Pavel A. Pevzner (auth.), Raffaele Giancarlo, Sridhar's Algorithms in Bioinformatics: 7th International Workshop, PDF

By Pavel A. Pevzner (auth.), Raffaele Giancarlo, Sridhar Hannenhalli (eds.)

ISBN-10: 3540741259

ISBN-13: 9783540741251

This booklet constitutes the refereed court cases of the seventh foreign Workshop on Algorithms in Bioinformatics, WABI 2007, held in Philadelphia, PA, united states in September 2007.

The 38 revised complete papers provided including the summary of a keynote speak have been conscientiously reviewed and chosen from 133 submissions. All present problems with algorithms in bioinformatics are addressed, starting from mathematical instruments to experimental reports of approximation algorithms and stories on major computational analyses. a number of organic difficulties are handled, together with genetic mapping, series alignment and series research, phylogeny, comparative genomics, and protein constitution. in addition the papers function high-performance computing ways to computationally demanding studying and optimization difficulties in bioinformatics and canopy tools, software program and dataset repositories for improvement and trying out of such algorithms and their underlying models.

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Additional info for Algorithms in Bioinformatics: 7th International Workshop, WABI 2007, Philadelphia, PA, USA, September 8-9, 2007. Proceedings

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80–85. : Svm-prot: Web-based support vector machine software for functional classification of a protein from its primary sequence. Nucleic Acids Res. : The pfam protein families database. Nucleic Acids Res. : Using a mixture of probabilistic decision trees for direct prediction of protein function. In: Proceedings of RECOMB, pp. : Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. : An improved hidden markov model for transmembrane protein detection and topology prediction and its applications to complete genomes.

To the purpose of this investigation we introduce three different classes of random errors: general errors, errors on contacts (that is errors on 1-entries of contact maps) and errors on non-contacts (that is errors on 0-entries of contact maps). We perform extensive tests of the reconstruction quality of our algorithm on a set of 120 nonredundant protein chains and compare the reconstruction performances in terms Fault Tolerance for Large Scale Protein 3D Reconstruction 27 of RMSD on the three classes of errors introduced.

This is done in order to simulate possible scenarios of reconstruction from predicted (and therefore highly noised) contact maps. From our analysis we obtain that our algorithm performs better reconstructions on blurred contact maps when contacts are under predicted than over predicted. Moreover we modify the algorithm into FTCOMAR [Fault Tolerant-COMAR] in order to use it with incomplete contact maps. FT-COMAR can ignore up to 75% of the contact map and still recover from the remaining 25% entries a 3D structure whose root mean square deviation (RMSD) from the native one is less then 4 Å.

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Algorithms in Bioinformatics: 7th International Workshop, WABI 2007, Philadelphia, PA, USA, September 8-9, 2007. Proceedings by Pavel A. Pevzner (auth.), Raffaele Giancarlo, Sridhar Hannenhalli (eds.)


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