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Download e-book for kindle: Algorithms in Bioinformatics: 15th International Workshop, by Mihai Pop, Hélène Touzet

By Mihai Pop, Hélène Touzet

ISBN-10: 3662482207

ISBN-13: 9783662482209

ISBN-10: 3662482215

ISBN-13: 9783662482216

This e-book constitutes the refereed complaints of the fifteenth foreign Workshop on Algorithms in Bioinformatics, WABI 2015, held in Atlanta, GA, united states, in September 2015. The 23 complete papers provided have been conscientiously reviewed and chosen from fifty six submissions. the chosen papers conceal a variety of issues from networks to phylogenetic stories, series and genome research, comparative genomics, and RNA structure.

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Extra info for Algorithms in Bioinformatics: 15th International Workshop, WABI 2015, Atlanta, GA, USA, September 10-12, 2015, Proceedings

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5 (or any other combination that considers some level of edge conservation). 5 (or equivalently βn = 1 and βe = 1), which equally favors node and edge conservation. Due to a large number of tests involved into evaluating different combinations of βn and βe values, all experiments in this section have been performed only on topology-only alignments of “synthetic” (noisy yeast) networks. 7 / 25 0. 5 0 5/ 5 0. 2 / 75 0. 7 / 25 0. 5 0 5/ 5 0. 2 / 75 0. 7 / 25 0. 5 0 5/ 5 0. 2 / 75 0. 0 1/ βn/βe 29 βn/βe βn/βe (b) (c) Fig.

2 in the Appendix). In summary, over both network sets (with known and unknown node mapping), both topology-only and best alignments, and all alignment quality measures, the edge-weighted version of WAVE is overall (though not always) superior to the edge-unweighted version. 84 %) for best alignments (Table 1). Interestingly, superiority of the edge-weighted version of WAVE becomes more pronounced with increase of noise in the data, especially for topology-only alignments (we base this conclusion only on “synthetic” (noisy yeast) networks for which we know the level of noise in the data).

1 Comparison of Edge-Weighted and Edge-Unweighted Versions of WAVE Here, we compare the edge-weighted and edge-unweighted versions of WAVE. We find that weighing conserved edges in general improves alignment quality (Figs. 1 and 2, as well as Figs. 2 in the Appendix), as follows. Networks with Known Node Mapping Topological Alignments. Weighing conserved edges improves alignment quality of topology-only alignments under both MI-GRAAL’s and GHOST’s NCFs, since the edge-weighted version of WAVE is comparable or superior to the edgeunweighted version in the majority of cases across all alignments and all alignment quality measures (Fig.

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Algorithms in Bioinformatics: 15th International Workshop, WABI 2015, Atlanta, GA, USA, September 10-12, 2015, Proceedings by Mihai Pop, Hélène Touzet

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