Information Theoretic Methods for Bioinformatics

Call for Papers

Information theoretic methods for modeling are at the center of the current efforts to interpret bioinformatics data. The high pace at which new technologies are developed for collecting genomic and proteomic data requires a sustained effort to provide powerful methods for modeling the data acquired. Recent advances in universal modeling and minimum description length techniques have been shown to be well suited for modeling and analyzing such data. This special issue calls for contributions to modelingof data arising in bioinformatics and systems biology by information theoretic means. Submissions should address theoretical developments, computational aspects, or specific applications. Suitable topics for this special issue include but are not limited to:

  • Normalized maximum-likelihood (NML) universal models
  • Minimum description length (MDL) techniques
  • Microarray data modeling
  • Denoising of genomic data
  • Pattern recognition
  • Data compression-based modeling

Authors should follow the EURASIP JBSB manuscript format described at the journal site http://www.hindawi.com/journals/bsb/. Prospective authors should submit an electronic copy of their complete manuscript through the EURASIP JBSB's Manuscript Tracking System at http://www.hindawi.com/mts/, according to the following timetable:

Manuscript DueMarch 1, 2007
First Round of ReviewsMay 1, 2007
Publication DateAugust 1, 2007

Guest Editors

  • Jorma Rissanen, Computer Learning Research Center, University of London, Royal Holloway,TW20 0EX, UK
  • Peter Grünwald, Centrum voor Wiskunde en Informatica (CWI), National Research Institute for Mathematics and Computer Science, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands
  • Jukka Heikkonen, Laboratory of Computational Engineering, Helsinki University of Technology, P.O. Box 9203, 02015 HUT, Finland
  • Petri Myllymäki, Department of Computer Science, University of Helsinki, P.O. Box 68 (Gustaf Hällströmin katu 2b), 00014, Finland
  • Teemu Roos, Complex Systems Computation Group, Helsinki Institute for Information Technology, University of Helsinki, P.O.Box 68, 00014, Finland
  • Juho Rousu, Department of Computer Science, University of Helsinki, P.O. Box 68 (Gustaf Hällströmin katu 2b), 00014, Finland