Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinomaResearch in context

Authors: Ana Patiño-García, Elizabeth Guruceaga, Maria Pilar Andueza, Marimar Ocón, Jafait Junior Fodop Sokoudjou, Nicolás de Villalonga Zornoza, Gorka Alkorta-Aranburu, Ibon Tamayo Uria, Alfonso Gurpide, Carlos Camps, Eloísa Jantus-Lewintre, Maria Navamuel-Andueza, Miguel F. Sanmamed, Ignacio Melero, Mohamed Elgendy, Juan Pablo Fusco, Javier J. Zulueta, Juan P. de-Torres, Gorka Bastarrika, Luis Seijo, Ruben Pio, Luis M. Montuenga, Mikel Hernáez, Idoia Ochoa, Jose Luis Perez-Gracia

Source: EBioMedicine, Vol 102, Iss , Pp 105048- (2024)

Subject Terms: Cancer risk, Extreme phenotypes, Whole exome sequencing, Tobacco, Lung adenocarcinoma, Medicine, Medicine (General), R5-920

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2352396424000835; https://doaj.org/toc/2352-3964

Access URL: https://doaj.org/article/325b5d8d436b42f0be4be23054440e34