Data structures and network algorithms
Data structures and network algorithms
Approximate string-matching with q-grams and maximal matches
Theoretical Computer Science - Selected papers of the Combinatorial Pattern Matching School
Change-Centric Management of Versions in an XML Warehouse
Proceedings of the 27th International Conference on Very Large Data Bases
A New Editing based Distance between Unordered Labeled Trees
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
Detecting Changes in XML Documents
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A three-way merge for XML documents
Proceedings of the 2004 ACM symposium on Document engineering
RWS-Diff: flexible and efficient change detection in hierarchical data
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Genome sequence data and annotations are subject to frequent changes resulting from re-assembly and re-annotation, or community feedback based on experimental evidence, giving rise to new data releases. These releases are rarely accompanied by a description of the changes, making it difficult for biologists working with the data to identify and work through the consequences of the changes that have taken place. This paper explores the extent to which existing XML difference algorithms, namely X-Diff, JXyDiff and 3DM, can be used to identify and document genome changes, in particular investigating: (i) their ability to detect typical changes in genome sequence documents; and (ii) the ease with which the difference report can be used to determine whether genes of interest are affected by changes to the genome. The evaluation compares the performance of the algorithms both with synthetic modifications and for detecting changes in a public genomic database. Typical behaviours of the algorithms are identified and a root cause analysis carried out.