FIK Model: Novel Efficient Granular Computing Model for Protein Sequence Motifs and Structure Information Discovery

@article{Chen2006FIKMN,
  title={FIK Model: Novel Efficient Granular Computing Model for Protein Sequence Motifs and Structure Information Discovery},
  author={Bernard Chen and Phang C. Tai and Robert W. Harrison and Yi Pan},
  journal={Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE'06)},
  year={2006},
  pages={20-26}
}
Protein sequence motifs information is very important to the analysis of biologically significant regions. The conserved regions have the potential to determine the conformation, function and activities of the proteins. The main purpose of this paper is trying to obtain protein sequence motifs which are universally conserved and across protein family boundaries. Therefore, unlike most popular motif discovering algorithms, our input dataset is extremely large. As a result, an efficient technique… CONTINUE READING

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