference on Genetic Algorithms (ICGA), July 1997.
  35. M. L. Raymer, W. F. Punch, P. C. Sanschagrin, E. D. Goodman, and L. A. Kuhn (1997), “Discovering the Chemistry of Conserved First-Shell and Active-Site Hydration in Proteins Using Pattern Classification with a Genetic Algorithm.” Presentation at Protein Society Symposium, Boston, Massachusetts, July 1997.
  36. M. L. Raymer, W. F. Punch, E. D. Goodman, and L. A. Kuhn (1996), “Genetic Programming for Improved Data Mining – Application to the Biochemistry of Protein Interactions.” Presentation at Genetic Programming 1996: the First Annual Conference, Stanford University, Palo Alto, California, July 1996.
  37. M. L. Raymer (1996), “Learning From Nature - Genetic Algorithms Applied to Protein Recognition.” Presentation for the Macromolecular Structural Techniques Group at Michigan State University, January, 1996.
  38. M. L. Raymer, W. F. Punch, E. D. Goodman, P. C. Sanschagrin, and L. A. Kuhn (1996), “Pattern Recognition Using Evolutionary Algorithms Applied to Understanding Water-Mediated Recognition in Proteins.” Presented at Sandia National Laboratory Workshop on Computational Molecular Biology, Albuquerque, New Mexico, March 1996.
  39. M. L. Raymer, S. Venkataraman, W. F. Punch, E. D. Goodman, and L. A. Kuhn (1995), “Predicting Conserved Water-Mediated Interactions in Protein Active Sites.” Invited presentation at the American Crystallographic Association Annual Meeting, Montreal, Quebec, Canada, July 1995.
  40. M. L. Raymer, W. F. Punch, E. D. Goodman, M. Pei, and L. A. Kuhn (1995), “Prediction of Conserved Water Sites Between Independently Solved Protein Structures Using a Genetic Algorithm and a K Nearest Neighbor Classifier.” West Coast Protein Crystallography Workshop, Pacific Grove, California, March 1995.
  41. L. A. Kuhn, P. C. Sanschagrin, and M. L. Raymer (1997), “Using Cluster Analysis to Identify Conserved Binding Sites in Proteins.” Presentation at the Protein Society Symposium, Boston, Massachusetts, July 1997.
  42. L. A. Kuhn, W. B. Anderson, C. E. Barkham, M. L. Raymer, and P. C. Sanschagrin (1997), “Implications of Structural Comparison of Prostaglandin Synthase Isozymes and Ribonucleotide Reductase for Understanding their Specificity and Catalysis.” Presentation at the American Heart Association, Michigan Affiliate Cardiovascular Research Forum, Ann Arbor, September 1997.
  43. P. C. Sanschagrin, M. L. Raymer, and L. A. Kuhn (1997), “Cluster Analysis of Multiple Serine Protease Structures Identifies Conserved Water Sites Involved in Structure and Specificity.” Presentation at West Coast Protein Crystallography Workshop, Pacific Grove, California, March 1997.
  44. L. A. Kuhn, M. L. Raymer, P. C. Sanschagrin, E. D. Goodman, and W. F. Punch (1996), “Resolving Water-Mediated and Polar Ligand Recognition Using Genetic Algorithms.” Presented at the International Conference on Protein Folding and Design, National Institutes of Health, Bethesda, Maryland, April 1996.
  45. L. A. Kuhn, M. L. Raymer, W. F. Punch, P. C. Sanschagrin, and E. D. Goodman (1996), “Predicting and Analyzing Determinants of Water-Mediated Ligand Recognition.” Presented at the International Union of Crystallography Congress and General Assembly, Seattle, Washington, August 1996.
  46. L. A. Kuhn, M. L. Raymer, W. F. Punch, P. C. Sanschagrin, and E. D. Goodman (1996), “Predicting and Analyzing Determinants of Water-Mediated Ligand Recognition.” International Union of Crystallography Congress and General Assembly, Seattle, Washington, August 1996.
  47. L. A. Kuhn, M. L. Raymer, P. C. Sanschagrin, E. D. Goodman, and W. F. Punch III (1995), “Genetic Algorithm Prediction of Water-mediated Ligand Interactions and the Implications for the Chemistry of Water Binding.” Invited talk for the Program in Mathematics and Molecular Biology Symposium: From DNA to Protein Structure and Function, Santa Fe, NM, November, 1995.

Service

Academic Service

Professional Service

Entrepreneurship

  • Co-founder, co-owner, and Senior Systems Engineer for Forensic Bioinformatics Services (FBS) (http://www.bioforensics.com) (2002–present).
  • Raymer Consulting, LCC - private consulting in machine learning, pattern recognition, and analytics (2020–present).