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Using Em-Algorithm for Gene Classification


The EM algorithm is considered for the problem of separation of distribution mixtures described by Markov chains, together with the related weighted likelihood maximization problem. Auxiliary algorithms are proposed to select the initial approximation and optimal number of mixture components, as well as a method to approximate the distribution mixture with given data using support vector machines. The results are applied to gene fragment classification.

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Correspondence to I. V. Sergienko.

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Translated from Kibernetika i Sistemnyi Analiz, No. 1, January–February, 2015, pp. 48–58.

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Sergienko, I.V., Gupal, A.M. & Ostrovskiy, A.V. Using Em-Algorithm for Gene Classification. Cybern Syst Anal 51, 41–50 (2015).

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  • Markov chain
  • classification
  • gene
  • bioinformatics
  • nucleotide
  • exon
  • intron
  • likelihood