ReP USP - Resultado da busca

Trabalho de evento-resumo periodico
Meningioma subgroups associated with functional genomic elements defined by DNA methylation (2019)
Malta, Tathiane Maistro; Snyder, James; Wells, Michael; Carvalho, Ana de; Poisson, Laila; Souza, Camila; Zadeh, Gelareh; Aldape, Kenneth; Tirapelli, Daniela Pretti da Cunha ; Carlotti Júnior, Carlos Gilberto ; Lee, Yan; Kalkanis, Steven; Walbert, Tobias; Noushmehr, Houtan
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: MENINGIOMA, DNA, GENÔMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALTA, Tathiane Maistro et al. Meningioma subgroups associated with functional genomic elements defined by DNA methylation. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-841. Acesso em: 17 nov. 2024. , 2019
APA
Malta, T. M., Snyder, J., Wells, M., Carvalho, A. de, Poisson, L., Souza, C., et al. (2019). Meningioma subgroups associated with functional genomic elements defined by DNA methylation. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-841
NLM
Malta TM, Snyder J, Wells M, Carvalho A de, Poisson L, Souza C, Zadeh G, Aldape K, Tirapelli DP da C, Carlotti Júnior CG, Lee Y, Kalkanis S, Walbert T, Noushmehr H. Meningioma subgroups associated with functional genomic elements defined by DNA methylation [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-841
Vancouver
Malta TM, Snyder J, Wells M, Carvalho A de, Poisson L, Souza C, Zadeh G, Aldape K, Tirapelli DP da C, Carlotti Júnior CG, Lee Y, Kalkanis S, Walbert T, Noushmehr H. Meningioma subgroups associated with functional genomic elements defined by DNA methylation [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-841
Trabalho de evento-resumo periodico
Non-invasive prediction of glioma tumor stemness using multimodal MRI (2019)
Davoodi-Bojd, Esmaeil; Malta, Tathiane; Griffith, Brent; Snyder, James; Walbert, Tobias; Noushmehr, Houtan ; Soltanian-Zadeh, Hamid
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: GLIOMA, TUMOR CARCINOIDE, RESSONÂNCIA MAGNÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAVOODI-BOJD, Esmaeil et al. Non-invasive prediction of glioma tumor stemness using multimodal MRI. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-1939. Acesso em: 17 nov. 2024. , 2019
APA
Davoodi-Bojd, E., Malta, T., Griffith, B., Snyder, J., Walbert, T., Noushmehr, H., & Soltanian-Zadeh, H. (2019). Non-invasive prediction of glioma tumor stemness using multimodal MRI. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-1939
NLM
Davoodi-Bojd E, Malta T, Griffith B, Snyder J, Walbert T, Noushmehr H, Soltanian-Zadeh H. Non-invasive prediction of glioma tumor stemness using multimodal MRI [Internet]. Cancer Research. 2019 ; 79( 13): 1939.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-1939
Vancouver
Davoodi-Bojd E, Malta T, Griffith B, Snyder J, Walbert T, Noushmehr H, Soltanian-Zadeh H. Non-invasive prediction of glioma tumor stemness using multimodal MRI [Internet]. Cancer Research. 2019 ; 79( 13): 1939.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-1939
Trabalho de evento-resumo periodico
Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer (2019)
Abraham, Brian J.; Reddy, Jessica; Fonseca, Marcos Abraão de Souza ; Klein, Isaac A.; Afeyan, Lena K.; Corona, Rosario I.; Cejas, Paloma; Segato, Felipe; Karlan, Beth Y.; Gayther, Simon A.; Freedman, Matthew L.; Noushmehr, Houtan ; Brown, Myles; Matulonis, Ursula A.; Lawrenson, Kate; Yong, Richard A.
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: NEOPLASIAS OVARIANAS, GENÉTICA MÉDICA, TUMOR CARCINOIDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ABRAHAM, Brian J. et al. Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-2615. Acesso em: 17 nov. 2024. , 2019
APA
Abraham, B. J., Reddy, J., Fonseca, M. A. de S., Klein, I. A., Afeyan, L. K., Corona, R. I., et al. (2019). Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-2615
NLM
Abraham BJ, Reddy J, Fonseca MA de S, Klein IA, Afeyan LK, Corona RI, Cejas P, Segato F, Karlan BY, Gayther SA, Freedman ML, Noushmehr H, Brown M, Matulonis UA, Lawrenson K, Yong RA. Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer [Internet]. Cancer Research. 2019 ; 79( 13): 2615.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-2615
Vancouver
Abraham BJ, Reddy J, Fonseca MA de S, Klein IA, Afeyan LK, Corona RI, Cejas P, Segato F, Karlan BY, Gayther SA, Freedman ML, Noushmehr H, Brown M, Matulonis UA, Lawrenson K, Yong RA. Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer [Internet]. Cancer Research. 2019 ; 79( 13): 2615.[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-2615
Trabalho de evento-resumo periodico
Bioinformatic method to define epigenetically regulated enhancer elements associated with cancer (2019)
Sabedot, Thais S.; Cassel, Seth H.; Gao, Galen F.; Lareau, Caleb A.; Chernniak, Andrew; Lazar, Alexander; Kadoch, Cigall; Noushmehr, Houtan
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: BIOINFORMÁTICA, EPIGÊNESE GENÉTICA, NEOPLASIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SABEDOT, Thais S. et al. Bioinformatic method to define epigenetically regulated enhancer elements associated with cancer. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-907. Acesso em: 17 nov. 2024. , 2019
APA
Sabedot, T. S., Cassel, S. H., Gao, G. F., Lareau, C. A., Chernniak, A., Lazar, A., et al. (2019). Bioinformatic method to define epigenetically regulated enhancer elements associated with cancer. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-907
NLM
Sabedot TS, Cassel SH, Gao GF, Lareau CA, Chernniak A, Lazar A, Kadoch C, Noushmehr H. Bioinformatic method to define epigenetically regulated enhancer elements associated with cancer [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-907
Vancouver
Sabedot TS, Cassel SH, Gao GF, Lareau CA, Chernniak A, Lazar A, Kadoch C, Noushmehr H. Bioinformatic method to define epigenetically regulated enhancer elements associated with cancer [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-907
Trabalho de evento-resumo periodico
Deep learning classification of neuro-oncology medical documents (2019)
Wells, Michael; Sabedot, Thais; Malta, Tathiane Maistro; Snyder, James; Poisson, Laila; Noushmehr, Houtan
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: NEUROLOGIA, ONCOLOGIA, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
WELLS, Michael et al. Deep learning classification of neuro-oncology medical documents. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-1640. Acesso em: 17 nov. 2024. , 2019
APA
Wells, M., Sabedot, T., Malta, T. M., Snyder, J., Poisson, L., & Noushmehr, H. (2019). Deep learning classification of neuro-oncology medical documents. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-1640
NLM
Wells M, Sabedot T, Malta TM, Snyder J, Poisson L, Noushmehr H. Deep learning classification of neuro-oncology medical documents [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-1640
Vancouver
Wells M, Sabedot T, Malta TM, Snyder J, Poisson L, Noushmehr H. Deep learning classification of neuro-oncology medical documents [Internet]. Cancer Research. 2019 ; 79( 13):[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-1640
Trabalho de evento-resumo periodico
Pre-surgical identification of diagnostic, prognostic and predictive DNA methylation-based markers in serum (liquid biopsy) of patients harboring gliomas (2019)
Noushmehr, Houtan ; Sabedot, Thais S.; Malta, Tathiane M.; Nelson, Kevin K.; Snyder, James; Wells, Michael; Mosella, Maritza S.; Carvalho, Ana de; Asmaro, karam; Scarpace, Lisa; Robin, Adam M.; Rosenblum, Mark L.; Mikkelsen, Tom; Rock, Jack; Walbert, Tobias; Lee, Ian; Poisson, Laila M.; Kalkanis, Steven N.; Castro, Ana V.
Source: Cancer Research. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: FMRP
Subjects: NEOPLASIAS OVARIANAS, GENÉTICA MÉDICA, TUMOR CARCINOIDE, GLIOMA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NOUSHMEHR, Houtan et al. Pre-surgical identification of diagnostic, prognostic and predictive DNA methylation-based markers in serum (liquid biopsy) of patients harboring gliomas. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1538-7445.AM2019-LB-234. Acesso em: 17 nov. 2024. , 2019
APA
Noushmehr, H., Sabedot, T. S., Malta, T. M., Nelson, K. K., Snyder, J., Wells, M., et al. (2019). Pre-surgical identification of diagnostic, prognostic and predictive DNA methylation-based markers in serum (liquid biopsy) of patients harboring gliomas. Cancer Research. Baltimore: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1158/1538-7445.AM2019-LB-234
NLM
Noushmehr H, Sabedot TS, Malta TM, Nelson KK, Snyder J, Wells M, Mosella MS, Carvalho A de, Asmaro karam, Scarpace L, Robin AM, Rosenblum ML, Mikkelsen T, Rock J, Walbert T, Lee I, Poisson LM, Kalkanis SN, Castro AV. Pre-surgical identification of diagnostic, prognostic and predictive DNA methylation-based markers in serum (liquid biopsy) of patients harboring gliomas [Internet]. Cancer Research. 2019 ; 79( 13): .[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-LB-234
Vancouver
Noushmehr H, Sabedot TS, Malta TM, Nelson KK, Snyder J, Wells M, Mosella MS, Carvalho A de, Asmaro karam, Scarpace L, Robin AM, Rosenblum ML, Mikkelsen T, Rock J, Walbert T, Lee I, Poisson LM, Kalkanis SN, Castro AV. Pre-surgical identification of diagnostic, prognostic and predictive DNA methylation-based markers in serum (liquid biopsy) of patients harboring gliomas [Internet]. Cancer Research. 2019 ; 79( 13): .[citado 2024 nov. 17 ] Available from: https://doi.org/10.1158/1538-7445.AM2019-LB-234
Trabalho de evento-resumo
Molecular characterization of carcinoma associated fibroblasts and those derived from normal breast tissue (2008)
Rozenchan, Patricia B.; Katayama, Maria Lucia H.; Brentani, Helena; Torres, Cesar H.; Lyra, Eduardo C.; Roela, Rosimeire A.; Folgueira, Maria Aparecida A. K.; Bromberg, Natália; Santos, Marinilce Fagundes dos ; Silva-Junior, Wilson A.; Brentani, M. Mitzi
Source: Abstracts. Conference titles: Annual Meeting American Association for Cancer Research - AACR. Unidade: ICB
Assunto: HISTOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROZENCHAN, Patricia B. et al. Molecular characterization of carcinoma associated fibroblasts and those derived from normal breast tissue. 2008, Anais.. San Diego: Instituto de Ciências Biomédicas, Universidade de São Paulo, 2008. . Acesso em: 17 nov. 2024.
APA
Rozenchan, P. B., Katayama, M. L. H., Brentani, H., Torres, C. H., Lyra, E. C., Roela, R. A., et al. (2008). Molecular characterization of carcinoma associated fibroblasts and those derived from normal breast tissue. In Abstracts. San Diego: Instituto de Ciências Biomédicas, Universidade de São Paulo.
NLM
Rozenchan PB, Katayama MLH, Brentani H, Torres CH, Lyra EC, Roela RA, Folgueira MAAK, Bromberg N, Santos MF dos, Silva-Junior WA, Brentani MM. Molecular characterization of carcinoma associated fibroblasts and those derived from normal breast tissue. Abstracts. 2008 ;[citado 2024 nov. 17 ]
Vancouver
Rozenchan PB, Katayama MLH, Brentani H, Torres CH, Lyra EC, Roela RA, Folgueira MAAK, Bromberg N, Santos MF dos, Silva-Junior WA, Brentani MM. Molecular characterization of carcinoma associated fibroblasts and those derived from normal breast tissue. Abstracts. 2008 ;[citado 2024 nov. 17 ]

USP Schools

ReP

Filtros

Authors

Subjects

Non normalized affiliation