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Artigo de periodico
A stochastic binary model for the regulation of gene expression to investigate responses to gene therapy (2022)
Giovanini, Guilherme ; Barros, Luciana R. C. ; Gama, Leonardo R. ; Tortelli Junior, Tharcisio Citrangulo ; Ramos, Alexandre Ferreira
Source: Cancers. Unidades: EACH, FM
Subjects: NEOPLASIAS, BIOLOGIA MOLECULAR, REGULAÇÃO GÊNICA, EXPRESSÃO GÊNICA, DINÂMICA ESTOCÁSTICA
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ABNT
GIOVANINI, Guilherme et al. A stochastic binary model for the regulation of gene expression to investigate responses to gene therapy. Cancers, v. 14, n. Ja 2022, p. 01-29, 2022Tradução . . Disponível em: https://doi.org/10.3390/cancers14030633. Acesso em: 15 jul. 2024.
APA
Giovanini, G., Barros, L. R. C., Gama, L. R., Tortelli Junior, T. C., & Ramos, A. F. (2022). A stochastic binary model for the regulation of gene expression to investigate responses to gene therapy. Cancers, 14( Ja 2022), 01-29. doi:10.3390/cancers14030633
NLM
Giovanini G, Barros LRC, Gama LR, Tortelli Junior TC, Ramos AF. A stochastic binary model for the regulation of gene expression to investigate responses to gene therapy [Internet]. Cancers. 2022 ; 14( Ja 2022): 01-29.[citado 2024 jul. 15 ] Available from: https://doi.org/10.3390/cancers14030633
Vancouver
Giovanini G, Barros LRC, Gama LR, Tortelli Junior TC, Ramos AF. A stochastic binary model for the regulation of gene expression to investigate responses to gene therapy [Internet]. Cancers. 2022 ; 14( Ja 2022): 01-29.[citado 2024 jul. 15 ] Available from: https://doi.org/10.3390/cancers14030633
Artigo de periodico
Binary Expression Enhances Reliability of Messaging in Gene Networks (2020)
Gama, Leonardo R. ; Giovanini, Guilherme ; Balázsi, Gábor ; Ramos, Alexandre Ferreira
Source: Entropy. Unidade: EACH
Subjects: BIOLOGIA MOLECULAR, EXPRESSÃO GÊNICA, DINÂMICA ESTOCÁSTICA
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ABNT
GAMA, Leonardo R. et al. Binary Expression Enhances Reliability of Messaging in Gene Networks. Entropy, v. 22, n. 4, p. 01-18, 2020Tradução . . Disponível em: https://doi.org/10.3390/e22040479. Acesso em: 15 jul. 2024.
APA
Gama, L. R., Giovanini, G., Balázsi, G., & Ramos, A. F. (2020). Binary Expression Enhances Reliability of Messaging in Gene Networks. Entropy, 22( 4), 01-18. doi:10.3390/e22040479
NLM
Gama LR, Giovanini G, Balázsi G, Ramos AF. Binary Expression Enhances Reliability of Messaging in Gene Networks [Internet]. Entropy. 2020 ; 22( 4): 01-18.[citado 2024 jul. 15 ] Available from: https://doi.org/10.3390/e22040479
Vancouver
Gama LR, Giovanini G, Balázsi G, Ramos AF. Binary Expression Enhances Reliability of Messaging in Gene Networks [Internet]. Entropy. 2020 ; 22( 4): 01-18.[citado 2024 jul. 15 ] Available from: https://doi.org/10.3390/e22040479
Artigo de periodico
Lessons and perspectives for applications of stochastic models in biological and cancer research (2018)
Sabino, Alan U.; Vasconcelos, Miguel F. S.; Sittoni, Misaki Yamada; Lautenschlager, Willian W.; Queiroga, Alexandre S.; Morais, Mauro C.C.; Ramos, Alexandre Ferreira
Source: Clinics. Unidade: EACH
Subjects: CADEIAS DE MARKOV, NEOPLASIAS, EXPRESSÃO GÊNICA
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ABNT
SABINO, Alan U. et al. Lessons and perspectives for applications of stochastic models in biological and cancer research. Clinics, v. 73, p. 01-08, 2018Tradução . . Disponível em: http://www.scielo.br/pdf/clin/v73s1/1807-5932-clin-73-e536s.pdf. Acesso em: 15 jul. 2024.
APA
Sabino, A. U., Vasconcelos, M. F. S., Sittoni, M. Y., Lautenschlager, W. W., Queiroga, A. S., Morais, M. C. C., & Ramos, A. F. (2018). Lessons and perspectives for applications of stochastic models in biological and cancer research. Clinics, 73, 01-08. doi:10.6061/clinics/2018/e536s
NLM
Sabino AU, Vasconcelos MFS, Sittoni MY, Lautenschlager WW, Queiroga AS, Morais MCC, Ramos AF. Lessons and perspectives for applications of stochastic models in biological and cancer research [Internet]. Clinics. 2018 ; 73 01-08.[citado 2024 jul. 15 ] Available from: http://www.scielo.br/pdf/clin/v73s1/1807-5932-clin-73-e536s.pdf
Vancouver
Sabino AU, Vasconcelos MFS, Sittoni MY, Lautenschlager WW, Queiroga AS, Morais MCC, Ramos AF. Lessons and perspectives for applications of stochastic models in biological and cancer research [Internet]. Clinics. 2018 ; 73 01-08.[citado 2024 jul. 15 ] Available from: http://www.scielo.br/pdf/clin/v73s1/1807-5932-clin-73-e536s.pdf
Artigo de periodico
Backward-stochastic-differential-equation approach to modeling of gene expression (2017)
Shamarova, Evelina; Chertovskih, Roman; Ramos, Alexandre Ferreira; Aguiar, Paulo de Castro
Source: Physical Review E : Covering Statistical, Nonlinear, Biological, and Soft Matter Physics. Unidade: EACH
Subjects: PROCESSOS ESTOCÁSTICOS, EXPRESSÃO GÊNICA, BIOLOGIA MOLECULAR
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ABNT
SHAMAROVA, Evelina et al. Backward-stochastic-differential-equation approach to modeling of gene expression. Physical Review E : Covering Statistical, Nonlinear, Biological, and Soft Matter Physics, v. 95, n. 3, 2017Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.95.032418. Acesso em: 15 jul. 2024.
APA
Shamarova, E., Chertovskih, R., Ramos, A. F., & Aguiar, P. de C. (2017). Backward-stochastic-differential-equation approach to modeling of gene expression. Physical Review E : Covering Statistical, Nonlinear, Biological, and Soft Matter Physics, 95( 3). doi:10.1103/PhysRevE.95.032418
NLM
Shamarova E, Chertovskih R, Ramos AF, Aguiar P de C. Backward-stochastic-differential-equation approach to modeling of gene expression [Internet]. Physical Review E : Covering Statistical, Nonlinear, Biological, and Soft Matter Physics. 2017 ; 95( 3):[citado 2024 jul. 15 ] Available from: https://doi.org/10.1103/PhysRevE.95.032418
Vancouver
Shamarova E, Chertovskih R, Ramos AF, Aguiar P de C. Backward-stochastic-differential-equation approach to modeling of gene expression [Internet]. Physical Review E : Covering Statistical, Nonlinear, Biological, and Soft Matter Physics. 2017 ; 95( 3):[citado 2024 jul. 15 ] Available from: https://doi.org/10.1103/PhysRevE.95.032418
Artigo de periodico
Stochastic model for gene transcription on Drosophila melanogaster embryos (2016)
Prata, Guilherme Nery; Hornos, José Eduardo Martinho; Ramos, Alexandre Ferreira
Source: Physical Review E (Statistical, Nonlinear, and Soft Matter Physics). Unidade: EACH
Subjects: PROCESSOS ESTOCÁSTICOS, DROSOPHILA, EXPRESSÃO GÊNICA, BIOLOGIA MOLECULAR
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ABNT
PRATA, Guilherme Nery e HORNOS, José Eduardo Martinho e RAMOS, Alexandre Ferreira. Stochastic model for gene transcription on Drosophila melanogaster embryos. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), v. 93, n. 2, p. 022403-1 - 022403-10, 2016Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.93.022403. Acesso em: 15 jul. 2024.
APA
Prata, G. N., Hornos, J. E. M., & Ramos, A. F. (2016). Stochastic model for gene transcription on Drosophila melanogaster embryos. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 93( 2), 022403-1 - 022403-10. doi:10.1103/PhysRevE.93.022403
NLM
Prata GN, Hornos JEM, Ramos AF. Stochastic model for gene transcription on Drosophila melanogaster embryos [Internet]. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics). 2016 ; 93( 2): 022403-1 - 022403-10.[citado 2024 jul. 15 ] Available from: https://doi.org/10.1103/PhysRevE.93.022403
Vancouver
Prata GN, Hornos JEM, Ramos AF. Stochastic model for gene transcription on Drosophila melanogaster embryos [Internet]. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics). 2016 ; 93( 2): 022403-1 - 022403-10.[citado 2024 jul. 15 ] Available from: https://doi.org/10.1103/PhysRevE.93.022403
Artigo de periodico
Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic (2013)
Kim, Ah-Ram; Martinez, Carlos; Ionides, John; Ramos, Alexandre Ferreira; Ludwig, Michael Z; Ogawa, Nobuo; Sharp, David H; Reinitz, John
Source: PLoS Genetics. Unidade: EACH
Subjects: DROSOPHILA, EXPRESSÃO GÊNICA, GENÔMICA, DNA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
KIM, Ah-Ram et al. Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic. PLoS Genetics, v. 9, n. 2, p. e1003243-1 - e1003243-18, 2013Tradução . . Disponível em: https://doi.org/10.1371/journal.pgen.1003243. Acesso em: 15 jul. 2024.
APA
Kim, A. -R., Martinez, C., Ionides, J., Ramos, A. F., Ludwig, M. Z., Ogawa, N., et al. (2013). Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic. PLoS Genetics, 9( 2), e1003243-1 - e1003243-18. doi:10.1371/journal.pgen.1003243
NLM
Kim A-R, Martinez C, Ionides J, Ramos AF, Ludwig MZ, Ogawa N, Sharp DH, Reinitz J. Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic [Internet]. PLoS Genetics. 2013 ; 9( 2): e1003243-1 - e1003243-18.[citado 2024 jul. 15 ] Available from: https://doi.org/10.1371/journal.pgen.1003243
Vancouver
Kim A-R, Martinez C, Ionides J, Ramos AF, Ludwig MZ, Ogawa N, Sharp DH, Reinitz J. Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic [Internet]. PLoS Genetics. 2013 ; 9( 2): e1003243-1 - e1003243-18.[citado 2024 jul. 15 ] Available from: https://doi.org/10.1371/journal.pgen.1003243

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