DeepAutoGlioma: a deep learning autoencoder-based multi-omics data integration and classification tools for glioma subtyping

Abstract Background and objective The classification of glioma subtypes is essential for precision therapy. Due to the heterogeneity of gliomas, the subtype-specific molecular pattern can be captured by integrating and analyzing high-throughput omics data from different genomic layers. The developme...

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Dades bibliogràfiques

Autors principals:	Sana Munquad, Asim Bikas Das
Format:	Artigo
Idioma:	Inglês
Publicat:	BMC 2023-11-01
Col·lecció:	BioData Mining
Matèries:	Multi-omics Autoencoder Lower-grade glioma (LGG) Glioblastoma multiforme (GBM) Convolutional neural network (CNN)
Accés en línia:	https://doi.org/10.1186/s13040-023-00349-7
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