Systematic analysis of splice-site-creating mutations in cancer (2018)
- Authors:
- USP affiliated authors: NOUSHMEHR, HOUTAN - FMRP ; CARLOTTI JUNIOR, CARLOS GILBERTO - FMRP ; SANTOS, JOSÉ SEBASTIÃO DOS - FMRP ; KEMP, RAFAEL - FMRP ; SANKARANKUTTY, AJITH KUMAR - FMRP ; TIRAPELLI, DANIELA PRETTI DA CUNHA - FMRP
- Unidade: FMRP
- DOI: 10.1016/j.celrep.2018.03.052
- Subjects: RNA; MUTAÇÃO; GENOMAS; NEOPLASIAS; BIOINFORMÁTICA
- Keywords: Mutations of clinical relevance; Splicing
- Language: Inglês
- Imprenta:
- Source:
- Título: Cell Reports
- ISSN: 2211-1247
- Volume/Número/Paginação/Ano: v. 23, n. 1, p. 270-281.e3, 2018
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: cc-by
-
ABNT
JAYASINGHE, Reyka G. et al. Systematic analysis of splice-site-creating mutations in cancer. Cell Reports, v. 23, n. 1, p. 270-281.e3, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.celrep.2018.03.052. Acesso em: 29 dez. 2025. -
APA
Jayasinghe, R. G., Noushmehr, H., Carlotti Júnior, C. G., Santos, J. S. dos, Kemp, R., Sankarankutty, A. K., & Tirapelli, D. P. da C. (2018). Systematic analysis of splice-site-creating mutations in cancer. Cell Reports, 23( 1), 270-281.e3. doi:10.1016/j.celrep.2018.03.052 -
NLM
Jayasinghe RG, Noushmehr H, Carlotti Júnior CG, Santos JS dos, Kemp R, Sankarankutty AK, Tirapelli DP da C. Systematic analysis of splice-site-creating mutations in cancer [Internet]. Cell Reports. 2018 ; 23( 1): 270-281.e3.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1016/j.celrep.2018.03.052 -
Vancouver
Jayasinghe RG, Noushmehr H, Carlotti Júnior CG, Santos JS dos, Kemp R, Sankarankutty AK, Tirapelli DP da C. Systematic analysis of splice-site-creating mutations in cancer [Internet]. Cell Reports. 2018 ; 23( 1): 270-281.e3.[citado 2025 dez. 29 ] Available from: https://doi.org/10.1016/j.celrep.2018.03.052 - 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: 10.1016/j.celrep.2018.03.052 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
002937702.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
