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A tumor can be thought of as an ecosystem, which critically means that we cannot just consider it as a collection of mutated cells but more as a complex system of many interacting cellular and microenvironmental elements. At its simplest, a…

种群与进化 · 定量生物学 2013-05-03 Jill Gallaher , Alexander R. A. Anderson

Genomic alterations lead to cancer complexity and form a major hurdle for a comprehensive understanding of the molecular mechanisms underlying oncogenesis. In this review, we describe the recent advances in studying cancer-associated genes…

分子网络 · 定量生物学 2007-12-24 Edwin Wang , Anne Lenferink , Maureen O'Connor-McCourt

Motivation. Cancer heterogeneity is observed at multiple biological levels. To improve our understanding of these differences and their relevance in medicine, approaches to link organ- and tissue-level information from diagnostic images and…

定量方法 · 定量生物学 2020-05-19 Nova F. Smedley , Suzie El-Saden , William Hsu

The emergence of acquired drug resistance in cancer represents a major barrier to treatment success. While research has traditionally focused on genetic sources of resistance, recent findings suggest that cancer cells can acquire transient…

种群与进化 · 定量生物学 2020-02-25 Einar Bjarki Gunnarsson , Subhajyoti De , Kevin Leder , Jasmine Foo

Cancer forms a robust system and progresses as stages over time typically with increasing aggressiveness and worsening prognosis. Characterizing these stages and identifying the genes driving transitions between them is critical to…

分子网络 · 定量生物学 2014-02-04 Sriganesh Srihari , Venkatesh Raman , Hon Wai Leong , Mark A. Ragan

We present a general computational theory of cancer and its developmental dynamics. The theory is based on a theory of the architecture and function of developmental control networks which guide the formation of multicellular organisms.…

分子网络 · 定量生物学 2011-11-16 Eric Werner

One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed…

Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of…

Complex gene interactions play a significant role in cancer progression, driving cellular behaviors that contribute to tumor growth, invasion, and metastasis. Gene co-expression networks model the functional connectivity between genes under…

分子网络 · 定量生物学 2024-11-27 Radwa Adel , Ercan Engin Kuruoglu

Identifying driver genes is crucial for understanding oncogenesis and developing targeted cancer therapies. Driver discovery methods using protein or pathway networks rely on traditional network science measures, focusing on nodes, edges,…

Cancer is a complex disease driven by dynamic regulatory shifts that cannot be fully captured by individual molecular profiling. We employ a data-driven approach to construct a coarse-grained dynamic network model based on hallmark…

定量方法 · 定量生物学 2025-02-28 Jiahe Wang , Yan Wu , Yuke Hou , Yang Li , Dachuan Xu , Changjing Zhuge , Yue Han

Cancer is a disease of cellular regulation, often initiated by genetic mutation within cells, and leading to a heterogeneous cell population within tissues. In the competition for nutrients and growth space within the tumors the phenotype…

种群与进化 · 定量生物学 2017-08-08 András Szabó , Roeland M. H. Merks

We study the effect of intratumor heterogeneity in the likelihood of cancer cells moving from a primary tumor to other sites in the human body, generating a metastatic process. We model different scenarios of competition between tumor cells…

种群与进化 · 定量生物学 2025-10-28 André Rocha , Claudia Manini , José I López , Annick Laruelle

Phenotype variations define heterogeneity of biological and molecular systems, which play a crucial role in several mechanisms. Heterogeneity has been demonstrated in tumor cells. Here, samples from blood of patients affected from colon…

生物物理 · 物理学 2015-11-09 Giuseppina Simone

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level…

分子网络 · 定量生物学 2012-11-22 James West , Ginestra Bianconi , Simone Severini , Andrew Teschendorff

The unwelcome evolution of malignancy during cancer progression emerges through a selection process in a complex heterogeneous population structure. In the present work, we investigate evolutionary dynamics in a phenotypically heterogeneous…

种群与进化 · 定量生物学 2018-02-07 Ali Mahdipour Shirayeh , Kamran Kaveh , Mohammad Kohandel , Siv Sivaloganathan

Primary tumors infrequently lead to demise of cancer patients; instead, mortality and a significant degree of morbidity result from the growth of secondary tumors in distant organs (metastasis). It is well-known that malignant tumors induce…

组织与器官 · 定量生物学 2015-10-09 Arianna Bianchi , Konstantinos Syrigos , Georgios Lolas

An endogenous molecular-cellular network for both normal and abnormal functions is assumed to exist. This endogenous network forms a nonlinear stochastic dynamical system, with many stable attractors in its functional landscape. Normal or…

亚细胞过程 · 定量生物学 2007-09-06 P. Ao , D. Galas , L. Hood , X. -M. Zhu

Recent evidence suggests that nongenetic (epigenetic) mechanisms play an important role at all stages of cancer evolution. In many cancers, these mechanisms have been observed to induce dynamic switching between two or more cell states,…

定量方法 · 定量生物学 2023-06-16 Einar Bjarki Gunnarsson , Jasmine Foo , Kevin Leder

There is a widening recognition that cancer cells are products of complex developmental processes. Carcinogenesis and metastasis formation are increasingly described as systems-level, network phenomena. Here we propose that malignant…

分子网络 · 定量生物学 2013-09-18 David M. Gyurko , Daniel V. Veres , Dezso Modos , Katalin Lenti , Tamas Korcsmaros , Peter Csermely
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