Finding Maximum Colorful Subtrees in Practice

  • Imran Rauf
  • Florian Rasche
  • François Nicolas
  • Sebastian Böcker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7262)


In metabolomics and other fields dealing with small compounds, mass spectrometry is applied as sensitive high-throughput technique. Recently, fragmentation trees have been proposed to automatically analyze the fragmentation mass spectra recorded by such instruments. Computationally, this leads to the problem of finding a maximum weight subtree in an edge weighted and vertex colored graph, such that every color appears at most once in the solution.

We introduce new heuristics and an exact algorithm for this Maximum Colorful Subtree problem, and evaluate them against existing algorithms on real-world datasets. Our tree completion heuristic consistently scores better than other heuristics, while the integer programming-based algorithm produces optimal trees with modest running times. Our fast and accurate heuristic can help to determine molecular formulas based on fragmentation trees. On the other hand, optimal trees from the integer linear program are useful if structure is relevant, e.g., for tree alignments.


Directed Acyclic Graph Integer Linear Program Tandem Mass Spectrum Input Graph Greedy Heuristic 
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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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Imran Rauf
    • 1
  • Florian Rasche
    • 2
  • François Nicolas
    • 2
  • Sebastian Böcker
    • 2
  1. 1.Department of Computer ScienceUniversity of KarachiKarachiPakistan
  2. 2.Lehrstuhl für BioinformatikFriedrich-Schiller-Universität JenaJenaGermany

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