ReviewMethods (San Diego, Calif.)2020
A computational system for identifying operons based on RNA-seq data.
Review in Methods (San Diego, Calif.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
65 citing papers in PubMed.
- Caerin 1.1/1.9 Inhibits Growth and Biofilm Formation of Carbapenem-Resistant Klebsiella pneumoniae and Induces Coordinated Transcriptomic Stress Responses.Current microbiology · 2026Article
- Article
- RhlR quorum-sensing receptor ligand sensitivity regulates the differential expression of phenazine genes inJournal of bacteriology · 2026Article
- Metabolome-driven rhizosphere microbiome assembly determining the health of medicinal herb (Angelica sinensis) against root rot.Microbiome · 2026Article
- TerminatorNet: comprehensive identification of intrinsic transcription terminators in bacteria.Bioinformatics (Oxford, England) · 2026Article
- CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization.Nature communications · 2026Article
- A platform for CRISPRi-seq inmBio · 2026Article
- ThemBio · 2026Article
- Hybrid capture RNA-seq defines temporal gene expression inbioRxiv : the preprint server for biology · 2026Article
- DNA topoisomerase I acts as supercoiling sensor for bacterial transcription elongation.Nature structural & molecular biology · 2026Article
- Deletion of sRNA0024 Reduces Virulence ofAnimals : an open access journal from MDPI · 2025Article
- Article
- A supervised Bayesian method for time (re)annotation of transcriptomics data.NAR genomics and bioinformatics · 2025Article
- Human antibody targetingmBio · 2025Article
- Tyrosine phosphorylation coupling of one-carbon metabolism and virulence in an endogenous pathogen.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Cappable-Seq reveals the transcriptional landscape of stress responses in the bacterial endosymbiontMicrobial genomics · 2025Article
- Conserved Heterochromatin-like Structures with Local Regulators Mediate the Iron Stress Response in Mycobacteria.bioRxiv : the preprint server for biology · 2025Article
- DNA methylation affects gene expression but not global chromatin structure inJournal of bacteriology · 2025Article
- Diverse marineMarine life science & technology · 2025Article
- Environmental cues in different host niches shape the survival fitness of Staphylococcus aureus.Nature communications · 2025Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
An operon is a set of neighboring genes in a genome that is transcribed as a single polycistronic message. Genes that are part of the same operon often have related functional roles or participate in the same metabolic pathways. The majority of all bacterial genes are co-transcribed with one or more other genes as part of a multi-gene operon. Thus, accurate identification of operons is important in understanding co-regulation of genes and their functional relationships. Here, we present a computational system that uses RNA-seq data to determine operons throughout a genome. The system takes the name of a genome and one or more files of RNA-seq data as input. Our method combines primary genomic sequence information with expression data from the RNA-seq files in a unified probabilistic model in order to identify operons. We assess our method's ability to accurately identify operons in a range of species through comparison to external databases of operons, both experimentally confirmed and computationally predicted, and through focused experiments that confirm new operons identified by our method. Our system is freely available at https://cs.wellesley.edu/~btjaden/Rockhopper/.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.