Ipromoter-Bncnn: A Novel Branched Cnn-Based Predictor For Identifying And Classifying Sigma Promoters

Motivation: Promoter is a short region of DNA which is responsible for initiating transcription of specific genes. Development of computational tools for automatic identification of promoters is in high demand. According to the difference of functions, promoters can be of different types. Promoters may have both intra- and interclass variation and similarity in terms of consensus sequences. Accurate classification of various types of sigma promoters still remains a challenge.Results: We present iPromoter-BnCNN for identification and accurate classification of six types of promoters-sigma(24), sigma(28), sigma(32), sigma(38), sigma(54), sigma(70). It is a CNN-based classifier which combines local features related to monomer nucleotide sequence, trimer nucleotide sequence, dimer structural properties and trimer structural properties through the use of parallel branching. We conducted experiments on a benchmark dataset and compared with six state-of-the-art tools to show our supremacy on 5-fold cross-validation. Moreover, we tested our classifier on an independent test dataset.