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

Conference Paper
Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
breast cancer subtype; gene signature; computational medicine
List of contributors:
Paci, Paola; Conte, Federica; Fiscon, Giulia
Authors of the University:
CONTE FEDERICA
Handle:
https://iris.cnr.it/handle/20.500.14243/434868
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175875208&partnerID=40&md5=8e3cf6f24facef535b3f9a29adc61598
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