Evolving turing machines for biosequence recognition and analysis

© Springer-Verlag Berlin Heidelberg 2001. This article presents a genetic programming system for biose- quence recognition and analysis. In our model, a population of Turing machines evolves the capability of biosequence recognition using genetic algorithms. We use HIV biosequences as the working example. Exper- imental results indicate that evolved Turing machines are capable of recognizing HIV biosequences in a collection of training sets. In addi- tion, we demostrate that the evolved Turing machines can be used to approximate the multiple sequence alignment problem.

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