Paper Info
Title
BioRegistry: automatic extraction of metadata for biological database retrieval and discovery
Abstract
Biological databases are blooming today at an increasing rate to deal with the huge amount of data produced by genomic and post-genomic research. The need for a well-maintained searchable directory is therefore an important issue for a good exploitation of these databases. The BioRegistry repository is automatically generated from a publicly available list of biological databases (The Molecular Biology Database Collection published in Nucleic Acids Research) and aims at associating content metadata with each database in view of database retrieval and/or discovery. Such content metadata are either simple keywords or terms belonging to a medical thesaurus. Querying modalities including a search by semantic similarity are described. The use of conceptual clustering methods is proposed to build a semantic classification of biological databases enabling browsing through the BioRegistry repository and discovering previously unknown databases.
Year
DOI
Venue
2008
10.1145/1497308.1497392
International Conference on Information Integration and Web-based Applications & Services (IIWAS)
Keywords
Field
DocType
semantic similarity,content metadata,biological databases,querying modality,conceptual clustering,bioregistry repository,semantic classification,molecular biology database collection,automatic extraction,resource discovery,unknown databases,database retrieval,nucleic acids research,biological database retrieval,metadata,nucleic acid,biological database,molecular biology
Data mining,Directory,Computer science,Conceptual clustering,Semantic similarity,Metadata,World Wide Web,Information retrieval,Biological database,Formal concept analysis,Database,Semantics,Database catalog
Conference
Citations 
PageRank 
References 
4
0.46
17
Authors
5
Name
Order
Citations
PageRank
Marie-Dominique Devignes121323.87
Philippe Franiatte260.82
Nizar Messai310619.26
Amedeo Napoli41180135.52
Malika Smaïl-Tabbone58613.49