Promoter Prediction with a GP-Automaton

  • Daniel Howard
  • Karl Benson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2611)


A GP-automaton evolves motif sequences for its states; it moves the point of motif application at transition time using an integer that is stored and evolved in the transition; and it combines motif matches via logical functions that it also stores and evolves in each transition. This scheme learns to predict promoters in human genome. The experiments reported use 5-fold cross validation.


Finite State Automaton Promoter Prediction Halt State Bacterial Promoter Finite State Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Daniel Howard
    • 1
  • Karl Benson
    • 1
  1. 1.Software Evolution Centre, Knowledge and Information Systems Division, QinetiQ LtdMalvern Technology CentreMalvernUK

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