Literature DB >> 14668226

SEMEDA: ontology based semantic integration of biological databases.

Jacob Köhler1, Stephan Philippi, Matthias Lange.   

Abstract

MOTIVATION: Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases.
RESULTS: In this publication, principles and methods that were used to implement SEMEDA (Semantic Meta Database) are described. Database owners can use SEMEDA to provide semantically integrated access to their databases as well as to collaboratively edit and maintain ontologies and controlled vocabularies. Biologists can use SEMEDA to query the integrated databases in real time without having to know the structure or any technical details of the underlying databases. AVAILABILITY: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.

Mesh:

Year:  2003        PMID: 14668226     DOI: 10.1093/bioinformatics/btg340

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  16 in total

1.  Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics.

Authors:  Jingshan Huang; Dejing Dou; Jiangbo Dang; J Harold Pardue; Xiao Qin; Jun Huan; William T Gerthoffer; Ming Tan
Journal:  World J Biol Chem       Date:  2012-02-26

Review 2.  The ACGT Master Ontology and its applications--towards an ontology-driven cancer research and management system.

Authors:  Mathias Brochhausen; Andrew D Spear; Cristian Cocos; Gabriele Weiler; Luis Martín; Alberto Anguita; Holger Stenzhorn; Evangelia Daskalaki; Fatima Schera; Ulf Schwarz; Stelios Sfakianakis; Stephan Kiefer; Martin Dörr; Norbert Graf; Manolis Tsiknakis
Journal:  J Biomed Inform       Date:  2010-05-11       Impact factor: 6.317

3.  Quality control for terms and definitions in ontologies and taxonomies.

Authors:  Jacob Köhler; Katherine Munn; Alexander Rüegg; Andre Skusa; Barry Smith
Journal:  BMC Bioinformatics       Date:  2006-04-19       Impact factor: 3.169

Review 4.  Database resources in metabolomics: an overview.

Authors:  Eden P Go
Journal:  J Neuroimmune Pharmacol       Date:  2009-05-07       Impact factor: 4.147

5.  Automated database mediation using ontological metadata mappings.

Authors:  Luis Marenco; Rixin Wang; Prakash Nadkarni
Journal:  J Am Med Inform Assoc       Date:  2009-06-30       Impact factor: 4.497

6.  semCDI: a query formulation for semantic data integration in caBIG.

Authors:  E Patrick Shironoshita; Yves R Jean-Mary; Ray M Bradley; Mansur R Kabuka
Journal:  J Am Med Inform Assoc       Date:  2008-04-24       Impact factor: 4.497

7.  How to Develop a Drug Target Ontology: KNowledge Acquisition and Representation Methodology (KNARM).

Authors:  Hande Küçük McGinty; Ubbo Visser; Stephan Schürer
Journal:  Methods Mol Biol       Date:  2019

Review 8.  Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned.

Authors:  Daniel E Sullivan; Joseph L Gabbard; Maulik Shukla; Bruno Sobral
Journal:  Chem Biodivers       Date:  2010-05       Impact factor: 2.408

9.  Ultra-Structure database design methodology for managing systems biology data and analyses.

Authors:  Christopher W Maier; Jeffrey G Long; Bradley M Hemminger; Morgan C Giddings
Journal:  BMC Bioinformatics       Date:  2009-08-19       Impact factor: 3.169

10.  Ontologies for bioinformatics.

Authors:  Nadine Schuurman; Agnieszka Leszczynski
Journal:  Bioinform Biol Insights       Date:  2008-03-12
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