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Common pathways and functional profiles reveal underlying patterns in Breast, Kidney and Lung cancers.

Fecha de publicación:

Autores de CIPF

Grupos de Investigación

Abstract

Cancer is a major health problem which presents a high heterogeneity. In this work we explore omics data from Breast, Kidney and Lung cancers at different levels as signalling pathways, functions and miRNAs, as part of the CAMDA 2019 Hi-Res Cancer Data Integration Challenge. Our goal is to find common functional patterns which give rise to the generic microenvironment in these cancers and contribute to a better understanding of cancer pathogenesis and a possible clinical translation down further studies.

Datos de la publicación

ISSN/ISSNe:
1745-6150, 1745-6150

Biology Direct  BioMed Central

Tipo:
Article
Páginas:
9-9
PubMed:
34039407

Citas Recibidas en Web of Science: 8

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Keywords

  • Artificial intelligence, Cancer, Functional analysis, Pathways, Signaling, Survival, miRNAs

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PID10470. No se ingresará dinero en el CIPF. La ayuda consiste en un estudio genómico (long & read-sequencing) para 25 muestras.

Investigador Principal: CARMEN ESPINÓS ARMERO

EASI- Genomics . 2020

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