Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
The computational linguistics of biological sequences
Artificial intelligence and molecular biology
A machine discovery from amino acid sequences by decision trees over regular patterns
Selected papers of international conference on Fifth generation computer systems 92
An introduction to computational learning theory
An introduction to computational learning theory
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Bioinformatics: the machine learning approach
Bioinformatics: the machine learning approach
Logic-based genetic programming with definite clause translation grammars
New Generation Computing
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Probabilistic Pattern Matching and the Evolution of Stochastic Regular Expressions
Applied Intelligence
Pattern Discovery in Biosequences
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Discovering biological motifs with genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The evolutionary computation approach to motif discovery in biological sequences
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Regulatory Motif Discovery Using a Population Clustering Evolutionary Algorithm
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Grammar guided genetic programming for flexible neural trees optimization
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Protein motif discovery with linear genetic programming
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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Stochastic regular motifs are evolved for protein sequences using genetic programming. The motif language, SRE-DNA, is a stochastic regular expression language suitable for denoting biosequences. Three restricted versions of SRE-DNA are used as target languages for evolved motifs. The genetic programming experiments are implemented in DCTG-GP, which is a genetic programming system that uses logic-based attribute grammars to define the target language for evolved programs. Earlier preliminary work tested SRE-DNA's viablility as a representation language for aligned protein sequences. This work establishes that SRE-DNA is also suitable for evolving motifs for unaligned sets of sequences.