GeNWeMME: a network-based computational method for prioritizing groups of significant related genes in cancer (2020)
- Authors:
- USP affiliated authors: SIMÃO, ADENILSO DA SILVA - ICMC ; CUTIGI, JORGE FRANCISCO - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-46417-2_3
- Subjects: NEOPLASIAS; MUTAÇÃO; GENÔMICA; BIOINFORMÁTICA
- Keywords: Cancer bioinformatics; Driver mutations; Significant mutations; Computational method
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Bioinformatics - LNBI
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 11347, p. 29-40, 2020
- Conference titles: Brazilian Symposium on Bioinformatics - BSB
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
CUTIGI, Jorge Francisco e EVANGELISTA, Adriane Feijó e SIMÃO, Adenilso da Silva. GeNWeMME: a network-based computational method for prioritizing groups of significant related genes in cancer. Lecture Notes in Bioinformatics - LNBI. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-46417-2_3. Acesso em: 05 nov. 2024. , 2020 -
APA
Cutigi, J. F., Evangelista, A. F., & Simão, A. da S. (2020). GeNWeMME: a network-based computational method for prioritizing groups of significant related genes in cancer. Lecture Notes in Bioinformatics - LNBI. Cham: Springer. doi:10.1007/978-3-030-46417-2_3 -
NLM
Cutigi JF, Evangelista AF, Simão A da S. GeNWeMME: a network-based computational method for prioritizing groups of significant related genes in cancer [Internet]. Lecture Notes in Bioinformatics - LNBI. 2020 ; 11347 29-40.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-46417-2_3 -
Vancouver
Cutigi JF, Evangelista AF, Simão A da S. GeNWeMME: a network-based computational method for prioritizing groups of significant related genes in cancer [Internet]. Lecture Notes in Bioinformatics - LNBI. 2020 ; 11347 29-40.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-46417-2_3 - Approaches for the identification of driver mutations in cancer: a tutorial from a computational perspective
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Informações sobre o DOI: 10.1007/978-3-030-46417-2_3 (Fonte: oaDOI API)
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