Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Abstract Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (...

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Bibliographic Details
Main Authors: Arnob Sarker, Md. Abdul Aziz, Md. Bayazid Hossen, Md. Manir Hossain Mollah, Al-Amin, Md. Nurul Haque Mollah
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Glioblastoma
Gene expression profiles
Key genes
Drug repurposing
Bioinformatics and machine learning approaches
Online Access:https://doi.org/10.1038/s41598-024-79391-2
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https://doi.org/10.1038/s41598-024-79391-2

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