ArticleBMC bioinformatics2004
Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models.
Article in BMC bioinformatics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- MiRNATIP: a SOM-based miRNA-target interactions predictor.BMC bioinformatics · 2016Article
- Classification and clustering analysis of pyruvate dehydrogenase enzyme based on their physicochemical properties.Bioinformation · 2010Article
- Genome signatures, self-organizing maps and higher order phylogenies: a parametric analysis.Evolutionary bioinformatics online · 2007Article
- GISMO--gene identification using a support vector machine for ORF classification.Nucleic acids research · 2007Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation.
resultsThis work explores a new approach to gene-prediction, based on the Self-Organizing Map, which has the ability to automatically identify multiple gene models within a genome. The current implementation, named RescueNet, uses relative synonymous codon usage as the indicator of protein-coding potential.
conclusionsWhile its raw accuracy rate can be less than other methods, RescueNet consistently identifies some genes that other methods do not, and should therefore be of interest to gene-prediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.
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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.