Introduction to Gene Prediction Using HMM Algorithm

  • Kim, Keon-Kyun (Department of Statistics, Chonnam National University) ;
  • Park, Eun-Sik (Department of Statistics, Chonnam National University)
  • 발행 : 2007.04.30

초록

Gene structure prediction, which is to predict protein coding regions in a given nucleotide sequence, is the most important process in annotating genes and greatly affects gene analysis and genome annotation. As eukaryotic genes have more complicated structures in DNA sequences than those of prokaryotic genes, analysis programs for eukaryotic gene structure prediction have more diverse and more complicated computational models. There are Ab Initio method, Similarity-based method, and Ensemble method for gene prediction method for eukaryotic genes. Each Method use various algorithms. This paper introduce how to predict genes using HMM(Hidden Markov Model) algorithm and present the process of gene prediction with well-known gene prediction programs.

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