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BioDIFF: An Effective Fast Change Detection Algorithm for Biological Annotations

Warehousing heterogeneous, dynamic biological data is a key technique for biological data integration as it greatly improves performance. However, it requires complex maintenance procedures to update the warehouse in light of the changes to the sources. Consequently, a key issue to address is how to...

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Detalles Bibliográficos
Autores principales: Song, Yang, Bhowmick, Sourav S., Dewey, C. Forbes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121968/
http://dx.doi.org/10.1007/978-3-540-71703-4_25
Descripción
Sumario:Warehousing heterogeneous, dynamic biological data is a key technique for biological data integration as it greatly improves performance. However, it requires complex maintenance procedures to update the warehouse in light of the changes to the sources. Consequently, a key issue to address is how to detect changes to the underlying biological data sources. In this paper, we present an algorithm called BioDiff for detecting exact changes to biological annotations. In our approach we transform heterogeneous biological data to XML format and then detect changes between two versions of XML representation of biological data. Our algorithm extends X-Diff, a published XML change detection algorithm. X-Diff, being designed for any type of XML data, does not exploit the semantics of biological data to reduce the data set of bipartite mapping. We have implemented BioDiff in Java. We have conducted an extensive performance study using data from EMBL, GenBank, SwissProt and PDB. Our experimental results show that BioDiff runs 1.5 to 6 times faster than X-Diff.