A modified Markov clustering approach to unsupervised classification of protein sequences

@article{Szilgyi2010AMM,
  title={A modified Markov clustering approach to unsupervised classification of protein sequences},
  author={L{\'a}szl{\'o} Szil{\'a}gyi and Lehel Medv{\'e}s and S{\'a}ndor Mikl{\'o}s Szil{\'a}gyi},
  journal={Neurocomputing},
  year={2010},
  volume={73},
  pages={2332-2345}
}

• László Szilágyi, Lehel Medvés, Sándor Miklós Szilágyi
• Published in Neurocomputing 2010
• DOI:10.1016/j.neucom.2010.02.023

In this paper we propose a modified Markov clustering algorithm for efficient and accurate clustering of large protein sequence databases, based on previously evaluated sequence similarity criteria. The proposed modification consists in an exponentially decreasing inflation rate, which aims at helping the quick creation of the hard structure of clusters by using a strong inflation in the beginning, and at producing fine partitions with a weaker inflation thereafter. The algorithm, which was… CONTINUE READING

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