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Speedy Colorful Subtrees

  • W. Timothy J. White
  • Stephan Beyer
  • Kai Dührkop
  • Markus Chimani
  • Sebastian Böcker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9198)

Abstract

Fragmentation trees are a technique for identifying molecular formulas and deriving some chemical properties of metabolites—small organic molecules—solely from mass spectral data. Computing these trees involves finding exact solutions to the NP-hard Maximum Colorful Subtree problem. Existing solvers struggle to solve the large instances involved fast enough to keep up with instrument throughput, and their performance remains a hindrance to adoption in practice.

We attack this problem on two fronts: by combining fast and effective reduction algorithms with a strong integer linear program (ILP) formulation of the problem, we achieve overall speedups of 9.4 fold and 8.8 fold on two sets of real-world problems—without sacrificing optimality. Both approaches are, to our knowledge, the first of their kind for this problem. We also evaluate the strategy of solving global problem instances, instead of first subdividing them into many candidate instances as has been done in the past. Software (C++ source for our reduction program and our CPLEX/Gurobi driver program) available under LGPL at https://github.com/wtwhite/speedy_colorful_subtrees/.

Keywords

Molecular Formula Integer Linear Program Full Version Reduction Rule Incoming Edge 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • W. Timothy J. White
    • 1
  • Stephan Beyer
    • 2
  • Kai Dührkop
    • 1
  • Markus Chimani
    • 2
  • Sebastian Böcker
    • 1
  1. 1.Chair for BioinformaticsFriedrich-Schiller-UniversityJenaGermany
  2. 2.Institute of Computer ScienceUniversity of OsnabrückOsnabrückGermany

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