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 Federica;Fiscon Giulia;Paci, Paola
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
Inglese
EIGHTH NATIONAL CONGRESS OF BIOENGINEERING Proceedings
8th National Congress of Bioengineering, GNB 2023
9788855580113
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175875208&partnerID=40&md5=8e3cf6f24facef535b3f9a29adc61598
21/06/2023, 23/06/2023
Padova, Italia
Nazionale
breast cancer subtype
gene signature
computational medicine
No
3
restricted
Conte, Federica; Fiscon, Giulia; Paci, Paola
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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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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