Operon Finder: A Deep Learning-based Web Server for Accurate Prediction of Prokaryotic Operons

Abstract

Operons are groups of adjacent genes that are transcribed together under the control of a common promoter. Because operons shape gene regulation and many physiological pathways, identifying them accurately is valuable. Detecting operons experimentally is slow and expensive, so experts often predict them from the genomic organization and functional relationships of genes. As the number of completely sequenced genomes grows, automated tools and web servers have become preferable to manual prediction. The most accurate current methods use deep learning to predict whether adjacent genes belong to the same operon, but using them requires programming knowledge and computational skills. Here we present Operon Finder, a web server for on-the-fly operon prediction with deep learning. It offers genome search, live filtering of predicted operons, viewing and downloading of operonic DNA sequences, export of the predictions, and links to the NCBI (National Center for Biotechnology Information) and UniProt databases. Operon Finder is available at https://www.iitg.ac.in/spkanaujia/operonfinder.html, and its source code is available at https://github.com/SPKlab/Operon-Finder.

This PDF is an author version of the accepted article. The first author reconstructed it from the June 2022 manuscript and the changes made in peer review; it does not include the publisher’s copyediting or typesetting. Please cite the published article.