ArticleNucleic acids research1992
The prediction of exons through an analysis of spliceable open reading frames.
Article in Nucleic acids research, 1992. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 86 citations in OpenAlex.
- Review
- Computational Identification of Novel Genes: Current and Future Perspectives.Bioinformatics and biology insights · 2016Review
- A brief review of computational gene prediction methods.Genomics, proteomics & bioinformatics · 2004Review
- Current methods of gene prediction, their strengths and weaknesses.Nucleic acids research · 2002Review
- Positional cloning of ZNF217 and NABC1: genes amplified at 20q13.2 and overexpressed in breast carcinoma.Proceedings of the National Academy of Sciences of the United States of America · 1998Article
- Construction and analysis of an hn-cDNA library derived from the p-arm of pig chromosome 12.Mammalian genome : official journal of the International Mammalian Genome Society · 1996Article
- Predicting internal exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames.Nucleic acids research · 1994Article
- Intrinsic and extrinsic approaches for detecting genes in a bacterial genome.Nucleic acids research · 1994Article
- Fission yeast gene structure and recognition.Nucleic acids research · 1994Article
- Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a computer program which predicts internal exons from naive genomic sequence data and which will run on any IBM-compatible 80286 (or higher) computer. The algorithm searches a sequence for 'spliceable open reading frames' (SORFs), which are open reading frames bracketed by suitable splice-recognition sequences, and then analyzes the region for codon usage. Potential exons are stratified according to the reliability of their prediction, from confidence levels 1 to 5. The program is designed to predict internal exons of length greater than 60 nucleotides. In an analysis of 116 genes of a training set, 384 out of 441 such exons (87.1%) are identified, with 280 (63.5%) of predictions matching the true exon exactly (at both 5' and 3' splice junctions and in the correct reading frame), and with 104 (23.6%) exons matching partially. In a similar analysis of 14 genes in a test set unrelated to the genes used to generate the parameters of the program, 70 out of 80 internal exons greater than 60 bp in length are identified (87.5%), with 47 completely and 23 partially matched. SORFs that partially match true internal exons share at least one splice junction with the exon, or share both splice junctions but are interpreted in an incorrect reading frame. Specificity (the percentage of SORFs that correspond to true exons) varies from 91% at confidence level 1 to 16% at confidence level 5, with an overall specificity of 35-40%. The output displays nucleotide position, confidence level, reading frame phase at the 5' and 3' ends, acceptor and donor sequences and scoring statistics and also gives an amino acid translation of the potential exon. SORFIND compares favourably with other programs currently used to predict protein-coding regions.
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