Abstract: We mainly surveyed the approaches on operon prediction and summarized the current art of the state in bioinformatics. After presenting most datasets in operon prediction and introducing most important popular algorithms, some disadvantages were pointed out. Furthermore, some future challenges w ere discussed and some solutions were suggested which are helpful to the future researches.

Key words: bioinformatics, operon prediction, machine learning, neural network, genetic algorithm