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  2. Patient-specific Boolean models of signalling networks guide personalised treatments

    1. Arnau Montagud
    2. Jonas Béal
    3. Luis Tobalina
    4. Pauline Traynard
    5. Vigneshwari Subramanian
    6. Bence Szalai
    7. Róbert Alföldi
    8. László Puskás
    9. Alfonso Valencia
    10. Emmanuel Barillot
    11. Julio Saez-Rodriguez
    12. Laurence Calzone

    • Curated by eLife

      Evaluation Summary:

      This paper presents a mathematical model for prioritizing drugs for prostate cancer patients based on signal network database. The manuscript is of broad interest to the field of oncology and precision medicine. The methodology developed is sophisticated and relevant to real patient prostate cancer data. The predictions from the model are validated in an experimental setting and provide suggestions for the personalisation of prostate cancer treatment. The study can serve as a roadmap for future development of predictive, personalized models.

      (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

    Reviewed by eLife

    5 evaluationsAppears in 2 listsLatest version Latest activity