Predicting the Prognostic Value of <i>POLI</i> Expression in Different Cancers via a Machine Learning Approach

Predicting the Prognostic Value of <i>POLI</i> Expression in Different Cancers via a Machine Learning Approach

Translesion synthesis (TLS) is a cell signaling pathway that facilitates the tolerance of replication stress. Increased TLS activity, the particularly elevated expression of TLS polymerases, has been linked to resistance to cancer chemotherapeutics and significantly altered patient outcomes. Buildin...

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Bibliographic Details
Main Authors: Xuan Xu, Majid Jaberi-Douraki, Nicholas A. Wallace
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:International Journal of Molecular Sciences
Subjects:
polymerase iota
cancer survival
machine learning
gene association
gene regulatory network
Online Access:https://www.mdpi.com/1422-0067/23/15/8571

Internet

https://www.mdpi.com/1422-0067/23/15/8571

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