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Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training
We describe a new ab initio algorithm, GeneMark-ES version 2, that identifies protein-coding genes in fungal genomes. The algorithm does not require a predetermined training set to estimate parameters of the underlying hidden Markov model (HMM). Instead, the anonymous genomic sequence in question is...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Cold Spring Harbor Laboratory Press
2008
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2593577/ https://ncbi.nlm.nih.gov/pubmed/18757608 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/gr.081612.108 |
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