Title |
SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models
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Published in |
BMC Bioinformatics, July 2014
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DOI | 10.1186/1471-2105-15-229 |
Pubmed ID | |
Authors |
Ian Reid, Nicholas O’Toole, Omar Zabaneh, Reza Nourzadeh, Mahmoud Dahdouli, Mostafa Abdellateef, Paul MK Gordon, Jung Soh, Gregory Butler, Christoph W Sensen, Adrian Tsang |
Abstract |
Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. |
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Mendeley readers
Geographical breakdown
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Environmental Science | 1 | <1% |
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