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Cancer Vaccines: State of the Art of the Computational Modeling Approaches
Cancer vaccines are a real application of the extensive knowledge of immunology to the field of oncology. Tumors are dynamic complex systems in which several entities, events, and conditions interact among them resulting in growth, invasion, and metastases. The immune system includes many cells and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591114/ https://www.ncbi.nlm.nih.gov/pubmed/23484073 http://dx.doi.org/10.1155/2013/106407 |
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author | Pappalardo, Francesco Chiacchio, Ferdinando Motta, Santo |
author_facet | Pappalardo, Francesco Chiacchio, Ferdinando Motta, Santo |
author_sort | Pappalardo, Francesco |
collection | PubMed |
description | Cancer vaccines are a real application of the extensive knowledge of immunology to the field of oncology. Tumors are dynamic complex systems in which several entities, events, and conditions interact among them resulting in growth, invasion, and metastases. The immune system includes many cells and molecules that cooperatively act to protect the host organism from foreign agents. Interactions between the immune system and the tumor mass include a huge number of biological factors. Testing of some cancer vaccine features, such as the best conditions for vaccine administration or the identification of candidate antigenic stimuli, can be very difficult or even impossible only through experiments with biological models simply because a high number of variables need to be considered at the same time. This is where computational models, and, to this extent, immunoinformatics, can prove handy as they have shown to be able to reproduce enough biological complexity to be of use in suggesting new experiments. Indeed, computational models can be used in addition to biological models. We now experience that biologists and medical doctors are progressively convinced that modeling can be of great help in understanding experimental results and planning new experiments. This will boost this research in the future. |
format | Online Article Text |
id | pubmed-3591114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-35911142013-03-12 Cancer Vaccines: State of the Art of the Computational Modeling Approaches Pappalardo, Francesco Chiacchio, Ferdinando Motta, Santo Biomed Res Int Review Article Cancer vaccines are a real application of the extensive knowledge of immunology to the field of oncology. Tumors are dynamic complex systems in which several entities, events, and conditions interact among them resulting in growth, invasion, and metastases. The immune system includes many cells and molecules that cooperatively act to protect the host organism from foreign agents. Interactions between the immune system and the tumor mass include a huge number of biological factors. Testing of some cancer vaccine features, such as the best conditions for vaccine administration or the identification of candidate antigenic stimuli, can be very difficult or even impossible only through experiments with biological models simply because a high number of variables need to be considered at the same time. This is where computational models, and, to this extent, immunoinformatics, can prove handy as they have shown to be able to reproduce enough biological complexity to be of use in suggesting new experiments. Indeed, computational models can be used in addition to biological models. We now experience that biologists and medical doctors are progressively convinced that modeling can be of great help in understanding experimental results and planning new experiments. This will boost this research in the future. Hindawi Publishing Corporation 2013 2012-12-23 /pmc/articles/PMC3591114/ /pubmed/23484073 http://dx.doi.org/10.1155/2013/106407 Text en Copyright © 2013 Francesco Pappalardo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Pappalardo, Francesco Chiacchio, Ferdinando Motta, Santo Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title | Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title_full | Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title_fullStr | Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title_full_unstemmed | Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title_short | Cancer Vaccines: State of the Art of the Computational Modeling Approaches |
title_sort | cancer vaccines: state of the art of the computational modeling approaches |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3591114/ https://www.ncbi.nlm.nih.gov/pubmed/23484073 http://dx.doi.org/10.1155/2013/106407 |
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