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In Silico Tools for Predicting Novel Epitopes.
Barra, Carolina; Nilsson, Jonas Birkelund; Saksager, Astrid; Carri, Ibel; Deleuran, Sebastian; Garcia Alvarez, Heli M; Høie, Magnus Haraldson; Li, Yuchen; Clifford, Joakim Nøddeskov; Wan, Yat-Tsai Richie; Moreta, Lys Sanz; Nielsen, Morten.
Affiliation
  • Barra C; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark. carolet@dtu.dk.
  • Nilsson JB; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Saksager A; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Carri I; Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina.
  • Deleuran S; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Garcia Alvarez HM; Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina.
  • Høie MH; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Li Y; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Clifford JN; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Wan YR; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Moreta LS; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
  • Nielsen M; Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
Methods Mol Biol ; 2813: 245-280, 2024.
Article in En | MEDLINE | ID: mdl-38888783
ABSTRACT
Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Simulation / Epitopes, T-Lymphocyte / Epitopes, B-Lymphocyte / Computational Biology Limits: Animals / Humans Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2024 Document type: Article Affiliation country: Denmark

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Simulation / Epitopes, T-Lymphocyte / Epitopes, B-Lymphocyte / Computational Biology Limits: Animals / Humans Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2024 Document type: Article Affiliation country: Denmark