Michael Paul Stewart Brown Homepage

Email
  • mpbrown@cse.ucsc.edu
  • mpsb314@earthlink.net
  • mpsb@hnc.com
Research Interests:
  • Bioinformatics. Application of probabilistic and machine learning techniques to new bioinformatics problems with large amounts of data.
  • Bayesian Modeling
  • RNA Modeling
  • Probabilistic generative models of sequences. Hidden Markov models, stochastic context-free grammars, graphical models, Fisher features.
  • Classifier systems. Support vector machines, Guassian processes, information geometries, boosting.
  • Unsupervised learning of concepts. Mixture and product models, simulated annealing, Expectation Maximization.
  • Characterization of information flow and mechanisms of living things. Genomic organization, pathway inference, RNA structure, transcription, translation, regulation, RNAi, cross species analysis.
  • Information retrieval and modeling. Vector space models, large vocabulary modeling, efficient search, link structure analysis.
Publications:
  • Papers. I have papers available for downloading on hidden Markov models, stochastic context-free grammars, Dirichlet mixtures, and support vector machines applied to protein modeling, RNA modeling including ribosomal RNA, RNA pseudoknot modeling, residue prior distributions, and DNA microarray data analysis.
Personal Information:
  • I finished my PhD with my advisor, David Haussler, at UCSC in October 1999. I am now working at HNC in San Diego doing bioinformatics, RNA modeling, large-scale pattern discovery, and learning more about information geometries.
  • CV in pdf
Software:
  • RNACAD
    • Package implementing stochastic context-free grammars for RNA secondary structure modeling. Includes an end-to-end tutorial for simple t-RNA modeling.
Web Pages:
Links:
Small Picture
updated 2000 08 01