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https://hdl.handle.net/1822/61781
Título: | Predicting promoters in phage genomes using machine learning models |
Autor(es): | Sampaio, Marta Rocha, Miguel Oliveira, Hugo Alexandre Mendes Dias, Oscar |
Palavras-chave: | Machine learning Genome analysis Phages Promoters Phages Promoters |
Data: | 2020 |
Editora: | Springer |
Revista: | Advances in Intelligent Systems and Computing |
Citação: | Sampaio, Marta; Rocha, Miguel; Oliveira, Hugo; Dias, Oscar, Predicting promoters in phage genomes using machine learning models. Advances in Intelligent Systems and Computing. Vol. 1005 (PACBB 2019), Springer, 105-112, 2020. |
Resumo(s): | The renewed interest in phages as antibacterial agents has led to the exponentially growing number of sequenced phage genomes. Therefore, the development of novel bioinformatics methods to automate and facilitate phage genome annotation is of utmost importance. The most difficult step of phage genome annotation is the identification of promoters. As the existing methods for predicting promoters are not well suited for phages, we used machine learning models for locating promoters in phage genomes. Several models were created, using different algorithms and datasets, which consisted of known phage promoter and non-promoter sequences. All models showed good performance, but the ANN model provided better results for the smaller dataset (92% of accuracy, 89% of precision and 87% of recall) and the SVM model returned better results for the larger dataset (93% of accuracy, 91% of precision and 80% of recall). Both models were applied to the genome of Pseudomonas phage phiPsa17 and were able to identify both types of promoters, host and phage, found in phage genomes. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/61781 |
ISBN: | 9783030238728 |
DOI: | 10.1007/978-3-030-23873-5_13 |
ISSN: | 2194-5357 |
e-ISSN: | 2194-5365 |
Versão da editora: | http://www.springer.com/series/11156 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document_51780_1.pdf | 424,63 kB | Adobe PDF | Ver/Abrir |