SARS‑CoV‑2 host prediction based on virus‑host genetic features (2022)
- Authors:
- USP affiliated authors: HASHIMOTO, RONALDO FUMIO - IME ; KAWASHIMA, IRINA YURI - BIOINFORMÁTICA ; LOPEZ, MARIA CLAUDIA NEGRET - BIOINFORMÁTICA ; CUNHA, MARIELTON DOS PASSOS - BIOINFORMÁTICA
- Unidades: IME; BIOINFORMÁTICA
- DOI: 10.1038/s41598-022-08350-6
- Subjects: GEOMETRIA E MODELAGEM COMPUTACIONAL; BIOINFORMÁTICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Scientific Reports
- ISSN: 2045-2322
- Volume/Número/Paginação/Ano: v. 12, artigo n. 4576, p. 1-9, 2022
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
KAWASHIMA, IrinaYuri et al. SARS‑CoV‑2 host prediction based on virus‑host genetic features. Scientific Reports, v. 12, n. artigo 4576, p. 1-9, 2022Tradução . . Disponível em: https://doi.org/10.1038/s41598-022-08350-6. Acesso em: 28 abr. 2024. -
APA
Kawashima, I. Y., Lopez, M. C. N., Cunha, M. dos P., & Hashimoto, R. F. (2022). SARS‑CoV‑2 host prediction based on virus‑host genetic features. Scientific Reports, 12( artigo 4576), 1-9. doi:10.1038/s41598-022-08350-6 -
NLM
Kawashima IY, Lopez MCN, Cunha M dos P, Hashimoto RF. SARS‑CoV‑2 host prediction based on virus‑host genetic features [Internet]. Scientific Reports. 2022 ; 12( artigo 4576): 1-9.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1038/s41598-022-08350-6 -
Vancouver
Kawashima IY, Lopez MCN, Cunha M dos P, Hashimoto RF. SARS‑CoV‑2 host prediction based on virus‑host genetic features [Internet]. Scientific Reports. 2022 ; 12( artigo 4576): 1-9.[citado 2024 abr. 28 ] Available from: https://doi.org/10.1038/s41598-022-08350-6 - An extension of an algorithm for finding sequential decomposition of erosions and dilations
- Incremental and efficient computation of families of component trees
- Biological sequence analysis using complex networks and entropy maximization: a case study in SARS-CoV-2
- Evaluation of the impact of initial positions obtained by clustering algorithms on the straight line segments classifier
- Is cross-validation better than resubstitution for ranking genes?
- Growing genetic regulatory networks from seed genes
- Inference of restricted stochastic Boolean GRN' s by Bayesian error and entropy based criteria
- A new training algorithm for pattern recognition technique based on straight line segments
- A Monte Carlo approach to measure the robustness of Boolean networks
- Growing seed genes from time series data and thresholded Boolean networks with perturbation
Informações sobre o DOI: 10.1038/s41598-022-08350-6 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 | 3073341.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
