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Find schema in a set of sequences using a genetic algorithm approach. Finding good schemas is very difficult because it takes forever to enumerate all of the potential schemas. This finder using a genetic algorithm approach to evolve good schema which match many times in a set of sequences. The default implementation of the finder is ready to find schemas in a set of DNA sequences, but the finder can be customized to deal with any type of data.
Find well-represented schemas in the given set of SeqRecords.
00458 00459 def find(self, seq_records): 00460 """Find well-represented schemas in the given set of SeqRecords. 00461 """ 00462 fitness_evaluator = MostCountSchemaFitness(seq_records, 00463 self.evaluator) 00464 00465 return self._finder.find_schemas(fitness_evaluator.calculate_fitness, 00466 self.num_schemas)
Find schemas which differentiate between the two sets of SeqRecords.
00467 00468 def find_differences(self, first_records, second_records): 00469 """Find schemas which differentiate between the two sets of SeqRecords. 00470 """ 00471 fitness_evaluator = DifferentialSchemaFitness(first_records, 00472 second_records, 00473 self.evaluator) 00474 00475 return self._finder.find_schemas(fitness_evaluator.calculate_fitness, 00476 self.num_schemas)