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Graph-kernels for the comparative analysis of protein active sites

dc.contributor.authorFober, Thomas
dc.contributor.authorMernberger, Marco
dc.contributor.authorMoritz, Ralph
dc.contributor.authorHüllermeier, Eyke
dc.contributor.editorGrosse, Ivo
dc.contributor.editorNeumann, Steffen
dc.contributor.editorPosch, Stefan
dc.contributor.editorSchreiber, Falk
dc.contributor.editorStadler, Peter
dc.date.accessioned2019-02-20T09:48:30Z
dc.date.available2019-02-20T09:48:30Z
dc.date.issued2009
dc.description.abstractGraphs are often used to describe and analyze the geometry and physicochemical composition of biomolecular structures, such as chemical compounds and protein active sites. A key problem in graph-based structure analysis is to define a measure of similarity that enables a meaningful comparison of such structures. In this regard, so-called kernel functions have recently attracted a lot of attention, especially since they allow for the application of a rich repertoire of methods from the field of kernel-based machine learning. Most of the existing kernel functions on graph structures, however, have been designed for the case of unlabeled and/or unweighted graphs. Since proteins are often more naturally and more exactly represented in terms of node-labeled and edge-weighted graphs, we propose corresponding extensions of existing graph kernels. Moreover, we propose an instance of the substructure fingerprint kernel suitability for the analysis of protein binding sites. The performance of these kernels is investigated by means of an experimental study in which graph kernels are used as similarity measures in the context of classification.en
dc.identifier.isbn978-3-88579-251-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/20306
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofGerman conference on bioinformatics 2009
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-157
dc.titleGraph-kernels for the comparative analysis of protein active sitesen
dc.typeText/Conference Paper
gi.citation.endPage31
gi.citation.publisherPlaceBonn
gi.citation.startPage21
gi.conference.date28th to 30th September 2009
gi.conference.locationHalle-Wittenberg
gi.conference.sessiontitleRegular Research Papers

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