A Genetic Algorithm for Simplifying the Amino Acid Alphabet in Bioinformatics Applications

M. Palensky and H. Ali (USA)


Genetic Algorithms, Protein Sequences, Bioinformatics, Amino Acid Alphabet


Simplifying the representation of protein sequences have been receiving considerable attention in recent years since having a simplified representation will potentially allow for the ability to tackle difficult problems such as the prediction of protein interaction. A central problem in creating simplified amino acid alphabets is narrowing down the massive number of possible simplifications. Since considering all possible simplifications is intractable, effectively creating simplified alphabets is essential. Genetic algorithms have been effective in providing near-optimal solutions for similar combinatorial problems with large solution spaces. This makes them a good candidate for creating simplified alphabets. Simplified amino acid alphabets could uncover hidden relationships in protein sequences, and in turn provide a valuable first step in solving protein-related microbiological problems. Simplifying amino acid alphabets may potentially reduce the degree of complexity for several difficult problems such as protein prediction interaction and protein structure prediction.

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