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A Biological Compression Model and Its Applications

  • Minh Duc Cao
  • Trevor I. Dix
  • Lloyd Allison
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 696)

Abstract

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

Keywords

Mutual Information Information Content Compression Algorithm Repeat Element Biological Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Clayton School of Information TechnologyMonash UniversityClaytonAustralia

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