Mining, compressing and classifying with extensible motifs
2006
Using Extensible Motifs for Data Compression and Classification
publication
Evidence: moderate
Author Information
Author(s): Alberto Apostolico, Matteo Comin, Laxmi Parida
Primary Institution: Dipartimento di Ingegneria dell'lnformazione, Università di Padova, Padova, Italy
Hypothesis
Can extensible motifs improve data compression and classification of biological sequences?
Conclusion
Off-line compression based on extensible motifs can be used advantageously to compress and classify biological sequences.
Supporting Evidence
- Extensible motifs improve compression ratios compared to rigid motifs.
- The method can classify biological sequences without alignment.
- The study tested the method on protein sequences from the PROSITE repository.
Takeaway
This study shows that using flexible patterns called extensible motifs can help make biological data smaller and easier to sort.
Methodology
The study used off-line data compression techniques by textual substitution based on extensible motifs.
Digital Object Identifier (DOI)
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