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Filtros : "Financiamento NIBIOHN" Limpar

Filtros

USP affiliated authors
- mello, rodrigo fernandes de (~2)
- rios, ricardo araújo (~1)
- rios, tatiane nogueira (~1)
Date published
- 2021 (~2)
Subjects
- análise de séries temporais (1)
- aprendizado computacional (1)
- bioinformática (1)
- covid-19 (1)
- hemofilia (1)

Artigo de periodico
Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII (2021)
Lopes, Tiago José da Silva ; Rios, Ricardo Araújo ; Nogueira, Tatiane ; Mello, Rodrigo Fernandes de
Source: Scientific Reports. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, HEMOFILIA, PROTEÍNAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOPES, Tiago José da Silva et al. Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII. Scientific Reports, v. 11, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1038/s41598-021-92201-3. Acesso em: 31 out. 2024.
APA
Lopes, T. J. da S., Rios, R. A., Nogueira, T., & Mello, R. F. de. (2021). Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII. Scientific Reports, 11, 1-11. doi:10.1038/s41598-021-92201-3
NLM
Lopes TJ da S, Rios RA, Nogueira T, Mello RF de. Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII [Internet]. Scientific Reports. 2021 ; 11 1-11.[citado 2024 out. 31 ] Available from: https://doi.org/10.1038/s41598-021-92201-3
Vancouver
Lopes TJ da S, Rios RA, Nogueira T, Mello RF de. Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII [Internet]. Scientific Reports. 2021 ; 11 1-11.[citado 2024 out. 31 ] Available from: https://doi.org/10.1038/s41598-021-92201-3
Artigo de periodico
Country transition index based on hierarchical clustering to predict next COVID-19 waves (2021)
Rios, Ricardo Araújo ; Nogueira, Tatiane ; Coimbra, Danilo Barbosa; Lopes, Tiago José da Silva ; Abraham, Ajith ; Mello, Rodrigo Fernandes de
Source: Scientific Reports. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, INTELIGÊNCIA ARTIFICIAL, SURTOS DE DOENÇAS, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIOS, Ricardo Araújo et al. Country transition index based on hierarchical clustering to predict next COVID-19 waves. Scientific Reports, v. 11, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1038/s41598-021-94661-z. Acesso em: 31 out. 2024.
APA
Rios, R. A., Nogueira, T., Coimbra, D. B., Lopes, T. J. da S., Abraham, A., & Mello, R. F. de. (2021). Country transition index based on hierarchical clustering to predict next COVID-19 waves. Scientific Reports, 11, 1-13. doi:10.1038/s41598-021-94661-z
NLM
Rios RA, Nogueira T, Coimbra DB, Lopes TJ da S, Abraham A, Mello RF de. Country transition index based on hierarchical clustering to predict next COVID-19 waves [Internet]. Scientific Reports. 2021 ; 11 1-13.[citado 2024 out. 31 ] Available from: https://doi.org/10.1038/s41598-021-94661-z
Vancouver
Rios RA, Nogueira T, Coimbra DB, Lopes TJ da S, Abraham A, Mello RF de. Country transition index based on hierarchical clustering to predict next COVID-19 waves [Internet]. Scientific Reports. 2021 ; 11 1-13.[citado 2024 out. 31 ] Available from: https://doi.org/10.1038/s41598-021-94661-z

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