Editorial: Special section on multiscale cancer modeling

The papers in this special section focus on the use of multiscale modeling in the field of cancer research. Cancer is a complex, heterogeneous disease, characterized by many interaction processes on, and across, multiple scales in time and space that act in concert to drive cancer formation, progres...

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Main Authors: Maini, P, Wang, Z
Format: Journal article
Published: Institute of Electrical and Electronics Engineers 2017
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author Maini, P
Wang, Z
author_facet Maini, P
Wang, Z
author_sort Maini, P
collection OXFORD
description The papers in this special section focus on the use of multiscale modeling in the field of cancer research. Cancer is a complex, heterogeneous disease, characterized by many interaction processes on, and across, multiple scales in time and space that act in concert to drive cancer formation, progression, invasion, and metastasis. These processes range from molecular reactions to cell-cell interactions, to tumor growth and invasion on the tissue-scale, and even to larger scales, such as the physiology, pathophysiology, and population scales. In addition, many cancer properties (including, e.g., size, cell density, extracellular ligands, cellular receptors, mutation type(s), phenotypic distribution, vasculature status, blood vessel permeability, and treatment prognosis) are dynamic and patient-dependent, changing and evolving with both time and treatments. For example, cell death rate may change over time due to chemotherapy. All these dynamically changing cancer properties make development of effective cancer therapies extremely difficult. Computational modeling has the potential to predict complex behaviors of cancer, elucidate regulatory mechanisms, and help inform experimental design. Everyone would agree that computer simulations are usually more cost-effective, efficient, and tractable, relative to laboratory experiments.
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spelling oxford-uuid:4c7a52a1-0f08-4afa-8f75-1037171edcfc2022-03-26T15:49:42ZEditorial: Special section on multiscale cancer modelingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4c7a52a1-0f08-4afa-8f75-1037171edcfcSymplectic Elements at OxfordInstitute of Electrical and Electronics Engineers2017Maini, PWang, ZThe papers in this special section focus on the use of multiscale modeling in the field of cancer research. Cancer is a complex, heterogeneous disease, characterized by many interaction processes on, and across, multiple scales in time and space that act in concert to drive cancer formation, progression, invasion, and metastasis. These processes range from molecular reactions to cell-cell interactions, to tumor growth and invasion on the tissue-scale, and even to larger scales, such as the physiology, pathophysiology, and population scales. In addition, many cancer properties (including, e.g., size, cell density, extracellular ligands, cellular receptors, mutation type(s), phenotypic distribution, vasculature status, blood vessel permeability, and treatment prognosis) are dynamic and patient-dependent, changing and evolving with both time and treatments. For example, cell death rate may change over time due to chemotherapy. All these dynamically changing cancer properties make development of effective cancer therapies extremely difficult. Computational modeling has the potential to predict complex behaviors of cancer, elucidate regulatory mechanisms, and help inform experimental design. Everyone would agree that computer simulations are usually more cost-effective, efficient, and tractable, relative to laboratory experiments.
spellingShingle Maini, P
Wang, Z
Editorial: Special section on multiscale cancer modeling
title Editorial: Special section on multiscale cancer modeling
title_full Editorial: Special section on multiscale cancer modeling
title_fullStr Editorial: Special section on multiscale cancer modeling
title_full_unstemmed Editorial: Special section on multiscale cancer modeling
title_short Editorial: Special section on multiscale cancer modeling
title_sort editorial special section on multiscale cancer modeling
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