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, P.. - (2023). (Intervento presentato al convegno 8th National Congress of Bioengineering, GNB 2023 tenutosi a Padova; Italy).

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

Fiscon G.
Secondo
;
Paci P.
Ultimo
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
8th National Congress of Bioengineering, GNB 2023
bioinformatics; breast cancer subtypes; computational medicine; gene signature
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Bioinformatics analyses to identify molecular gene signatures associated with breast cancer phenotypes / Conte, F.; Fiscon, G.; Paci, P.. - (2023). (Intervento presentato al convegno 8th National Congress of Bioengineering, GNB 2023 tenutosi a Padova; Italy).
File allegati a questo prodotto
File Dimensione Formato  
Conte_Bioinformatics_2023.pdf

accesso aperto

Note: http://gnb2023.it/assets/img/proceedings_gnb2023.pdf
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 890.72 kB
Formato Adobe PDF
890.72 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1692563
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact