A New Variational Framework for Rigid-Body Alignment

  • Tsuyoshi Kato
  • Koji Tsuda
  • Kentaro Tomii
  • Kiyoshi Asai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)


We present a novel algorithm for estimating the rigid-body transformation of a sequence of coordinates, aiming at the application to protein structures. Basically the sequence is modeled as a hidden Markov model where each state outputs an ellipsoidal Gaussian. Since maximum likelihood estimation requires to solve a complicated optimization problem, we introduce a variational estimation technique, which performs singular value decomposition in each step. Our probabilistic algorithm allows to superimpose a number of sequences which are rotated and translated in arbitrary ways.


Hide Markov Model Singular Value Decomposition Shape Model Hide Variable Variational Framework 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Tsuyoshi Kato
    • 1
  • Koji Tsuda
    • 1
    • 2
  • Kentaro Tomii
    • 1
  • Kiyoshi Asai
    • 1
    • 3
  1. 1.AIST Computational Biology Research CenterTokyoJapan
  2. 2.Max Planck Institute of Biological CyberneticsTübingenGermany
  3. 3.Graduate School of Frontier SciencesThe University of TokyoKashiwaJapan

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