By Yelena Frid, Dan Gusfield (auth.), Vincent Moulton, Mona Singh (eds.)
This publication constitutes the refereed complaints of the tenth foreign Workshop on Algorithms in Bioinformatics, WABI 2010, held in Liverpool, united kingdom, in September 2010. The 30 revised complete papers awarded have been rigorously reviewed and chosen from eighty three submissions. The papers are geared up in topical sections on biomolecular constitution: RNA, protein and molecular comparability; comparative genomics; haplotype and genotype research; high-throughput information research: subsequent new release sequencing and move cytometry; networks; phylogenetics; and sequences, strings and motifs.
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Additional info for Algorithms in Bioinformatics: 10th International Workshop, WABI 2010, Liverpool, UK, September 6-8, 2010. Proceedings
Performance analysis. Our method is robust and consistent (Fig 3A,B). The consistency and accuracy of our method depends on the extent of correlation between the features. Correlation between structures that are truly variable and ones variable due to noise, will make the regression convoluted; diﬀerent regularization penalties (λ) will select diﬀerent structures, leading to highly varying regression weights . e. conformations in the ensemble) are uncorrelated to a large extent (Fig 3A), indicated by the overall smooth trends for ω as we increase the regularization penalty λ.
Vp-trees are based on vantage points, stored in the inner nodes of the trees . Each node has two subtrees: one for the points closest to the nodes vantage point, and one for those further away. Figure 2b illustrates a vp-tree on a set of points, with p1 as the vantage point. vp-trees are constructed by recursively selecting vantage points and splitting the points into two subsets according to their distance from the vantage points. Each node stores the vantage point p along with the vantage point radius pr within which all the closest points are located.
Vectors are often used for representing molecular structures when searching for chemical compounds with similar properties. The entries of these vectors can be binary, in which case they are referred to as ﬁngerprints, or real valued, in which case they are referred to as descriptors. A diverse set of similarity measures are available for dealing with these vectors . This study focuses on the Tanimoto coeﬃcient, which is applicable to ﬁngerprints as well as descriptors. V. Moulton and M. ): WABI 2010, LNBI 6293, pp.
Algorithms in Bioinformatics: 10th International Workshop, WABI 2010, Liverpool, UK, September 6-8, 2010. Proceedings by Yelena Frid, Dan Gusfield (auth.), Vincent Moulton, Mona Singh (eds.)