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dc.contributor.authorHess, Martinen_US
dc.contributor.authorJente, Danielen_US
dc.contributor.authorWiemeyer, Josefen_US
dc.contributor.authorHamacher, Kayen_US
dc.contributor.authorGoesele, Michaelen_US
dc.contributor.editorStefan Bruckner and Bernhard Preim and Anna Vilanova and Helwig Hauser and Anja Hennemuth and Arvid Lundervolden_US
dc.date.accessioned2016-09-07T05:37:23Z
dc.date.available2016-09-07T05:37:23Z
dc.date.issued2016
dc.identifier.isbn978-3-03868-010-9
dc.identifier.issn2070-5786
dc.identifier.urihttp://dx.doi.org/10.2312/vcbm.20161268
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20161268
dc.description.abstractMultiple Sequence Alignments (MSA) of a set of DNA, RNA or protein sequences form the fundamental basis for various biological applications such as evolutionary heritage and protein structure prediction. The quality of an MSA is crucial in order to provide useful and correct results. The analysis of MSAs is, however, still a challenging task since constructing MSAs is an NP hard problem and thus the optimal MSA is usually unknown. Additionally, MSA quality analysis is often completely ignored, especially by non-expert users, due to the lack of tools for the visual comparison and the intuitive quality assessment of alignments. In this paper, we present an interactive visual approach to simultaneously assess the quality of multiple alternative MSAs of the same set of sequences. We provide a direct assessment of the alignment quality using different highlighting techniques in combination with automatic quality measures and editing capabilities. An in-depth evaluation of our approach highlights its benefits for MSA quality assessment.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.1.2 [Information Systems]
dc.subjectUser/Machine Systems
dc.subjectHuman information processing
dc.subjectJ.3 [Computer Applications]
dc.subjectLife and Medical Sciences
dc.subjectBiology and genetics
dc.titleVisual Analysis and Comparison of Multiple Sequence Alignmentsen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.description.sectionheadersVisual Exploration and Analysis of Biological Data
dc.identifier.doi10.2312/vcbm.20161268
dc.identifier.pages31-40


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