Large‐scale pathogenicity prediction analysis of cancer‐associated kinase mutations reveals variability in sensitivity and specificity of computational methods

Large‐scale pathogenicity prediction analysis of cancer‐associated kinase mutations reveals variability in sensitivity and specificity of computational methods

Abstract Background Mutations in kinases are the most frequent genetic alterations in cancer; however, experimental evidence establishing their cancerous nature is available only for a small fraction of these mutants. Aims Predicition analysis of kinome mutations is the primary aim of this study. Fu...

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Main Authors: Sravani Akula, Sai Charitha Mullaguri, Niklas Max Melton, Archana Katta, Venkata Sai Giridhar Reddy Naga, Shyamson Kandula, Raj Kumar Pedada, Janakiraman Subramanian, Rama Krishna Kancha
Format: Article
Jezik:English
Izdano: Wiley 2023-08-01
Serija:Cancer Medicine
Teme:
kinase
pathogenicity prediction
point mutations
prediction accuracy
sensitivity and specificity
Online dostop:https://doi.org/10.1002/cam4.6324

Internet

https://doi.org/10.1002/cam4.6324

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