The representation of biological data as text information opened new perspectives in the evolution of biological research. Many biological sequence databases are providing detailed information about sequences allowing investigations like searches, comparison, the establishment of relations between different sequences and species. The algorithmic procedures used for data sequence analysis are coming from many areas of computational sciences. Within this book chapter, we are bringing together a diversity of language engineering techniques and those involving information theoretic principles in analyzing protein sequences from similarity perspective. After we are proposing a state of the art in the subject, presenting a survey of the different approaches identified, the attention is oriented to the two methods we experimented. The description of these methods and the experiments performed open discussions addressed to the interested reader that may think about new ideas of improvement.
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Bogan-Marta, A., Hategan, A., Pitas, I. (2008). Language engineering and information theoretic methods in protein sequence similarity studies. In: Kelemen, A., Abraham, A., Liang, Y. (eds) Computational Intelligence in Medical Informatics. Studies in Computational Intelligence, vol 85. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75767-2_8
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