Information Theoretic Methods for Bioinformatics

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  EURASIP Journal on Bioinformatics and Systems Biology - An Open Access Journal

  Special Issue on

  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 modeling of 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:

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

  Authors should follow the EURASIP JBSB manuscript format described at
  the journal site http://www.hindawi.com/GetJournal.aspx?journal=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 Due             February 1, 2007
  Acceptance Notification    May 1, 2007
  Final Manuscript Due       July 1, 2007
  Publication Date           3rd Quarter, 2007

  Guest Editors:

  Jorma Rissanen, Computer Learning Research Center, University of London,
  Royal Holloway,TW20 0EX, UK; jorma.rissanen@mdl-research.org

  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; pdg@cwi.nl

  Jukka Heikkonen, Laboratory of Computational Engineering, Helsinki
  University of Technology, P.O. Box 9203, 02015 HUT, Finland;
  jukka.heikkonen@tkk.fi

  Petri Myllymaki, Department of Computer Science, University of Helsinki,
  P.O. Box 68 (Gustaf Hallstromin katu 2b), 00014, Finland;
  petri.myllymaki@cs.helsinki.fi

  Teemu Roos, Complex Systems Computation Group, Helsinki Institute for
  Information Technology, University of Helsinki, P.O.Box 68, 00014, Finland;
  teemu.roos@hiit.fi

  Juho Rousu, Department of Computer Science, University of Helsinki,
  P.O. Box 68 (Gustaf Hallstromin katu 2b), 00014, Finland;
  juho.rousu@cs.helsinki.fi

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