Autophagy dark genes: Can we find them with machine learning?

Abstract excerpt

Identifying novel genes associated with autophagy (ATG) in man remains an important task for gaining complete understanding on this fundamental physiological process. A machine-learning guided approach can highlight potentially “missing pieces” linking core autophagy genes with understudied, “dark” genes that can help us gain deeper insight into these processes. In this study, we used a set of 103 (out of 288 gene...

Topics

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• Autophagy in Disease and Therapy
• Bioinformatics and Genomic Networks
• CRISPR and Genetic Engineering
• Endoplasmic Reticulum Stress and Disease
• MicroRNA in disease regulation
• Phagocytosis and Immune Regulation
• RNA modifications and cancer
• Ubiquitin and proteasome pathways

Identifiers and source

Literature Corpus work

2d7b0f16-703f-5f1f-abac-4f808103290b

DOI

10.1101/715037