INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases

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Abstract Identifying hyperactive kinases in cancer is crucial for individualized treatment with specific inhibitors. Kinase activity can be discerned from global protein phosphorylation profiles obtained with mass spectrometry‐based phosphoproteomics. A major challenge is to relate such profiles to...

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Bibliographic Details
Main Authors: Robin Beekhof, Carolien van Alphen, Alex A Henneman, Jaco C Knol, Thang V Pham, Frank Rolfs, Mariette Labots, Evan Henneberry, Tessa YS Le Large, Richard R de Haas, Sander R Piersma, Valentina Vurchio, Andrea Bertotti, Livio Trusolino, Henk MW Verheul, Connie R Jimenez
Format: Article
Language:English
Published: Springer Nature 2019-04-01
Series:Molecular Systems Biology
Subjects:
cancer
computational tool
drug selection
kinase–substrate phosphorylation network
single‐sample analysis
Online Access:https://doi.org/10.15252/msb.20188250

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