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0577005 - MBÚ 2024 RIV GB eng J - Journal Article
Le, A. V. - Větrovský, Tomáš - Baručić, D. - Saraiva, J. P. - Dobbler, Priscila Thiago - Kohout, Petr - Pospíšek, M. - da Rocha, U. N. - Kléma, J. - Baldrian, Petr
Improved recovery and annotation of genes in metagenomes through the prediction of fungal introns.
Molecular Ecology Resources. Roč. 23, č. 8 (2023), s. 1800-1811. ISSN 1755-098X. E-ISSN 1755-0998
R&D Projects: GA ČR(CZ) GA21-17749S
Research Infrastructure: e-INFRA CZ - 90140
Institutional support: RVO:61388971
Keywords : artificial intelligence * eukaryote * fungi * gene prediction * intron * metagenomics
OECD category: Microbiology
Impact factor: 7.7, year: 2022
Method of publishing: Limited access
https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13852
Permanent Link: https://hdl.handle.net/11104/0347997