IDA - Intelligent Data Analysis Research Group

BibTeX Entry

  category = {ida-publications},
  author = {Kubal{\'i}k J.},
  title = {Solving the Multiple Sequence Alignment Problem Using Prototype Optimization with Evolved Improvement Steps},
  booktitle = {Adaptive and Natural Computing Algorithms},
  year = {2009},
  publisher = {Heidelberg: Springer},
  pages = {183--192},
  url = {},
  abstract = {This paper deals with a Multiple Sequence Alignment problem, for which an implementation of the Prototype Optimization with Evolved Improvement Steps (POEMS) algorithm has been proposed. The key feature of the POEMS is that it takes some initial solution, which is then iteratively improved by means of what we call evolved hypermutations. In this work, the POEMS is seeded with a solution provided by the Clustal X algorithm. Major result of the presented experiments was that the proposed POEMS implementation performs significantly better than the other two compared algorithms, which rely on random hypermutations only. Based on the carried out analyses we proposed two modifications of the POEMS algorithm that might further improve its performance.},
  vvvs = {0},

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