Breast cancer is a heterogeneous and complex disease as witnessed by the existence of different subtypes with distinct morphologies and clinical implications. Despite the remarkable advances in understanding the mechanisms underlying breast cancer, this disease is still a major public health problem worldwide and poses significant open challenges. Here, we show how a multi-omics data integration analysis may provide useful insights in the identification of promising molecular signatures associated with the different breast cancer subtypes.

Bioinformatics analyses to identify molecular gene signatures associated with breast cancer phenotypes

Conte F;Fiscon G;Paci;
2023

Abstract

Breast cancer is a heterogeneous and complex disease as witnessed by the existence of different subtypes with distinct morphologies and clinical implications. Despite the remarkable advances in understanding the mechanisms underlying breast cancer, this disease is still a major public health problem worldwide and poses significant open challenges. Here, we show how a multi-omics data integration analysis may provide useful insights in the identification of promising molecular signatures associated with the different breast cancer subtypes.
2023
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
9788855580113
breast cancer subtype
gene signature
computational medicine
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/434868
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