Riboflow: Using Deep Learning to Classify Riboswitches With ∼99% Accuracy.

ABSTRACT: Riboswitches are cis-regulatory genetic elements that use an aptamer to control gene expression. Specificity to cognate ligand and diversity of such ligands have expanded the functional repertoire of riboswitches to mediate mounting apt responses to sudden metabolic demands and signal changes in environmental conditions. Given their critical role in microbial life, riboswitch characterisation remains a challenging computational problem. Here we have addressed the issue with advanced deep learning frameworks, namely convolutional neural networks (CNN), and bidirectional recurrent neural networks (RNN) with Long Short-Term Memory (LSTM). Using a comprehensive dataset of 32 ligand classes and a stratified train-validate-test approach, we demonstrated the accurate performance of both th

SUBMITTER: Premkumar KAR 

PROVIDER: S-EPMC7371854 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature