Fast alignment of fragmentation trees

Bioinformatics

Volumn 28, Issue 12, 2012, Pages

  Hufsky, Franziska ^a,b   Dührkop, Kai ^a   Rasche, Florian ^a   Chimani, Markus ^a   Böcker, Sebastian ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

^b MAX PLANCK INSTITUTE FOR CHEMICAL ECOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGY; FACTUAL DATABASE; MASS SPECTROMETRY; METABOLOMICS; METHODOLOGY;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; MASS SPECTROMETRY; METABOLOMICS;

EID: 84863510663     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts207     Document Type: Article

References (30)

1. Arora, S. et al. (1998). Proof verification and the hardness of approximation problems. J. ACM, 45, 501-555.
2. Backofen, R. et al. (2011). Sparse RNA folding: time and space efficient algorithms. J. Discrete Algorithms, 9, 12-31.
3. Björklund, A. et al. (2007). Fourier meets Möbius: fast subset convolution. In Proceedings of ACM Symposium on Theory of Computing (STOC 2007), ACM Press, New York, pp. 67-74.
4. Böcker, S. and Rasche, F. (2008). Towards de novo identification of metabolites by analyzing tandem mass spectra. Bioinformatics, 24, I49-I55. [Proceedings of European Conference on Computational Biology (ECCB 2008)].
5. Canzar, S. et al. (2011). On tree-constrained matchings and generalizations. In Proceedings of International Conference on Automata, Languages and Programming (ICALP 2011), Springer, Berlin, Vol. 6755, pp. 98-109.
6. Cui, Q. et al. (2008). Metabolite identification via the Madison Metabolomics Consortium Database. Nat. Biotechnol., 26, 162-164.
7. Fernie, A.R. et al. (2004). Metabolite profiling: from diagnostics to systems biology. Nat. Rev. Mol. Cell Biol., 5, 763-769.
8. Fiehn, O. (2008). Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry. Trends Analyt. Chem., 27, 261-269.
9. Halket, J.M. et al. (2005). Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS. J. Exp. Bot., 56, 219-243.
10. Herlihy, M. et al. (2008). Hopscotch hashing. In Proceedings of Symposium on Distributed Computing (DISC 2008), Springer, Berlin, Vol. 5218, pp. 350-364.
11. Hill, D.W. et al. (2008). Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra. Anal. Chem., 80, 5574-5582.
12. Horai, H. et al. (2010). MassBank: a public repository for sharing mass spectral data for life sciences. J. Mass Spectrom., 45, 703-714.
13. Jiang, T. et al. (1995). Alignment of trees: an alternative to tree edit. Theor. Comput. Sci., 143, 137-148.
14. Last, R.L. et al. (2007). Towards the plant metabolome and beyond. Nat. Rev. Mol. Cell Biol., 8, 167-174.
15. Lederberg, J. (1965). Topological mapping of organic molecules. Proc. Natl. Acad. Sci. USA, 53, 134-139.
16. Le, S.Y. et al. (1989). Tree graphs of RNA secondary structures and their comparisons. Comput. Biomed. Res., 22, 461-473.
17. Li, J.W.-H. and Vederas, J.C. (2009). Drug discovery and natural products: end of an era or an endless frontier? Science, 325, 161-165.
18. Ljubíc, I. et al. (2005). Solving the prize-collecting steiner tree problem to optimality. In Proceedings of Algorithm Engineering and Experiments (ALENEX 2005), SIAM, pp. 68-76.
19. Neumann, S. and Böcker, S. (2010). Computational mass spectrometry for metabolomics - a review. Anal. Bioanal. Chem., 398, 2779-2788.
20. Oberacher, H. et al. (2009). On the inter-instrument and inter-laboratory transferability of a tandem mass spectral reference library: 1. results of an Austrian multicenter study. J. Mass Spectrom., 44, 485-493.
21. Pagh, R. and Rodler, F.F. (2004). Cuckoo hashing. J. Algorithms, 51, 122-144.
22. Rasche, F. et al. (2011). Computing fragmentation trees from tandem mass spectrometry data. Anal. Chem., 83, 1243-1251.
23. Rasche, F. et al. (2012). Identifying the unknowns by aligning fragmentation trees. Anal. Chem., 84, 3417-3426.
24. Rauf, I. et al. (2012). Finding maximum colorful subtrees in practice. In Proceedings of Research in Computational Molecular Biology (RECOMB 2012). Springer, Berlin, Vol. 7262, pp. 213-223.
25. Scheubert, K. et al. (2011). Computing fragmentation trees from metabolite multiple mass spectrometry data. In Proceedings of Research in Computational Molecular Biology (RECOMB 2011), Vol. 6577, pp. 377-391.
26. Schmidt, B.M. et al. (2007). Revisiting the ancient concept of botanical therapeutics. Nat. Chem. Biol., 3, 360-366.
27. Sniedovich, M. (2006). Dijkstra's algorithm revisited: the dynamic programming connexion. Control Cybern., 35, 599-620.
28. Werner, E. et al. (2008). Mass spectrometry for the identification of the discriminating signals from metabolomics: current status and future trends. J. Chromatogr. B, 871, 143-163.
29. Zhang, K. and Jiang, T. (1994). Some MAX SNP-hard results concerning unordered labeled trees. Inf. Process. Lett., 49, 249-254.
30. Zhang, K. (1996). A constrained edit distance between unordered labeled trees. Algorithmica, 15, 205-222.