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Artigo de periodico
CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts (2021)
Nachtigall, Pedro Gabriel ; Kashiwabara, André Yoshiaki ; Durham, Alan Mitchell
Source: Briefings in Bioinformatics. Unidade: IME
Subjects: BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO
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ABNT
NACHTIGALL, Pedro Gabriel e KASHIWABARA, André Yoshiaki e DURHAM, Alan Mitchell. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, v. 22, n. 3, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbaa045. Acesso em: 13 jun. 2024.
APA
Nachtigall, P. G., Kashiwabara, A. Y., & Durham, A. M. (2021). CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, 22( 3), 1-11. doi:10.1093/bib/bbaa045
NLM
Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1093/bib/bbaa045
Vancouver
Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1093/bib/bbaa045
Artigo de periodico
Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells (2020)
Pereira, Túlio Felipe; Levin, Gabriel ; DeOcesano-Pereira, Carlos ; Caodaglio, Amanda Schiersner ; Fujita, André ; Tonso, Aldo ; Sogayar, Mari Cleide
Source: BMC Research Notes. Unidades: IME, EP, IQ, BIOTECNOLOGIA, FM
Subjects: BIOINFORMÁTICA, PROLIFERAÇÃO CELULAR
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ABNT
PEREIRA, Túlio Felipe et al. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells. BMC Research Notes, v. 13, n. 1, p. 1-7, 2020Tradução . . Disponível em: https://doi.org/10.1186/s13104-020-4914-8. Acesso em: 13 jun. 2024.
APA
Pereira, T. F., Levin, G., DeOcesano-Pereira, C., Caodaglio, A. S., Fujita, A., Tonso, A., & Sogayar, M. C. (2020). Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells. BMC Research Notes, 13( 1), 1-7. doi:10.1186/s13104-020-4914-8
NLM
Pereira TF, Levin G, DeOcesano-Pereira C, Caodaglio AS, Fujita A, Tonso A, Sogayar MC. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells [Internet]. BMC Research Notes. 2020 ;13( 1): 1-7.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1186/s13104-020-4914-8
Vancouver
Pereira TF, Levin G, DeOcesano-Pereira C, Caodaglio AS, Fujita A, Tonso A, Sogayar MC. Fluorescence-based method is more accurate than counting-based methods for plotting growth curves of adherent cells [Internet]. BMC Research Notes. 2020 ;13( 1): 1-7.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1186/s13104-020-4914-8
Artigo de periodico
Dynamic gene network analysis of caco-2 cell response to shiga toxin-producing Escherichia coli-associated hemolytic-uremic syndrome (2019)
Bando, Sílvia Yumi ; Iamashita, Priscila ; Silva, Filipi Nascimento ; Costa, Luciano da Fontoura ; Abe, Cecília M. ; Bertonha, Fernanda Bernardi ; Guth, Beatriz E. C. ; Fujita, André ; Moreira-Filho, Carlos Alberto
Source: Microorganisms. Unidades: FM, IFSC, IME
Subjects: ESCHERICHIA COLI, EXPRESSÃO GÊNICA
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ABNT
BANDO, Sílvia Yumi et al. Dynamic gene network analysis of caco-2 cell response to shiga toxin-producing Escherichia coli-associated hemolytic-uremic syndrome. Microorganisms, v. 7, n. 7, p. 195-1-195-23, 2019Tradução . . Disponível em: https://doi.org/10.3390/microorganisms7070195. Acesso em: 13 jun. 2024.
APA
Bando, S. Y., Iamashita, P., Silva, F. N., Costa, L. da F., Abe, C. M., Bertonha, F. B., et al. (2019). Dynamic gene network analysis of caco-2 cell response to shiga toxin-producing Escherichia coli-associated hemolytic-uremic syndrome. Microorganisms, 7( 7), 195-1-195-23. doi:10.3390/microorganisms7070195
NLM
Bando SY, Iamashita P, Silva FN, Costa L da F, Abe CM, Bertonha FB, Guth BEC, Fujita A, Moreira-Filho CA. Dynamic gene network analysis of caco-2 cell response to shiga toxin-producing Escherichia coli-associated hemolytic-uremic syndrome [Internet]. Microorganisms. 2019 ; 7( 7): 195-1-195-23.[citado 2024 jun. 13 ] Available from: https://doi.org/10.3390/microorganisms7070195
Vancouver
Bando SY, Iamashita P, Silva FN, Costa L da F, Abe CM, Bertonha FB, Guth BEC, Fujita A, Moreira-Filho CA. Dynamic gene network analysis of caco-2 cell response to shiga toxin-producing Escherichia coli-associated hemolytic-uremic syndrome [Internet]. Microorganisms. 2019 ; 7( 7): 195-1-195-23.[citado 2024 jun. 13 ] Available from: https://doi.org/10.3390/microorganisms7070195
Artigo de periodico
A hemolytic-uremic syndrome-associated strain O113:H21 Shiga toxin-producing Escherichia coli specifically expresses a transcriptional module containing dicA and is related to gene network dysregulation in Caco-2 cells (2017)
Bando, Sílvia Yumi ; Iamashita, Priscila ; Guth, Beatriz Ernestina Cabilio ; Santos, Luis F.; Fujita, André ; Abe, Cecília Mari ; Ferreira, Leandro Rodrigues; Moreira-Filho, Carlos Alberto
Source: PLOS ONE. Unidades: FM, IME
Assunto: BIOINFORMÁTICA
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ABNT
BANDO, Sílvia Yumi et al. A hemolytic-uremic syndrome-associated strain O113:H21 Shiga toxin-producing Escherichia coli specifically expresses a transcriptional module containing dicA and is related to gene network dysregulation in Caco-2 cells. PLOS ONE, v. 12, n. 12, p. 1-28, 2017Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0189613. Acesso em: 13 jun. 2024.
APA
Bando, S. Y., Iamashita, P., Guth, B. E. C., Santos, L. F., Fujita, A., Abe, C. M., et al. (2017). A hemolytic-uremic syndrome-associated strain O113:H21 Shiga toxin-producing Escherichia coli specifically expresses a transcriptional module containing dicA and is related to gene network dysregulation in Caco-2 cells. PLOS ONE, 12( 12), 1-28. doi:10.1371/journal.pone.0189613
NLM
Bando SY, Iamashita P, Guth BEC, Santos LF, Fujita A, Abe CM, Ferreira LR, Moreira-Filho CA. A hemolytic-uremic syndrome-associated strain O113:H21 Shiga toxin-producing Escherichia coli specifically expresses a transcriptional module containing dicA and is related to gene network dysregulation in Caco-2 cells [Internet]. PLOS ONE. 2017 ; 12( 12): 1-28.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1371/journal.pone.0189613
Vancouver
Bando SY, Iamashita P, Guth BEC, Santos LF, Fujita A, Abe CM, Ferreira LR, Moreira-Filho CA. A hemolytic-uremic syndrome-associated strain O113:H21 Shiga toxin-producing Escherichia coli specifically expresses a transcriptional module containing dicA and is related to gene network dysregulation in Caco-2 cells [Internet]. PLOS ONE. 2017 ; 12( 12): 1-28.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1371/journal.pone.0189613
Trabalho de evento-resumo
CETICSDB: a platform for integration and analysis of high-throughput-omics data and mathematical modeling of biochemical reactions (2015)
Nishiyama Junior, Milton Yutaka; Reis, M S; Silva, D. F; Junqueira-de-Azevedo, Inácio de Loiola Meirelles; Cunha, J. P. C. da; Barrera, Júnior; Iwai, L. K; Serrano, S. M. T; Armelin, Hugo Aguirre
Source: Abstracts Book. Conference titles: Congress of the International Union for Biochemistry and Molecular Biology - IUBMB. Unidades: IME, IQ
Subjects: BIOQUÍMICA, BIOINFORMÁTICA, MODELOS MATEMÁTICOS
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ABNT
NISHIYAMA JUNIOR, Milton Yutaka et al. CETICSDB: a platform for integration and analysis of high-throughput-omics data and mathematical modeling of biochemical reactions. 2015, Anais.. São Paulo: Sociedade Brasileira de Bioquímica e Biologia Molecular (SBBq), 2015. Disponível em: http://www.sbbq.org.br/iubmb2015/cdrom/resumos/R09084-1.pdf. Acesso em: 13 jun. 2024.
APA
Nishiyama Junior, M. Y., Reis, M. S., Silva, D. F., Junqueira-de-Azevedo, I. de L. M., Cunha, J. P. C. da, Barrera, J., et al. (2015). CETICSDB: a platform for integration and analysis of high-throughput-omics data and mathematical modeling of biochemical reactions. In Abstracts Book. São Paulo: Sociedade Brasileira de Bioquímica e Biologia Molecular (SBBq). Recuperado de http://www.sbbq.org.br/iubmb2015/cdrom/resumos/R09084-1.pdf
NLM
Nishiyama Junior MY, Reis MS, Silva DF, Junqueira-de-Azevedo I de LM, Cunha JPC da, Barrera J, Iwai LK, Serrano SMT, Armelin HA. CETICSDB: a platform for integration and analysis of high-throughput-omics data and mathematical modeling of biochemical reactions [Internet]. Abstracts Book. 2015 ;[citado 2024 jun. 13 ] Available from: http://www.sbbq.org.br/iubmb2015/cdrom/resumos/R09084-1.pdf
Vancouver
Nishiyama Junior MY, Reis MS, Silva DF, Junqueira-de-Azevedo I de LM, Cunha JPC da, Barrera J, Iwai LK, Serrano SMT, Armelin HA. CETICSDB: a platform for integration and analysis of high-throughput-omics data and mathematical modeling of biochemical reactions [Internet]. Abstracts Book. 2015 ;[citado 2024 jun. 13 ] Available from: http://www.sbbq.org.br/iubmb2015/cdrom/resumos/R09084-1.pdf
Trabalho de evento-resumo
Mathematical modeling of the Ras/MAPK and PI3K/AKT signaling networks in the K-Ras-driven mouse Y1 adrenocortical tumor cells (2014)
Reis, Marcelo da Silva ; Dias, M. H. S; Nakano, Fabio; Barrera, Júnior; Armelin, Hugo Aguirre
Source: Program and Index. Conference titles: Annual Meeting of the Brazilian Biochemistry and Molecular Biology Society (SBBq). Unidades: EACH, IME, IQ
Subjects: FIBROBLASTOS, CÉLULAS CULTIVADAS DE TUMOR
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ABNT
REIS, Marcelo da Silva et al. Mathematical modeling of the Ras/MAPK and PI3K/AKT signaling networks in the K-Ras-driven mouse Y1 adrenocortical tumor cells. 2014, Anais.. São Paulo: Sociedade Brasileira de Bioquímica e Biologia Molecular (SBBq), 2014. Disponível em: http://www.sigeventos.com.br/sbbq/cd/2014/resumos/R08802-1.pdf. Acesso em: 13 jun. 2024.
APA
Reis, M. da S., Dias, M. H. S., Nakano, F., Barrera, J., & Armelin, H. A. (2014). Mathematical modeling of the Ras/MAPK and PI3K/AKT signaling networks in the K-Ras-driven mouse Y1 adrenocortical tumor cells. In Program and Index. São Paulo: Sociedade Brasileira de Bioquímica e Biologia Molecular (SBBq). Recuperado de http://www.sigeventos.com.br/sbbq/cd/2014/resumos/R08802-1.pdf
NLM
Reis M da S, Dias MHS, Nakano F, Barrera J, Armelin HA. Mathematical modeling of the Ras/MAPK and PI3K/AKT signaling networks in the K-Ras-driven mouse Y1 adrenocortical tumor cells [Internet]. Program and Index. 2014 ;[citado 2024 jun. 13 ] Available from: http://www.sigeventos.com.br/sbbq/cd/2014/resumos/R08802-1.pdf
Vancouver
Reis M da S, Dias MHS, Nakano F, Barrera J, Armelin HA. Mathematical modeling of the Ras/MAPK and PI3K/AKT signaling networks in the K-Ras-driven mouse Y1 adrenocortical tumor cells [Internet]. Program and Index. 2014 ;[citado 2024 jun. 13 ] Available from: http://www.sigeventos.com.br/sbbq/cd/2014/resumos/R08802-1.pdf
Artigo de periodico
Enviromental genotoxicity evaluation: Bayesian approach for a mixture statistical model (2002)
Bueno, Ângela Maria de Souza; Pereira, Carlos Alberto de Bragança ; Rabello-Gay, Maria Nazareth; Stern, Julio Michael
Source: Stochastic Environmental Research and Risk Assessment (SERRA). Unidade: IME
Subjects: DISTRIBUIÇÕES (PROBABILIDADE), PROBABILIDADE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BUENO, Ângela Maria de Souza et al. Enviromental genotoxicity evaluation: Bayesian approach for a mixture statistical model. Stochastic Environmental Research and Risk Assessment (SERRA), v. 16, n. 4, p. 267-278, 2002Tradução . . Disponível em: https://doi.org/10.1007/s00477-002-0100-x. Acesso em: 13 jun. 2024.
APA
Bueno, Â. M. de S., Pereira, C. A. de B., Rabello-Gay, M. N., & Stern, J. M. (2002). Enviromental genotoxicity evaluation: Bayesian approach for a mixture statistical model. Stochastic Environmental Research and Risk Assessment (SERRA), 16( 4), 267-278. doi:10.1007/s00477-002-0100-x
NLM
Bueno ÂM de S, Pereira CA de B, Rabello-Gay MN, Stern JM. Enviromental genotoxicity evaluation: Bayesian approach for a mixture statistical model [Internet]. Stochastic Environmental Research and Risk Assessment (SERRA). 2002 ; 16( 4): 267-278.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1007/s00477-002-0100-x
Vancouver
Bueno ÂM de S, Pereira CA de B, Rabello-Gay MN, Stern JM. Enviromental genotoxicity evaluation: Bayesian approach for a mixture statistical model [Internet]. Stochastic Environmental Research and Risk Assessment (SERRA). 2002 ; 16( 4): 267-278.[citado 2024 jun. 13 ] Available from: https://doi.org/10.1007/s00477-002-0100-x

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