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Computational Tactics for Precision Cancer Network Biology

Network biology has garnered tremendous attention in understanding complex systems of cancer, because the mechanisms underlying cancer involve the perturbations in the specific function of molecular networks, rather than a disorder of a single gene. In this article, we review the various computation...

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Detalles Bibliográficos
Autores principales: Park, Heewon, Miyano, Satoru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695754/
https://www.ncbi.nlm.nih.gov/pubmed/36430875
http://dx.doi.org/10.3390/ijms232214398
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author Park, Heewon
Miyano, Satoru
author_facet Park, Heewon
Miyano, Satoru
author_sort Park, Heewon
collection PubMed
description Network biology has garnered tremendous attention in understanding complex systems of cancer, because the mechanisms underlying cancer involve the perturbations in the specific function of molecular networks, rather than a disorder of a single gene. In this article, we review the various computational tactics for gene regulatory network analysis, focused especially on personalized anti-cancer therapy. This paper covers three major topics: (1) cell line’s (or patient’s) cancer characteristics specific gene regulatory network estimation, which enables us to reveal molecular interplays under varying conditions of cancer characteristics of cell lines (or patient); (2) computational approaches to interpret the multitudinous and massive networks; (3) network-based application to uncover molecular mechanisms of cancer and related marker identification. We expect that this review will help readers understand personalized computational network biology that plays a significant role in precision cancer medicine.
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spelling pubmed-96957542022-11-26 Computational Tactics for Precision Cancer Network Biology Park, Heewon Miyano, Satoru Int J Mol Sci Review Network biology has garnered tremendous attention in understanding complex systems of cancer, because the mechanisms underlying cancer involve the perturbations in the specific function of molecular networks, rather than a disorder of a single gene. In this article, we review the various computational tactics for gene regulatory network analysis, focused especially on personalized anti-cancer therapy. This paper covers three major topics: (1) cell line’s (or patient’s) cancer characteristics specific gene regulatory network estimation, which enables us to reveal molecular interplays under varying conditions of cancer characteristics of cell lines (or patient); (2) computational approaches to interpret the multitudinous and massive networks; (3) network-based application to uncover molecular mechanisms of cancer and related marker identification. We expect that this review will help readers understand personalized computational network biology that plays a significant role in precision cancer medicine. MDPI 2022-11-19 /pmc/articles/PMC9695754/ /pubmed/36430875 http://dx.doi.org/10.3390/ijms232214398 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Park, Heewon
Miyano, Satoru
Computational Tactics for Precision Cancer Network Biology
title Computational Tactics for Precision Cancer Network Biology
title_full Computational Tactics for Precision Cancer Network Biology
title_fullStr Computational Tactics for Precision Cancer Network Biology
title_full_unstemmed Computational Tactics for Precision Cancer Network Biology
title_short Computational Tactics for Precision Cancer Network Biology
title_sort computational tactics for precision cancer network biology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695754/
https://www.ncbi.nlm.nih.gov/pubmed/36430875
http://dx.doi.org/10.3390/ijms232214398
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