dorsal/arxiv
View SchemaSelf-organizing Approach for Automated Gene Identification in Whole Genomes
| Authors | Alexander N. Gorban, Andrey Yu. Zinovyev, Tatyana G. Popova |
|---|---|
| Categories | |
| ArXiv ID | physics/0108016 |
| URL | https://arxiv.org/abs/physics/0108016 |
Abstract
An approach based on using the idea of distinguished coding phase in explicit form for identification of protein-coding regions (exons) in whole genome has been proposed. For several genomes an optimal window length for averaging GC-content function and calculating codon frequencies has been found. Self-training procedure based on clustering in multidimensional space of triplet frequencies is proposed. For visualization of data in the space of triplet requiencies method of elastic maps was applied.
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"date_created": "2026-03-02T18:00:36.219000Z",
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"abstract": "An approach based on using the idea of distinguished coding phase in explicit\nform for identification of protein-coding regions (exons) in whole genome has\nbeen proposed. For several genomes an optimal window length for averaging\nGC-content function and calculating codon frequencies has been found.\nSelf-training procedure based on clustering in multidimensional space of\ntriplet frequencies is proposed. For visualization of data in the space of\ntriplet requiencies method of elastic maps was applied.",
"arxiv_id": "physics/0108016",
"authors": [
"Alexander N. Gorban",
"Andrey Yu. Zinovyev",
"Tatyana G. Popova"
],
"categories": [
"physics.bio-ph",
"q-bio.GN"
],
"title": "Self-organizing Approach for Automated Gene Identification in Whole Genomes",
"url": "https://arxiv.org/abs/physics/0108016"
},
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