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Deep Learning and Transformers in MHC-Peptide Binding and Presentation Towards Personalized Vaccines in Cancer Immunology: A Brief Review

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Practical Applications of Computational Biology and Bioinformatics, 17th International Conference (PACBB 2023) (PACBB 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 743))

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Abstract

Cancer immunology is a new alternative to traditional cancer treatments like radiotherapy and chemotherapy. There are some strategies, but neoantigen detection for developing cancer vaccines are methods with a high impact in recent years. However, neoantigen detection depends on the correct prediction of peptide-MHC binding. Furthermore, transformers are considered a revolution in artificial intelligence with a high impact on NLP tasks. Since amino acids and proteins could be considered like words and sentences, the peptide-MHC binding prediction problem could be seen as a NLP task. Therefore, in this work, we performed a systematic literature review of deep learning and transformer methods used in peptide-MHC binding and presentation prediction. We analyzed how ANNs, CNNs, RNNs, and Transformer are used.

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Author information

Authors and Affiliations

  1. Universidad La Salle, Arequipa, Peru

    Vicente Enrique Machaca & Valeria Goyzueta

  2. Universidad Católica San Pablo, Arequipa, Peru

    Maria Cruz & Yvan Tupac

Authors
  1. Vicente Enrique Machaca
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  2. Valeria Goyzueta
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  3. Maria Cruz
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  4. Yvan Tupac
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Corresponding author

Correspondence to Vicente Enrique Machaca .

Editor information

Editors and Affiliations

  1. Centro de Engenharia Biológica, Universidade de Vigo, Braga, Portugal

    Miguel Rocha

  2. Computer Science Department, University of Minho, Vigo, Spain

    Florentino Fdez-Riverola

  3. Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates

    Mohd Saberi Mohamad

  4. University of Salamanca, Salamanca, Spain

    Ana Belén Gil-González

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Machaca, V.E., Goyzueta, V., Cruz, M., Tupac, Y. (2023). Deep Learning and Transformers in MHC-Peptide Binding and Presentation Towards Personalized Vaccines in Cancer Immunology: A Brief Review. In: Rocha, M., Fdez-Riverola, F., Mohamad, M.S., Gil-González, A.B. (eds) Practical Applications of Computational Biology and Bioinformatics, 17th International Conference (PACBB 2023). PACBB 2023. Lecture Notes in Networks and Systems, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-031-38079-2_2

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