Universal mtDNA Fragment for Cervidae Barcoding Species Identification and Preliminary Analysis of Machine Learning Approach

Scientists have developed a new method for identifying animal species using degraded bone samples, according to a paper in Scientific Reports. The team used accurate bioinformatics tools and a machine learning approach to identify three species of deer using partial mitochondrial cytochrome b (Cytb) gene sequences. The sequences were used as a marker for species-specific identification. The study also analysed the effect of barcodes on species identification from a machine learning approach, comparing BLOG and WEKA with TaxonDNA and NJ tree. The results indicated that BLOG and WEKA’s SMO classifier performed the best. The technique provides a reproducible and sensitive method of identifying wild deer populations. The team enriched the existing mtDNA base of Cervidae species.