ArticleNucleic acids research2001
A computational approach to identify genes for functional RNAs in genomic sequences.
Article in Nucleic acids research, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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61 citing papers in PubMed.
- Random and Natural Non-Coding RNA Have Similar Structural Motif Patterns but Differ in Bulge, Loop, and Bond Counts.Life (Basel, Switzerland) · 2023Article
- Artificial Intelligence and Cardiovascular Genetics.Life (Basel, Switzerland) · 2022Review
- PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region.RNA biology · 2021Article
- Revisiting the Relationships Between Genomic G + C Content, RNA Secondary Structures, and Optimal Growth Temperature.Journal of molecular evolution · 2021Article
- Genetic variations analysis for complex brain disease diagnosis using machine learning techniques: opportunities and hurdles.PeerJ. Computer science · 2021Article
- Reprogramming of gene expression in Escherichia coli cultured on pyruvate versus glucose.Molecular genetics and genomics : MGG · 2019Article
- CPPred: coding potential prediction based on the global description of RNA sequence.Nucleic acids research · 2019Article
- Sequence-based bacterial small RNAs prediction using ensemble learning strategies.BMC bioinformatics · 2018Article
- Synthetic Biology of Small RNAs and Riboswitches.Microbiology spectrum · 2018Review
- A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria.RNA biology · 2018Article
- Identification of 15 candidate structured noncoding RNA motifs in fungi by comparative genomics.BMC genomics · 2017Article
- An improved method for identification of small non-coding RNAs in bacteria using support vector machine.Scientific reports · 2017Article
- Review
- In silico discovery and modeling of non-coding RNA structure in viruses.Methods (San Diego, Calif.) · 2015Review
- Tiling array study of MNNG treated Escherichia coli reveals a widespread transcriptional response.Scientific reports · 2013Article
- Computational small RNA prediction in bacteria.Bioinformatics and biology insights · 2013Article
- Predicting sRNAs and their targets in bacteria.Genomics, proteomics & bioinformatics · 2012Review
- An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains.Nucleic acids research · 2012Article
- Deep sequencing reveals as-yet-undiscovered small RNAs in Escherichia coli.BMC genomics · 2011Article
- Article
1 more citing papers are in PubMed but not listed here.
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Currently there is no successful computational approach for identification of genes encoding novel functional RNAs (fRNAs) in genomic sequences. We have developed a machine learning approach using neural networks and support vector machines to extract common features among known RNAs for prediction of new RNA genes in the unannotated regions of prokaryotic and archaeal genomes. The Escherichia coli genome was used for development, but we have applied this method to several other bacterial and archaeal genomes. Networks based on nucleotide composition were 80-90% accurate in jackknife testing experiments for bacteria and 90-99% for hyperthermophilic archaea. We also achieved a significant improvement in accuracy by combining these predictions with those obtained using a second set of parameters consisting of known RNA sequence motifs and the calculated free energy of folding. Several known fRNAs not included in the training datasets were identified as well as several hundred predicted novel RNAs. These studies indicate that there are many unidentified RNAs in simple genomes that can be predicted computationally as a precursor to experimental study. Public access to our RNA gene predictions and an interface for user predictions is available via the web.
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