Publication:
Interactive Data Mining for Molecular Graphs

dc.contributor.authorYılmaz, Burcu
dc.contributor.authorGöktürk, Mehmet
dc.contributor.authorIDTR104973tr_TR
dc.date.accessioned2016-05-04T12:57:08Z
dc.date.available2016-05-04T12:57:08Z
dc.date.issued2009
dc.description.abstractDesigning new medical drugs for a specific disease requires extensive analysis of many molecules that have an activity for the disease. The main goal of these extensive analyses is to discover substructures (fragments) that account for the activity of these molecules. Once they are discovered, these fragments are used to understand the structure of new drugs and design new medicines for the disease. In this paper, we propose an interactive approach for visual molecule mining to discover fragments of molecules that are responsible for the desired activity with respect to a specific disease. Our approach visualizes molecular data in a form that can be interpreted by a human expert. Using a pipelining structure, it enables experts to contribute to the solution with their expertise at different levels. In order to derive desired fragments, it combines histogram-based filtering and clustering methods in a novel way. This combination enables a flexible determination of frequent fragments that repeat in molecules exactly or with some variations. Copyright (C) 2009 B. Yilmaz and M. Gokturk.tr_TR
dc.identifier.issn1463-9246
dc.identifier.scopus2-s2.0-75749102956
dc.identifier.urihttp://hdl.handle.net/11413/1277
dc.identifier.wos273318700001
dc.language.isoen
dc.publisherHindawi Publishing Corp, 410 Park Avenue, 15Th Floor, #287 Pmb, New York, Ny 10022 Usa
dc.relationJournal Of Automated Methods & Management In Chemistrytr_TR
dc.titleInteractive Data Mining for Molecular Graphstr_TR
dc.typeArticle
dspace.entity.typePublication
local.indexed.atWOS
local.indexed.atScopus

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