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Showing 1–4 of 4 results
Advanced filters: Author: Eric J. Jaehnig Clear advanced filters

  • Kinases regulate cellular processes, making their study essential for understanding cellular function and disease. Here, the authors evaluate methods to infer kinase activity from phosphoproteomics data and provide a toolkit to evaluate future methods.

    • Sophia Müller-Dott
    • Eric J. Jaehnig
    • Julio Saez-Rodriguez
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-21

  • Connecting genomics and proteomics allows the development of more efficient and specific treatments for cancer. Here, the authors develop proteogenomic methods to defining cancer signaling in-vivo starting from core needle biopsies and with application to a HER2 breast cancer focused clinical trial.

    • Shankha Satpathy
    • Eric J. Jaehnig
    • Matthew J. Ellis
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-16

  • Phosphoproteomics data analysis is limited by poor phosphosite annotation. Here, the authors use machine learning with pan-cancer data to build a co-regulation network of phosphosites and a model for predicting kinase-substrate associations, providing a framework for systematic data interpretation.

    • Wen Jiang
    • Eric J. Jaehnig
    • Bing Zhang
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-17