Detecting inconsistency in biological molecular databases using ontologies Chen, Qingfeng, Chen, Yi-Ping Phoebe and Zhang, Chengqi 2007, Detecting inconsistency in biological molecular databases using ontologies, Data mining and knowledge discovery, vol. 15, no. 2, pp. 275-296, doi: 10.1007/s10618-007-0071-0. Attached Files Name Description MIMEType Size Downloads Title Detecting inconsistency in biological molecular databases using ontologies Author(s) Chen, Qingfeng Chen, Yi-Ping Phoebe Zhang, Chengqi Journal name Data mining and knowledge discovery Volume number 15 Issue number 2 Start page 275 End page 296 Publisher Kluwer Academic Publishers Place of publication Boston, Mass. Publication date 2007-10 ISSN 1384-5810 1573-756X Keyword(s) data preparation inconsistency ontology measure biological molecular databases integration Summary The rapid growth of life science databases demands the fusion of knowledge from heterogeneous databases to answer complex biological questions. The discrepancies in nomenclature, various schemas and incompatible formats of biological databases, however, result in a significant lack of interoperability among databases. Therefore, data preparation is a key prerequisite for biological database mining. Integrating diverse biological molecular databases is an essential action to cope with the heterogeneity of biological databases and guarantee efficient data mining. However, the inconsistency in biological databases is a key issue for data integration. This paper proposes a framework to detect the inconsistency in biological databases using ontologies. A numeric estimate is provided to measure the inconsistency and identify those biological databases that are appropriate for further mining applications. This aids in enhancing the quality of databases and guaranteeing accurate and efficient mining of biological databases. Language eng DOI 10.1007/s10618-007-0071-0 Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2007, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30007568 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Engineering and Information Technology Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 05 Mar 2009, 13:35:21 EST Thu, 08 Apr 2010, 11:58:06 EST Thu, 15 Sep 2011, 15:56:19 EST Thu, 15 Sep 2011, 15:57:55 EST Thu, 15 Sep 2011, 15:58:35 EST Fri, 17 Oct 2014, 08:55:17 EST Filtered Full Citation counts:   Cited 6 times in TR Web of Science Cited 15 times in Scopus Search Google Scholar Access Statistics: 661 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Mon, 29 Sep 2008, 08:53:37 EST