Identification of protein coding genes in genomes with statistical functions based on the circular code.
A new statistical approach using functions based on the circular code classifies correctly more than 93% of bases in protein (coding) genes and non-coding genes of human sequences. Based on this statistical study, a research software called 'Analysis of Coding Genes' (ACG) has been developed for identifying protein genes in the genomes and for determining their frame. Furthermore, the software ACG also allows an evaluation of the length of protein genes, their position in the genome, their relative position between themselves, and the prediction of internal frames in protein genes.
Arquès
Didier G
DG
Equipe de Biologie Théorique, Institut Gaspard Monge, Université de Marne la Vallée, 2 rue de la Butte Verte, 93160 Noisy le Grand, France. arques@univ-mlv.fr
Lacan
Jérôme
J
Michel
Christian J
CJ
D001483:Base Sequence; D001699:Biometry; D004247:DNA / Q000235:genetics; D005815:Genetic Code; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D008969:Molecular Sequence Data; D011506:Proteins / Q000235:genetics*; D020543:Proteome; D012984:Software
D011506:Proteins; D020543:Proteome; D004247:DNA