Machine learning methods and harmonized datasets improve immunogenic neoantigen prediction-Reference-Cited by-同舟云学术

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Machine learning methods and harmonized datasets improve immunogenic neoantigen prediction

Published:2023-11 Issue:11 Volume:56 Page:2650-2663.e6
ISSN:1074-7613
Container-title:Immunity
language:en
Short-container-title:Immunity

Author:

Müller Markus,Huber Florian,Arnaud Marion,Kraemer Anne I.,Altimiras Emma Ricart,Michaux Justine,Taillandier-Coindard Marie,Chiffelle Johanna,Murgues Baptiste,Gehret Talita,Auger Aymeric,Stevenson Brian J.,Coukos George,Harari Alexandre,Bassani-Sternberg Michal

Funder

Swiss Cancer Research Foundation

Fondation ISREC

Ludwig Institute for Cancer Research

Swiss Cancer Foundation

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Elsevier BV

Subject

Infectious Diseases,Immunology,Immunology and Allergy

Reference70 articles.

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3. Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors;Chen;J. Clin. Invest.,2019

4. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer;Rizvi;Science,2015

5. Genetic basis for clinical response to CTLA-4 blockade in melanoma;Snyder;N. Engl. J. Med.,2014

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