Species identification using part of DNA sequence: Evidence from machine learning algorithms

Abstract

In biological studies, species identification is considered one of the most important issues. Several methods have been suggested to identify species using the whole DNA sequences. In this study, we present new insights for species identification using only part of the DNA sequence. The Clustering k-Nearest Neighbor (K-CNN) and Support Vector Machine (SVM) classifiers were used to test and evaluate the improved statistical features extracted from DNA sequences for four species (Aquifex aeolicus, Bacillus subtilis, Aeropyrum pernix and Buchnera sp). The results show that part of DNA sequences can be used to identify species.