Paper Info
Title
Analyzing Inconsistency Toward Enhancing Integration of Biological Molecular Databases
Abstract
The rapid growth of biological databases not only provides biologists with abundant data but also presents a big challenge in relation to the analysis of data. Many data analysis approaches such as data mining, information retrieval and machine learning have been used to extract frequent patterns from diverse biological databases. However, the discrepancies, due to the differences in the structure of databases and their terminologies, result in a significant lack of interoperability. Although ontology-based approaches have been used to integrate biological databases, the inconsistent analysis of biological databases has been greatly disregarded. This paper presents a method by which to measure the degree of inconsistency between biological databases. It not only presents a guideline for correct and efficient database integration, but also exposes high quality data for data mining and knowledge discovery.
Year
DOI
Venue
2006
10.1142/9781860947292_0023
Series on Advances in Bioinformatics and Computational Biology
Keywords
Field
DocType
information retrieval,knowledge discovery,data analysis,machine learning,data mining,biological database,database integration
Data integration,Ontology,Data analysis,Information retrieval,Computer science,Biological database,Database testing,Knowledge extraction,Bioinformatics,Database theory,Probabilistic database
Conference
Volume
ISSN
Citations 
3
1751-6404
1
PageRank 
References 
Authors
0.37
6
2
Name
Order
Citations
PageRank
Yi-ping Phoebe Chen11060128.42
Qingfeng Chen2653.82