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Artigo de periodico-carta/editorial
Translational and comparative research on innovative anti-cancer therapies [Editorial] (2023)
Queiroga, Felisbina ; Cogliati, Bruno
Source: Cancers. Unidade: FMVZ
Subjects: NEOPLASIAS, ONCOLOGIA VETERINÁRIA, ONCOLOGIA
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ABNT
QUEIROGA, Felisbina e COGLIATI, Bruno. Translational and comparative research on innovative anti-cancer therapies [Editorial]. Cancers. Basel: Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo. Disponível em: https://doi.org/10.3390/cancers15041335. Acesso em: 06 nov. 2024. , 2023
APA
Queiroga, F., & Cogliati, B. (2023). Translational and comparative research on innovative anti-cancer therapies [Editorial]. Cancers. Basel: Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo. doi:10.3390/cancers15041335
NLM
Queiroga F, Cogliati B. Translational and comparative research on innovative anti-cancer therapies [Editorial] [Internet]. Cancers. 2023 ; 15( 4): 1-3.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers15041335
Vancouver
Queiroga F, Cogliati B. Translational and comparative research on innovative anti-cancer therapies [Editorial] [Internet]. Cancers. 2023 ; 15( 4): 1-3.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers15041335
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: 06 nov. 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 nov. 06 ] 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 nov. 06 ] Available from: https://doi.org/10.3390/cancers14030633
Artigo de periodico
Reproducibility of gene expression signatures in diffuse large B-cell lymphoma (2022)
Plaça, Jessica Rodrigues; Diepstra, Arjan; Los, Tjitske; Mendeville, Matías; Seitz, Annika; Lugtenburg, Pieternella J.; Zijlstra, Josée; Lam, King; Silva Junior, Wilson Araújo da ; Ylstra, Bauke; Jong, Daphne de; Berg, Anke van den; Nijland, Marcel
Source: Cancers. Unidade: FMRP
Subjects: LINFOMA, EXPRESSÃO GÊNICA, NEOPLASIAS
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ABNT
PLAÇA, Jessica Rodrigues et al. Reproducibility of gene expression signatures in diffuse large B-cell lymphoma. Cancers, v. 14, n. 5, p. 1-15, 2022Tradução . . Disponível em: https://doi.org/10.3390/cancers14051346. Acesso em: 06 nov. 2024.
APA
Plaça, J. R., Diepstra, A., Los, T., Mendeville, M., Seitz, A., Lugtenburg, P. J., et al. (2022). Reproducibility of gene expression signatures in diffuse large B-cell lymphoma. Cancers, 14( 5), 1-15. doi:10.3390/cancers14051346
NLM
Plaça JR, Diepstra A, Los T, Mendeville M, Seitz A, Lugtenburg PJ, Zijlstra J, Lam K, Silva Junior WA da, Ylstra B, Jong D de, Berg A van den, Nijland M. Reproducibility of gene expression signatures in diffuse large B-cell lymphoma [Internet]. Cancers. 2022 ; 14( 5): 1-15.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers14051346
Vancouver
Plaça JR, Diepstra A, Los T, Mendeville M, Seitz A, Lugtenburg PJ, Zijlstra J, Lam K, Silva Junior WA da, Ylstra B, Jong D de, Berg A van den, Nijland M. Reproducibility of gene expression signatures in diffuse large B-cell lymphoma [Internet]. Cancers. 2022 ; 14( 5): 1-15.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers14051346
Artigo de periodico
YAP1 is a potential predictive molecular biomarker for response to SMO inhibitor in medulloblastoma cells (2021)
Cruzeiro, Gustavo Alencastro Veiga ; Magalhães, Taciani de Almeida; Sousa, Graziella Ribeiro de ; Silva, Ricardo Bonfim; Biagi Junior, Carlos Alberto Oliveira de ; Chagas, Pablo Ferreira das ; Queiroz, Rosane Gomes de Paula; Scrideli, Carlos Alberto ; Tone, Luiz Gonzaga ; Valera, Elvis Terci
Source: Cancers. Unidade: FMRP
Subjects: MEDULOBLASTOMA, GENÔMICA, NEOPLASIAS, BIOMARCADORES, TERAPIA COMBINADA
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ABNT
CRUZEIRO, Gustavo Alencastro Veiga et al. YAP1 is a potential predictive molecular biomarker for response to SMO inhibitor in medulloblastoma cells. Cancers, v. 13, n. 24, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.3390/cancers13246249. Acesso em: 06 nov. 2024.
APA
Cruzeiro, G. A. V., Magalhães, T. de A., Sousa, G. R. de, Silva, R. B., Biagi Junior, C. A. O. de, Chagas, P. F. das, et al. (2021). YAP1 is a potential predictive molecular biomarker for response to SMO inhibitor in medulloblastoma cells. Cancers, 13( 24), 1-11. doi:10.3390/cancers13246249
NLM
Cruzeiro GAV, Magalhães T de A, Sousa GR de, Silva RB, Biagi Junior CAO de, Chagas PF das, Queiroz RG de P, Scrideli CA, Tone LG, Valera ET. YAP1 is a potential predictive molecular biomarker for response to SMO inhibitor in medulloblastoma cells [Internet]. Cancers. 2021 ; 13( 24): 1-11.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers13246249
Vancouver
Cruzeiro GAV, Magalhães T de A, Sousa GR de, Silva RB, Biagi Junior CAO de, Chagas PF das, Queiroz RG de P, Scrideli CA, Tone LG, Valera ET. YAP1 is a potential predictive molecular biomarker for response to SMO inhibitor in medulloblastoma cells [Internet]. Cancers. 2021 ; 13( 24): 1-11.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers13246249
Artigo de periodico
Effects of aerobic exercise training on myomirs expression in cachectic and non-cachectic cancer mice (2021)
Gomes, João Lucas Penteado ; Tobias, Gabriel Cardial ; Fernandes, Tiago ; Silveira, André Casanova ; Negrão, Carlos Eduardo ; Chammas, Roger ; Brum, Patrícia Chakur ; Oliveira, Edilamar Menezes de
Source: Cancers. Unidades: EEFE, FM
Subjects: MICRORNAS, NEOPLASIAS, NEOPLASIAS DO COLON, NEOPLASIAS MAMÁRIAS, CAQUEXIA, TREINAMENTO AERÓBIO, RATOS
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ABNT
GOMES, João Lucas Penteado et al. Effects of aerobic exercise training on myomirs expression in cachectic and non-cachectic cancer mice. Cancers, v. 13, n. 22, 2021Tradução . . Disponível em: https://doi.org/10.3390/cancers13225728. Acesso em: 06 nov. 2024.
APA
Gomes, J. L. P., Tobias, G. C., Fernandes, T., Silveira, A. C., Negrão, C. E., Chammas, R., et al. (2021). Effects of aerobic exercise training on myomirs expression in cachectic and non-cachectic cancer mice. Cancers, 13( 22). doi:10.3390/cancers13225728
NLM
Gomes JLP, Tobias GC, Fernandes T, Silveira AC, Negrão CE, Chammas R, Brum PC, Oliveira EM de. Effects of aerobic exercise training on myomirs expression in cachectic and non-cachectic cancer mice [Internet]. Cancers. 2021 ; 13( 22):[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers13225728
Vancouver
Gomes JLP, Tobias GC, Fernandes T, Silveira AC, Negrão CE, Chammas R, Brum PC, Oliveira EM de. Effects of aerobic exercise training on myomirs expression in cachectic and non-cachectic cancer mice [Internet]. Cancers. 2021 ; 13( 22):[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers13225728
Artigo de periodico
Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer (2020)
Valieris, Renan; Amaro, Lucas; Osório, Cynthia Aparecida Bueno de Toledo; Bueno, Adriana Passos; Mitrowsky, Rafael Andrés Rosales ; Carraro, Dirce Maria; Nunes, Diana Noronha; Dias-Neto, Emmanuel; Silva, Israel Tojal da
Source: Cancers. Unidade: FFCLRP
Subjects: BIOMARCADORES, NEOPLASIAS, DNA, APRENDIZADO COMPUTACIONAL, TERAPÊUTICA MÉDICA, ALGORITMOS, CARCINOGÊNESE, IMUNOTERAPIA, RECOMBINAÇÃO GENÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VALIERIS, Renan et al. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer. Cancers, v. 12, n. 12, p. 1-12, 2020Tradução . . Disponível em: https://doi.org/10.3390/cancers12123687. Acesso em: 06 nov. 2024.
APA
Valieris, R., Amaro, L., Osório, C. A. B. de T., Bueno, A. P., Mitrowsky, R. A. R., Carraro, D. M., et al. (2020). Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer. Cancers, 12( 12), 1-12. doi:10.3390/cancers12123687
NLM
Valieris R, Amaro L, Osório CAB de T, Bueno AP, Mitrowsky RAR, Carraro DM, Nunes DN, Dias-Neto E, Silva IT da. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer [Internet]. Cancers. 2020 ; 12( 12): 1-12.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers12123687
Vancouver
Valieris R, Amaro L, Osório CAB de T, Bueno AP, Mitrowsky RAR, Carraro DM, Nunes DN, Dias-Neto E, Silva IT da. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer [Internet]. Cancers. 2020 ; 12( 12): 1-12.[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/cancers12123687

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