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Artigo de periodico
Unexpected links reflect the noise in networks (2016)
Iambartsev, Anatoli; Perlin, Michael A.; Kovchegov, Yevgeniy; Shulzhenko, Natalia; Mine, Karina L.; Dong, Xiaoxi; Morgun, Andrey
Fonte: Biology Direct. Unidade: IME
Assuntos: GENES, VARIAÇÃO GENÉTICA, GENÉTICA ESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
IAMBARTSEV, Anatoli et al. Unexpected links reflect the noise in networks. Biology Direct, v. 11, n. 1, p. 1-12, 2016Tradução . . Disponível em: https://doi.org/10.1186/s13062-016-0155-0. Acesso em: 07 nov. 2024.
APA
Iambartsev, A., Perlin, M. A., Kovchegov, Y., Shulzhenko, N., Mine, K. L., Dong, X., & Morgun, A. (2016). Unexpected links reflect the noise in networks. Biology Direct, 11( 1), 1-12. doi:10.1186/s13062-016-0155-0
NLM
Iambartsev A, Perlin MA, Kovchegov Y, Shulzhenko N, Mine KL, Dong X, Morgun A. Unexpected links reflect the noise in networks [Internet]. Biology Direct. 2016 ; 11( 1): 1-12.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1186/s13062-016-0155-0
Vancouver
Iambartsev A, Perlin MA, Kovchegov Y, Shulzhenko N, Mine KL, Dong X, Morgun A. Unexpected links reflect the noise in networks [Internet]. Biology Direct. 2016 ; 11( 1): 1-12.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1186/s13062-016-0155-0
Artigo de periodico
Differentially correlated genes in co-expression networks control phenotype transitions (2016)
Thomas, Lina Dornelas; Vyshenska, Dariia; Shulzhenko, Natalia; Iambartsev, Anatoli; Morgun, Andrey
Fonte: F1000Research. Unidade: IME
Assunto: EXPRESSÃO GÊNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
THOMAS, Lina Dornelas et al. Differentially correlated genes in co-expression networks control phenotype transitions. F1000Research, v. 5, p. 2740, 2016Tradução . . Disponível em: https://doi.org/10.12688%2Ff1000research.9708.1. Acesso em: 07 nov. 2024.
APA
Thomas, L. D., Vyshenska, D., Shulzhenko, N., Iambartsev, A., & Morgun, A. (2016). Differentially correlated genes in co-expression networks control phenotype transitions. F1000Research, 5, 2740. doi:10.12688%2Ff1000research.9708.1
NLM
Thomas LD, Vyshenska D, Shulzhenko N, Iambartsev A, Morgun A. Differentially correlated genes in co-expression networks control phenotype transitions [Internet]. F1000Research. 2016 ; 5 2740.[citado 2024 nov. 07 ] Available from: https://doi.org/10.12688%2Ff1000research.9708.1
Vancouver
Thomas LD, Vyshenska D, Shulzhenko N, Iambartsev A, Morgun A. Differentially correlated genes in co-expression networks control phenotype transitions [Internet]. F1000Research. 2016 ; 5 2740.[citado 2024 nov. 07 ] Available from: https://doi.org/10.12688%2Ff1000research.9708.1
Artigo de periodico
Reverse enGENEering of regulatory networks from big data: a roadmap for biologists (2015)
Dong, Xiaoxi; Iambartsev, Anatoli ; Ramsey, Stephen A; Thomas, Lina Dornelas; Shulzhenko, Natalia; Morgun, Andrey
Fonte: Bioinformatics and Biology Insights. Unidade: IME
Assuntos: ESTATÍSTICA APLICADA, BIOESTATÍSTICA, PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DONG, Xiaoxi et al. Reverse enGENEering of regulatory networks from big data: a roadmap for biologists. Bioinformatics and Biology Insights, v. 9, p. 61-74, 2015Tradução . . Disponível em: https://doi.org/10.4137/BBI.S12467. Acesso em: 07 nov. 2024.
APA
Dong, X., Iambartsev, A., Ramsey, S. A., Thomas, L. D., Shulzhenko, N., & Morgun, A. (2015). Reverse enGENEering of regulatory networks from big data: a roadmap for biologists. Bioinformatics and Biology Insights, 9, 61-74. doi:10.4137/BBI.S12467
NLM
Dong X, Iambartsev A, Ramsey SA, Thomas LD, Shulzhenko N, Morgun A. Reverse enGENEering of regulatory networks from big data: a roadmap for biologists [Internet]. Bioinformatics and Biology Insights. 2015 ; 9 61-74.[citado 2024 nov. 07 ] Available from: https://doi.org/10.4137/BBI.S12467
Vancouver
Dong X, Iambartsev A, Ramsey SA, Thomas LD, Shulzhenko N, Morgun A. Reverse enGENEering of regulatory networks from big data: a roadmap for biologists [Internet]. Bioinformatics and Biology Insights. 2015 ; 9 61-74.[citado 2024 nov. 07 ] Available from: https://doi.org/10.4137/BBI.S12467
Artigo de periodico
Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer (2013)
Mine, Karina L; Shulzhenko, Natalia; Iambartsev, Anatoli; Rochman, Mark; Sanson, Gerdine F. O; Lando, Malin; Varma, Sudhir; Skinner, Jeff; Volfovsky, Natalia; Deng, Tao; Brenna, Sylvia Michelina Fernandes; Carvalho, Carmen Regina Nogueira de; Ribalta, Julisa C. L; Bustin, Michael; Matzinger, Polly; Silva, Ismael D. C. G; Lyng, Heidi; Gerbase-Delima, Maria; Morgun, Andrey
Fonte: Nature Communications. Unidade: IME
Assuntos: GENES, CARCINOMA, REGIÃO CERVICAL, BIOESTATÍSTICA
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ABNT
MINE, Karina L et al. Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer. Nature Communications, v. 4, p. 1-11, 2013Tradução . . Disponível em: https://doi.org/10.1038/ncomms2693. Acesso em: 07 nov. 2024.
APA
Mine, K. L., Shulzhenko, N., Iambartsev, A., Rochman, M., Sanson, G. F. O., Lando, M., et al. (2013). Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer. Nature Communications, 4, 1-11. doi:10.1038/ncomms2693
NLM
Mine KL, Shulzhenko N, Iambartsev A, Rochman M, Sanson GFO, Lando M, Varma S, Skinner J, Volfovsky N, Deng T, Brenna SMF, Carvalho CRN de, Ribalta JCL, Bustin M, Matzinger P, Silva IDCG, Lyng H, Gerbase-Delima M, Morgun A. Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer [Internet]. Nature Communications. 2013 ; 4 1-11.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1038/ncomms2693
Vancouver
Mine KL, Shulzhenko N, Iambartsev A, Rochman M, Sanson GFO, Lando M, Varma S, Skinner J, Volfovsky N, Deng T, Brenna SMF, Carvalho CRN de, Ribalta JCL, Bustin M, Matzinger P, Silva IDCG, Lyng H, Gerbase-Delima M, Morgun A. Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer [Internet]. Nature Communications. 2013 ; 4 1-11.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1038/ncomms2693
Artigo de periodico
New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer (2008)
Guzman, Valeska B.; Yambartsev, Anatoli ; Gonçalves-Primo, Amador; Silva, Ismael Dale Cotrim Guerreiro da; Carvalho, Carmen R. N.; Ribalta, Julisa C. L.; Goulart, Luiz Ricardo; Shulzhenko, Natalia; Gerbase-Delima, Maria; Morgun, Andrey
Fonte: Human Molecular Genetics. Unidade: IME
Assuntos: PAPILLOMAVIRUS, NEOPLASIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUZMAN, Valeska B. et al. New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer. Human Molecular Genetics, v. 17, n. 12, p. 1838-1844, 2008Tradução . . Disponível em: https://doi.org/10.1093/hmg/ddn077. Acesso em: 07 nov. 2024.
APA
Guzman, V. B., Yambartsev, A., Gonçalves-Primo, A., Silva, I. D. C. G. da, Carvalho, C. R. N., Ribalta, J. C. L., et al. (2008). New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer. Human Molecular Genetics, 17( 12), 1838-1844. doi:10.1093/hmg/ddn077
NLM
Guzman VB, Yambartsev A, Gonçalves-Primo A, Silva IDCG da, Carvalho CRN, Ribalta JCL, Goulart LR, Shulzhenko N, Gerbase-Delima M, Morgun A. New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer [Internet]. Human Molecular Genetics. 2008 ; 17( 12): 1838-1844.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1093/hmg/ddn077
Vancouver
Guzman VB, Yambartsev A, Gonçalves-Primo A, Silva IDCG da, Carvalho CRN, Ribalta JCL, Goulart LR, Shulzhenko N, Gerbase-Delima M, Morgun A. New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer [Internet]. Human Molecular Genetics. 2008 ; 17( 12): 1838-1844.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1093/hmg/ddn077
Artigo de periodico
Selection of control genes for quantitative RT-PCR based on microarray data (2005)
Shulzhenko, Natalia; Iambartsev, Anatoli; Gonçalves-Primo, Amador; Gerbase-Delima, Maria; Morgun, Andrey
Fonte: Biochemical and Biophysical Research Communications. Unidade: IME
Assunto: GENES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SHULZHENKO, Natalia et al. Selection of control genes for quantitative RT-PCR based on microarray data. Biochemical and Biophysical Research Communications, v. 337, n. 1, p. 306-312, 2005Tradução . . Disponível em: https://doi.org/10.1016/j.bbrc.2005.09.048. Acesso em: 07 nov. 2024.
APA
Shulzhenko, N., Iambartsev, A., Gonçalves-Primo, A., Gerbase-Delima, M., & Morgun, A. (2005). Selection of control genes for quantitative RT-PCR based on microarray data. Biochemical and Biophysical Research Communications, 337( 1), 306-312. doi:10.1016/j.bbrc.2005.09.048
NLM
Shulzhenko N, Iambartsev A, Gonçalves-Primo A, Gerbase-Delima M, Morgun A. Selection of control genes for quantitative RT-PCR based on microarray data [Internet]. Biochemical and Biophysical Research Communications. 2005 ; 337( 1): 306-312.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.bbrc.2005.09.048
Vancouver
Shulzhenko N, Iambartsev A, Gonçalves-Primo A, Gerbase-Delima M, Morgun A. Selection of control genes for quantitative RT-PCR based on microarray data [Internet]. Biochemical and Biophysical Research Communications. 2005 ; 337( 1): 306-312.[citado 2024 nov. 07 ] Available from: https://doi.org/10.1016/j.bbrc.2005.09.048

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