New PDF release: Algorithms in Bioinformatics: 15th International Workshop,

By Mihai Pop, Hélène Touzet

ISBN-10: 3662482207

ISBN-13: 9783662482209

ISBN-10: 3662482215

ISBN-13: 9783662482216

This ebook constitutes the refereed court cases 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 reviews, 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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A) Results for the five NCF-AS methods on best alignments of “synthetic” (noisy yeast) networks. (b) Results for the five NCF-AS methods on best alignments of real-world PPI networks of different species. Details (per network pair and alignment quality measure) for panels (a)-(b) are shown in Figs. 5. Recall that M-M and G-G are MI-GRAAL and GHOST. Y. Sun et al. 2 0 0 -W G -G G -M G -W M -M M -M -W G -G G -M G -W M M Aligner Aligner (a) (b) 100 90 80 70 60 50 40 30 20 100 Exp-GO(%) 90 LCCS(%) 100 90 80 70 60 50 40 30 20 10 0 S3(%) NC(%) Fig.

Then, its NCF computes topological distance (or equivalently, similarity) between two nodes by comparing the nodes’ “spectral signatures”. We recently fairly compared MI-GRAAL’s GDV-similarity-based NCF with GHOST’s “spectral signature”-based NCF within our above mix-andmatch framework, concluding that MI-GRAAL’s NCF is superior or comparable to GHOST’s NCF, depending on data [42]. Hence, since none of the two NCFs was dominant in all cases, we consider both NCFs in our study. Just as MIGRAAL, GHOST also allows for integration of protein sequence information into its NCF.

MAGNA does). As more biological network data are becoming available, network alignment will only continue to gain importance in the computational biology domain [41,55,56]. For example, network alignment has already redefined the notion of sequence-based orthology to the notion of network-based orthology, as it can identify conserved network (rather than sequence) regions between different species [57]. , aging-related) knowledge from well-studied model species to poorly-studied species such as human.

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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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