2025.03.24.645056

Total: 1

#1 OpDetect: A convolutional and recurrent neural network classifier for precise and sensitive operon detection from RNA-seq data [PDF] [Copy] [Kimi] [REL]

Authors: Rezvan Karaji, Lourdes Pena-Castillo

An operon refers to a group of neighbouring genes belonging to one or more overlapping transcription units that are transcribed in the same direction and have at least one gene in common. Operons are a characteristic of prokaryotic genomes. Identifying which genes belong to the same operon facilitates understanding of gene function and regulation. There are several computational approaches for operon detection; however, many of these computational approaches have been developed for a specific target bacterium or require information only available for a restricted number of bacterial species. Here, we introduce a general method, OpDetect, that directly utilizes RNA-sequencing (RNA-seq) reads as a signal over nucleotide bases in the genome. This representation enabled us to employ a convolutional and recurrent deep neural network architecture which demonstrated superior performance in terms of recall, f1-score and AUROC compared to previous approaches. Additionally, OpDetect showcases species-agnostic capabilities, successfully detecting operons in a wide range of bacterial species and even in Caenorhabditis elegans, one of few eukaryotic organisms known to have operons. OpDetect is available at https://github.com/BioinformaticsLabAtMUN/OpDetect.

Subject: Bioinformatics

Publish: 2025-03-28