Patent Document ID: 8762119
Application ID: 12855366
Patent Flag: 1

Claim One:
1. A method to predict and/or recognize and/or classify biological sequences wherein said biological sequences are predicted, recognized and/or classified by rules extracted from Neural Network (NN) learning process for poorly conserved biological sequences, the process being carried out by a computer and comprising the steps of: a) conducting NN learning for “X” sequences obtained from a database of sequences of binding site recognition motifs poorly conserved, namely, sequences where the relative position of the motifs are poorly conserved; b) extracting a rule for the “X” sequences of binding site recognition motifs poorly conserved; c) replacing prototype values from NN rule extraction by an integer number for the “X” sequences of binding site recognition motifs poorly conserved; d) analyzing each of the sequences for the “X” sequences of binding site recognition motifs poorly conserved; e) scoring each of the sequences and determining whether each of the sequences is greater than a cut-off value; and f) verifying if each of the sequences is a promoter of “X” sigma factor family, where “X” means the family of a given sequence, “X” being more than 1, and wherein the architecture of the NN learning process comprises between 2 and 5 neurons in a hidden layer of the NN, thereby allowing for the predicting and/or recognizing and/or classifying of the sequence.