Michael A. Langston

Professor - Electrical Engineering and Computer Science Department

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Dr. Langston received the Ph.D. in Computer Science from Texas A&M University in 1981. He currently holds the title of Professor of Computer Science at the University of Tennessee. He is core faculty in the university’s Genomics Science and Technology program, and a long-time collaborator with several divisions at the Oak Ridge National Laboratory. Langston is probably best known for his long-standing work on combinatorial algorithms, complexity theory and design paradigms for sequential and parallel computation. His present research efforts are focused primarily on the development, synthesis, analysis and high performance implementation of novel graph algorithms and emergent mathematical methods. Applications of these tools are largely concentrated in the study of high throughput and/or heterogeneous biological data. In addition to maintaining his research program, he regularly teaches courses on algorithm design, automata theory, combinatorics, graph theory and related subjects. Langston’s work has been funded in the U.S. by the National Science Foundation, the National Institutes of Health, the Department of Defense, the Department of Energy and a variety of other state and federal agencies. He has been supported overseas by the Australian Research Council and the European Commission. He has also served on an assortment of editorial boards, including the Association for Computing Machinery’s flagship publication, Communications of the ACM.

Focus Areas:  Biomarker Discovery | Computational Systems Biology | High Throughput Omics Analysis

Skills and Expertise:  Combinatorics and Graph Theory | Heterogeneous Data Decomposition | High Performance Computation

Selected Publications:

Differential Shannon Entropy and Differential Coefficient of Variation: Alternatives and Augmentations to Differential Expression in the Search for Disease-Related Genes (accepted)
K. Wang, C.A. Phillips, G.L. Rogers, F. Barrenäs, M. Benson and M.A. Langston, International Journal of Computational Biology and Drug Design,
Complex Genetic Interactions Of Twenty Loci Define Major Subtypes Of Type 1 Diabetes (in review)
G. Morahan, C. Nguyen, M. Mehta, R. Ram, G.L. Rogers, M.A. Langston, P. Concannon, S.S. Rich and L.C. Harrison,
GeneWeaver: a Web-based System for Integrative Functional Genomics
E.J. Baker, J.J. Jay, J.A. Bubier, M.A. Langston, and E.J. Chesler, Nucleic Acids Research, vol. 40, no. D1, pp. D1067-D1076, 2012.
Increased Expression of IRF4 and ETS1 in CD4+ Cells from Patients with Intermittent Allergic Rhinitis
S. Bruhn, F. Barrenäs, R. Mobini, B.A. Andersson, S. Chavali, B.S. Egan, E. Hovig, G.K. Sandve, M.A. Langston, G.L. Rogers, H. Wang, and M. Benson, Allergy, vol. 67, no. 1, pp. 33-40, 2012.
Genetic Dissection of Acute Ethanol Responsive Gene Networks in Prefrontal Cortex: Functional and Mechanistic Implications
A.R. Wolen, C.A. Phillips, M.A. Langston, A.H. Putman, P.J. Vorster, N.A. Bruce, T.P. York, R.W. Williams and M.F. Miles, PLoS ONE , vol. 7, e33575, 2012.
Highly Interconnected Genes in Disease-Specific Networks are Enriched for Disease-Associated Polymorphisms
F. Barrenäs, S. Chavali, A.C. Alves, L. Coin, M. Jarvelin, R. Jörnsten, M.A Langston, A. Ramasamy, G.L. Rogers, H. Wang and M. Benson, Genome Biology, vol. 13, no. R46, 2012.
Immersion Containment and Connectivity in Color-Critical Graphs
F.N. Abu-Khzam and M.A. Langston, Discrete Mathematics and Theoretical Computer Science, vol. 14, no. 2, pp. 155-164, 2012.
Fixed-Parameter Tractability, A Prehistory
M.A. Langston, The Multivariate Complexity Revolution and Beyond, Lecture Notes in Computer Science, vol. 7370, pp. 3-16, 2012.
Inferring Networks for Disease
M. Benson and M.A. Langston, Encyclopedia of Molecular Cell Biology and Molecular Medicine, pp. 565-592, 2012.
A Systematic Comparison of Genome Scale Clustering Algorithms
J.J. Jay, J.D. Eblen, Y. Zhang, M. Benson, A.D. Perkins, A.M. Saxton, B.H. Voy, E.J. Chesler and M.A. Langston, Bioinformatics Research and Applications, Lecture Notes in Computer Science, vol. 6674, pp. 416-427, 2011.