By Markus T. Friberg, Pedro Gonnet, Yves Barral (auth.), Philipp Bücher, Bernard M. E. Moret (eds.)

This e-book constitutes the refereed lawsuits of the sixth foreign Workshop on Algorithms in Bioinformatics, WABI 2006, held in Zurich, Switzerland in September 2006 throughout the ALGO 2006 convention meetings.

The 36 revised complete papers provided have been conscientiously reviewed and chosen from a hundred submissions. All present problems with algorithms in bioinformatics are addressed, starting from mathematical instruments to experimental reports of approximation algorithms and studies on major computational analyses. The papers care for a number of organic difficulties, together with genetic mapping, series alignment and series research, phylogeny, comparative genomics, and protein constitution. For the 1st time, assurance extends to machine-learning techniques besides combinatorial optimization.

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Extra info for Algorithms in Bioinformatics: 6th International Workshop, WABI 2006, Zurich, Switzerland, September 11-13, 2006. Proceedings

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Schur’s Theorem [13] states that the number of decompositions of an integer M over {b1 , . . , bm } grows with a polynomial in M of degree m − 1. Since the ER-algorithm of [2] runs in time proportional to the number of decompositions, and the number of solutions of the bottom equation is considerably lower than of any of the original equations, we improve on runtime. However, even though we can guarantee that all entries of R are integers, some could be negative, yielding infinitely many solutions.

A. Yergey. A general approach to calculating isotopic distributions for mass spectrometry. Int. J. Mass Spectrom. , 52(2–3):337–349, 1983. 15. N. Zhang, R. Aebersold, and B. Schwikowski. ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Proteomics, 2(10):1406–1412, 2002. 16. W. T. Chait. ProFound: an expert system for protein identification using mass spectrometric peptide mapping information. Anal. , 72(11):2482– 2489, 2000.

Nevertheless, our results are only a first step towards automated determination of sum formula from high resolution mass spectrometry data. We want to conduct further studies regarding mass and intensity variations and are currently gathering an independent test set of about 100 sample spectra. Note that we have deliberately ignored some information available in the data, in order to evaluate the discriminative power of a single isotope pattern, such as different charge states, prior probability of the elements, or neutral losses.

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