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Improved Automated Reaction Mapping

  • Tina Kouri
  • Dinesh Mehta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6630)

Abstract

Automated reaction mapping is an important tool in cheminformatics where it may be used to classify reactions or validate reaction mechanisms. The reaction mapping problem is known to be NP-Complete and may be formulated as an optimization problem. In this paper we present three algorithms that continue to obtain optimal solutions to this problem, but with significantly improved runtimes over the previous CCV algorithm. Our algorithmic improvements include (a) the use of a fast (but not 100% accurate) canonical labeling algorithm, (b) name reuse (i.e., storing intermediate results rather than recomputing), and (c) an incremental approach to canonical name computation. Experimental results on chemical reaction databases demonstrate our 2-CCV NR FDN algorithm usually performs over ten times faster than previous fastest automated reaction mapping algorithms.

Keywords

Applied Algorithms Automated Reaction Mapping Cheminformatics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tina Kouri
    • 1
  • Dinesh Mehta
    • 1
  1. 1.Colorado School of MinesUSA

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