Bioinformatics: the machine learning approach
Bioinformatics: the machine learning approach
The evolution of stochastic regular motifs for protein sequences
New Generation Computing
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Evolving the Topology of Hidden Markov Models Using Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Alignment Of Protein Structures With A Memetic Evolutionary Algorithm
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Evolving Turing Machines for Biosequence Recognition and Analysis
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Optimizing Hidden Markov Models with a Genetic Algorithm
AE '95 Selected Papers from the European conference on Artificial Evolution
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Optimization of HMM by a Genetic Algorithm
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
INBS '95 Proceedings of the First International Symposium on Intelligence in Neural and Biological Systems (INBS'95)
Multiple Sequence Alignment with Evolutionary Computation
Genetic Programming and Evolvable Machines
Particle Swarm Optimisation for Protein Motif Discovery
Genetic Programming and Evolvable Machines
Multiple DNA sequences alignment by means of genetic algorithm
Design and application of hybrid intelligent systems
Structural emergence with order independent representations
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Evolutionary two-dimensional DNA sequence alignment
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
TFBS identification by position- and consensus-led genetic algorithm with local filtering
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Regulatory Motif Discovery Using a Population Clustering Evolutionary Algorithm
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
It's not junk!: the search for functional elements in noncoding DNA
ACM SIGEVOlution
Modeling evolutionary fitness for DNA motif discovery
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
GAMIV: a genetic algorithm for identifying variable-lengthmotifs in noncoding DNA
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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Finding motifs — patterns of conserved residues — within nucleotide and protein sequences is a key part of understanding function and regulation within biological systems. This paper presents a review of current approaches to motif discovery, both evolutionary computation based and otherwise, and a speculative look at the advantages of the evolutionary computation approach and where it might lead us in the future. Particular attention is given to the problem of characterising regulatory DNA motifs and the value of expressive representations for providing accurate classification.