A Comparative Study of Machine Learning Methods for Detecting Promoters in Bacterial DNA Sequences

Abstract. Machine Learning methods have been widely used in bioin-formatics, mainly for data classification and pattern recognition. The detection of genes in DNA sequences is still an open problem. Identify-ing the promoter region laying prior the gene itself is an important aid to detect a gene. This paper aims at applying several Machine Learning methods to the construction of classifiers for detection of promoters in the DNA of Escherichia coli. A thorough comparison of methods was done. In general, probabilistic and neural network-based methods were those that performed better regarding accuracy rate