Schemata and sequential thought processes in PDP models
Parallel distributed processing
Protein motif prediction by grammatical inference
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
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In this work we tackle the task of detecting biological motifs, i.e. subsequences with an associated function. This task is important in bioinformatics because it is related to the prediction of the behaviour of the whole protein. Artificial neural networks are used to, somewhat, translate the sequence of amino acids of the protein into a code that shows the subsequences where the presence of the studied motif is expected. The experimentation performed prove the good performance of our approach.