MEME

MAST

Other MEME- and MAST-related publications

• Timothy L. Bailey and Michael Gribskov, "Methods and statistics for combining motif match scores", Journal of Computational Biology, Vol. 5, pp. 211-221, 1998.
• Timothy L. Bailey and Michael Gribskov, "Score distributions for simultaneous matching to multiple motifs", Journal of Computational Biology, Vol. 4, pp. 45-59, 1997.
• William N. Grundy, Timothy L. Bailey, Charles P. Elkan and Michael E. Baker. "Hidden Markov Model Analysis of Motifs in Steroid Dehydrogenases and their Homologs", Biochemical and Biophysical Research Communications, Vol 231, pp. 760-766, 1997.
• William N. Grundy, Timothy L. Bailey, Charles P. Elkan and Michael E. Baker. "Meta-MEME: Motif-based Hidden Markov Models of Protein Families", Computer Applications in the Biological Sciences (CABIOS), Vol. 13, pp. 397-406, 1997.
• Timothy L. Bailey, Michael E. Baker and Charles P. Elkan, "An artificial intelligence approach to motif discovery in protein sequences: application to steriod dehydrogenases", Journal of steroid biochemistry and molecular biology, Vol. 62, 1997.
• William N. Grundy, Timothy L. Bailey and Charles P. Elkan, ParaMEME: A Parallel Implementation and a Web Interface for a DNA and Protein Motif Discovery Tool, Computer Applications in the Biological Sciences (CABIOS), Vol. 12, pp. 303-310, 1996.
• Timothy L. Bailey and Michael Gribskov, The megaprior heuristic for discovering protein sequence patterns, Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology, pp. 15-24 AAAI Press, Menlo Park, California, 1996.
• Timothy L. Bailey and Charles Elkan, The value of prior knowledge in discovering motifs with MEME, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 21-29, AAAI Press, Menlo Park, California, 1995.
• Timothy L. Bailey, Discovering motifs in DNA and protein sequences: The approximate common substring problem, Ph.D. dissertation, University of California at San Diego, 1995.
• Timothy L. Bailey and Charles Elkan, Unsupervised Learning of Multiple Motifs in Biopolymers using EM, Machine Learning, 21(1-2):51-80, October, 1995.
• Timothy L. Bailey and Charles Elkan, Fitting a mixture model by expectation maximization to discover motifs in biopolymers, UCSD Technical Report, CS94-351, March, 1994, University of California at San Diego.