Integrated genomic characterization of oesophageal carcinoma (2017)
- Authors:
- USP affiliated authors: KEMP, RAFAEL - FMRP ; CARLOTTI JUNIOR, CARLOS GILBERTO - FMRP ; SANTOS, JOSÉ SEBASTIÃO DOS - FMRP ; NOUSHMEHR, HOUTAN - FMRP ; TIRAPELLI, DANIELA PRETTI DA CUNHA - FMRP ; SANKARANKUTTY, AJITH KUMAR - FMRP
- Unidade: FMRP
- DOI: 10.1038/nature20805
- Subjects: ADENOCARCINOMA; CARCINOMA DE CÉLULAS ESCAMOSAS; NEOPLASIAS ESOFÁGICAS; NEOPLASIAS GÁSTRICAS; GENOMAS
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: other-oa
-
ABNT
KEMP, Rafael et al. Integrated genomic characterization of oesophageal carcinoma. Nature, v. 541, p. 169-175, 2017Tradução . . Disponível em: https://doi.org/10.1038/nature20805. Acesso em: 29 dez. 2025. -
APA
Kemp, R., Carlotti Júnior, C. G., Santos, J. S. dos, Noushmehr, H., Tirapelli, D. P. da C., & Sankarankuty, A. K. (2017). Integrated genomic characterization of oesophageal carcinoma. Nature, 541, 169-175. doi:10.1038/nature20805 -
NLM
Kemp R, Carlotti Júnior CG, Santos JS dos, Noushmehr H, Tirapelli DP da C, Sankarankuty AK. Integrated genomic characterization of oesophageal carcinoma [Internet]. Nature. 2017 ; 541 169-175.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1038/nature20805 -
Vancouver
Kemp R, Carlotti Júnior CG, Santos JS dos, Noushmehr H, Tirapelli DP da C, Sankarankuty AK. Integrated genomic characterization of oesophageal carcinoma [Internet]. Nature. 2017 ; 541 169-175.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1038/nature20805 - Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers
- Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images
- Machine learning detects pan-cancer ras pathway activation in the cancer genome atlas
- An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics
- Pathogenic germline variants in 10,389 adult cancers
- Comprehensive analysis of alternative splicing across tumors from 8,705 patients
- Scalable open science approach for mutation calling of tumor exomes using multiple genomic pipelines
- Oncogenic signaling pathways in the cancer genome atlas
- Machine learning identifies stemness features associated with oncogenic dedifferentiation
- Comprehensive characterization of cancer driver genes and mutations
Informações sobre o DOI: 10.1038/nature20805 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
