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Cancer Systems Biology
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Abstract
In contrast to prevailing wisdom that cancer is a genetic disease that evolves via Darwinian selection, it is increasingly recognized that in addition to genetic mutations, intratumoral heterogeneity also results through non-genetic mechanisms. Furthermore, it is now evident that the malignant phenotype results from complex interactions between genetic and non-genetic mechanisms. These interactions contribute to functional changes across multiple spatiotemporal scales, from molecular to cellular to tissue level, creating a heterogeneous cancer cell population. Cancer Systems Biology is a comprehensive, up-to-date treatise that addresses these issues. The main intent of this compendium is to encourage cross-pollination of ideas from experts in multiple disciplines including basic and translational science researchers, systems/mathematical biologists, and biophysicists and clinicians interested in decoding a systems-level emergent view of cancer so that a deeper understanding of disease progression can be gained and more effective treatment strategies can be designed.
Oxford University PressOxford
Title: Cancer Systems Biology
Description:
Abstract
In contrast to prevailing wisdom that cancer is a genetic disease that evolves via Darwinian selection, it is increasingly recognized that in addition to genetic mutations, intratumoral heterogeneity also results through non-genetic mechanisms.
Furthermore, it is now evident that the malignant phenotype results from complex interactions between genetic and non-genetic mechanisms.
These interactions contribute to functional changes across multiple spatiotemporal scales, from molecular to cellular to tissue level, creating a heterogeneous cancer cell population.
Cancer Systems Biology is a comprehensive, up-to-date treatise that addresses these issues.
The main intent of this compendium is to encourage cross-pollination of ideas from experts in multiple disciplines including basic and translational science researchers, systems/mathematical biologists, and biophysicists and clinicians interested in decoding a systems-level emergent view of cancer so that a deeper understanding of disease progression can be gained and more effective treatment strategies can be designed.
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