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Classifying Coding DNA with Nucleotide Statistics
In this report, we compared the success rate of classification of coding sequences (CDS) vs. introns by Codon Structure Factor (CSF) and by a method that we called Universal Feature Method (UFM). UFM is based on the scoring of purine bias (Rrr) and stop codon frequency. We show that the success rate...
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Formato: | Texto |
Lenguaje: | English |
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Libertas Academica
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808172/ https://www.ncbi.nlm.nih.gov/pubmed/20140062 |
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author | Carels, Nicolas Frías, Diego |
author_facet | Carels, Nicolas Frías, Diego |
author_sort | Carels, Nicolas |
collection | PubMed |
description | In this report, we compared the success rate of classification of coding sequences (CDS) vs. introns by Codon Structure Factor (CSF) and by a method that we called Universal Feature Method (UFM). UFM is based on the scoring of purine bias (Rrr) and stop codon frequency. We show that the success rate of CDS/intron classification by UFM is higher than by CSF. UFM classifies ORFs as coding or non-coding through a score based on (i) the stop codon distribution, (ii) the product of purine probabilities in the three positions of nucleotide triplets, (iii) the product of Cytosine (C), Guanine (G), and Adenine (A) probabilities in the 1st, 2nd, and 3rd positions of triplets, respectively, (iv) the probabilities of G in 1st and 2nd position of triplets and (v) the distance of their GC3 vs. GC2 levels to the regression line of the universal correlation. More than 80% of CDSs (true positives) of Homo sapiens (>250 bp), Drosophila melanogaster (>250 bp) and Arabidopsis thaliana (>200 bp) are successfully classified with a false positive rate lower or equal to 5%. The method releases coding sequences in their coding strand and coding frame, which allows their automatic translation into protein sequences with 95% confidence. The method is a natural consequence of the compositional bias of nucleotides in coding sequences. |
format | Text |
id | pubmed-2808172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-28081722010-02-04 Classifying Coding DNA with Nucleotide Statistics Carels, Nicolas Frías, Diego Bioinform Biol Insights Original Research In this report, we compared the success rate of classification of coding sequences (CDS) vs. introns by Codon Structure Factor (CSF) and by a method that we called Universal Feature Method (UFM). UFM is based on the scoring of purine bias (Rrr) and stop codon frequency. We show that the success rate of CDS/intron classification by UFM is higher than by CSF. UFM classifies ORFs as coding or non-coding through a score based on (i) the stop codon distribution, (ii) the product of purine probabilities in the three positions of nucleotide triplets, (iii) the product of Cytosine (C), Guanine (G), and Adenine (A) probabilities in the 1st, 2nd, and 3rd positions of triplets, respectively, (iv) the probabilities of G in 1st and 2nd position of triplets and (v) the distance of their GC3 vs. GC2 levels to the regression line of the universal correlation. More than 80% of CDSs (true positives) of Homo sapiens (>250 bp), Drosophila melanogaster (>250 bp) and Arabidopsis thaliana (>200 bp) are successfully classified with a false positive rate lower or equal to 5%. The method releases coding sequences in their coding strand and coding frame, which allows their automatic translation into protein sequences with 95% confidence. The method is a natural consequence of the compositional bias of nucleotides in coding sequences. Libertas Academica 2009-10-28 /pmc/articles/PMC2808172/ /pubmed/20140062 Text en Copyright © 2009 The authors. http://creativecommons.org/licenses/by/2.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/2.0/). |
spellingShingle | Original Research Carels, Nicolas Frías, Diego Classifying Coding DNA with Nucleotide Statistics |
title | Classifying Coding DNA with Nucleotide Statistics |
title_full | Classifying Coding DNA with Nucleotide Statistics |
title_fullStr | Classifying Coding DNA with Nucleotide Statistics |
title_full_unstemmed | Classifying Coding DNA with Nucleotide Statistics |
title_short | Classifying Coding DNA with Nucleotide Statistics |
title_sort | classifying coding dna with nucleotide statistics |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808172/ https://www.ncbi.nlm.nih.gov/pubmed/20140062 |
work_keys_str_mv | AT carelsnicolas classifyingcodingdnawithnucleotidestatistics AT friasdiego classifyingcodingdnawithnucleotidestatistics |