ArticleNucleic acids research2007
Operon prediction in Pyrococcus furiosus.
Article in Nucleic acids research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 40 citations in OpenAlex.
- Detecting operons in bacterial genomes via visual representation learning.Scientific reports · 2021Article
- Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons.BMC genomics · 2021Article
- Cautions about the reliability of pairwise gene correlations based on expression data.Frontiers in microbiology · 2015Article
- Transcriptome dynamics-based operon prediction in prokaryotes.BMC bioinformatics · 2014Article
- Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling.BMC genomics · 2013Article
- Genome sequencing of a genetically tractable Pyrococcus furiosus strain reveals a highly dynamic genome.Journal of bacteriology · 2012Article
- High accuracy operon prediction method based on STRING database scores.Nucleic acids research · 2010Article
- Binary particle swarm optimization for operon prediction.Nucleic acids research · 2010Article
- De novo computational prediction of non-coding RNA genes in prokaryotic genomes.Bioinformatics (Oxford, England) · 2009Article
- Novel multiprotein complexes identified in the hyperthermophilic archaeon Pyrococcus furiosus by non-denaturing fractionation of the native proteome.Molecular & cellular proteomics : MCP · 2009Article
- Bioinformatics resources for the study of gene regulation in bacteria.Journal of bacteriology · 2009Review
- SurR: a transcriptional activator and repressor controlling hydrogen and elemental sulphur metabolism in Pyrococcus furiosus.Molecular microbiology · 2009Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Identification of operons in the hyperthermophilic archaeon Pyrococcus furiosus represents an important step to understanding the regulatory mechanisms that enable the organism to adapt and thrive in extreme environments. We have predicted operons in P.furiosus by combining the results from three existing algorithms using a neural network (NN). These algorithms use intergenic distances, phylogenetic profiles, functional categories and gene-order conservation in their operon prediction. Our method takes as inputs the confidence scores of the three programs, and outputs a prediction of whether adjacent genes on the same strand belong to the same operon. In addition, we have applied Gene Ontology (GO) and KEGG pathway information to improve the accuracy of our algorithm. The parameters of this NN predictor are trained on a subset of all experimentally verified operon gene pairs of Bacillus subtilis. It subsequently achieved 86.5% prediction accuracy when applied to a subset of gene pairs for Escherichia coli, which is substantially better than any of the three prediction programs. Using this new algorithm, we predicted 470 operons in the P.furiosus genome. Of these, 349 were validated using DNA microarray data.
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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.