GANN (Genetic Algorithm Neural Networks) is a machine learning method designed with the complexities of transcriptional regulation in mind.The key principle is that regulatory regions are composed of features such as consensus strings, characterized binding sites, and DNA structural properties. GANN identifies these features in a set of sequences, and then identifies combinations of features that can differentiate between the positive set (sequences with known or putative regulatory function) and the negative set (sequences with no regulatory function). Once these features have been identified, they can be used to classify new sequences of unknown function.
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Beiko, R.G. and Charlebois, R.L. (2005).
GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA.
BMC Bioinformatics 6: 36.