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Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.
Bulashevska, Alla; Nacsa, Zsófia; Lang, Franziska; Braun, Markus; Machyna, Martin; Diken, Mustafa; Childs, Liam; König, Renate.
Afiliación
  • Bulashevska A; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
  • Nacsa Z; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
  • Lang F; TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany.
  • Braun M; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
  • Machyna M; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
  • Diken M; TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany.
  • Childs L; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
  • König R; Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany.
Front Immunol ; 15: 1394003, 2024.
Article en En | MEDLINE | ID: mdl-38868767
ABSTRACT
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Medicina de Precisión / Inmunoterapia / Antígenos de Neoplasias / Neoplasias Límite: Animals / Humans Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Medicina de Precisión / Inmunoterapia / Antígenos de Neoplasias / Neoplasias Límite: Animals / Humans Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza