Finding maximum colorful subtrees in practice

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Abstract

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. © 2012 Springer-Verlag Berlin Heidelberg.

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APA

Rauf, I., Rasche, F., Nicolas, F., & Böcker, S. (2012). Finding maximum colorful subtrees in practice. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7262 LNBI, pp. 213–223). https://doi.org/10.1007/978-3-642-29627-7_22

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