Genetic programming for protein related text classification

Since the genomics revolution, bioinformatics has never been so popular. Many researchers have investigated with great success the use of evolutionary computation in bioinformatics [19] for example in the field of protein folding or determining genome sequences. In this paper, instead of using evolutionary computation as a way to provide new and innovative solutions to complex bioinformatics problems, we use genetic programming as a tool to evolve programs that are able to automatically classify research papers as dealing or not with a given protein. In a second part, we show that the attributes that are selected by the genetic programming evolved programs can be used efficiently for proteins classification. Track: Genetic Programming Categories and Subject Descriptors

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Marc Segond, Cyril Fonlupt, Denis Robilliard
• Keywords: Bioinformatics, Evolutionary Computation, GECCO 2009, Genetic Programming, Optimization