DeepTE: A Convolutional Neural Network based neural network for de novo classification of transposons.

                   The classification of transposons has long been used to study their role in genome evolution. The genome sequence analysis and efficient classification of TEs has begun to see a new era with the non model organisms’ sequences getting accumulated in the databases.
                     

                 Yan H. et. al.(2020) have used neural networks to develop DeepTE which classifies the unknown TEs. They have used several models to train to classify many TEs. In many respects the DeepTE, was more efficient than rest of the TE classification softwares.
         

         The code and implementation of algorithm is available at the following URL: https://github.com/LiLabAtVT/DeepTE

Reference:

Yan H. et. al.(2020)DeepTE: a computaional method for de novo classification of transposons with convolutional neural networks. Bioinformatics 36(15):4269-4275.