English
Related papers

Related papers: Evolution and Controllability of Cancer Networks: …

200 papers

Environmental and genetic mutations can transform the cells in a co-operating healthy tissue into an ecosystem of individualistic tumour cells that compete for space and resources. Various selection forces are responsible for driving the…

Tissues and Organs · Quantitative Biology 2008-10-28 David Basanta , Andreas Deutsch

Cancer results from genetic alterations that disturb the normal cooperative behavior of cells. Recent high-throughput genomic studies of cancer cells have shown that the mutational landscape of cancer is complex and that individual cancers…

Populations and Evolution · Quantitative Biology 2011-11-10 Niko Beerenwinkel , Tibor Antal , David Dingli , Arne Traulsen , Kenneth W. Kinzler , Victor E. Velculescu , Bert Vogelstein , Martin A. Nowak

Significant advances in biotechnology have allowed for simultaneous measurement of molecular data points across multiple genomic and transcriptomic levels from a single tumor/cancer sample. This has motivated systematic approaches to…

The aim of this paper is to discuss the role of robustness and diversity in population dynamics in particular to some properties of the multi-step from healthy tissue to fully malignant tumours. Recent evidence shows that diversity within…

Populations and Evolution · Quantitative Biology 2010-03-12 Tomas Alarcon , Henrik Jeldtoft Jensen

The editing of transcribed RNA by other molecules such that the form of the final product differs from that specified in the corresponding DNA sequence is ubiquitous. This paper uses an abstract, tunable Boolean genetic regulatory network…

Neural and Evolutionary Computing · Computer Science 2015-05-11 Larry Bull

As a discrete approach to genetic regulatory networks, Boolean models provide an essential qualitative description of the structure of interactions among genes and proteins. Boolean models generally assume only two possible states…

Molecular Networks · Quantitative Biology 2007-05-23 Madalena Chaves , Eduardo D. Sontag , Reka Albert

Theoretical and computational tools that can be used in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth is desired. To develop such a predictive model, one must…

Cell Behavior · Quantitative Biology 2015-05-20 Salvatore Torquato

Cancer results from a sequence of genetic and epigenetic changes which lead to a variety of abnormal phenotypes including increased proliferation and survival of somatic cells, and thus, to a selective advantage of pre-cancerous cells. The…

Populations and Evolution · Quantitative Biology 2011-12-05 Erik A. Martens , R. Kostadinov , Carlo C. Maley , Oskar Hallatschek

Identifying genes underlying cancer development is critical to cancer biology and has important implications across prevention, diagnosis and treatment. Cancer sequencing studies aim at discovering genes with high frequencies of somatic…

Applications · Statistics 2013-12-09 Jie Ding , Lorenzo Trippa , Xiaogang Zhong , Giovanni Parmigiani

Despite their potential to address crucial bottlenecks in computing architectures and contribute to the pool of biological inspiration for engineering, pathological biological mechanisms remain absent from computational theory. We hereby…

Neural and Evolutionary Computing · Computer Science 2025-03-18 Rosalia Moreddu , Michael Levin

In this work we present a flexible tool for tumor progression, which simulates the evolutionary dynamics of cancer. Tumor progression implements a multi-type branching process where the key parameters are the fitness landscape, the mutation…

Populations and Evolution · Quantitative Biology 2013-03-22 Johannes G. Reiter , Ivana Bozic , Krishnendu Chatterjee , Martin A. Nowak

Research into somatic mutations in cancer cell DNA and their role in tumour growth and progression between successive stages is crucial for improving our understanding of cancer evolution. Mathematical and computer modelling can provide…

Populations and Evolution · Quantitative Biology 2024-02-26 Andrzej Polanski , Mateusz Kania , Jarosław Gil , Wojciech Łabaj , Ewa Lach , Agnieszka Szczęsna

Recently, there has been a resurgence of interest in rigorous algorithms for the inference of cancer progression from genomic data. The motivations are manifold: (i) growing NGS and single cell data from cancer patients, (ii) need for novel…

Machine Learning · Computer Science 2016-02-25 Daniele Ramazzotti

The genomic profile underlying an individual tumor can be highly informative in the creation of a personalized cancer treatment strategy for a given patient; a practice known as precision oncology. This involves next generation sequencing…

Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations,…

Tissues and Organs · Quantitative Biology 2013-08-29 Caterina A. M. La Porta , Stefano Zapperi , James P. Sethna

In this paper, we analyse large random Boolean networks in terms of a constraint satisfaction problem. We first develop an algorithmic scheme which allows to prune simple logical cascades and under-determined variables, returning thereby…

Statistical Mechanics · Physics 2009-11-11 L. Correale , M. Leone , A. Pagnani , M. Weigt , R. Zecchina

Boolean networks have been proposed as potentially useful models for genetic control. An important aspect of these networks is the stability of their dynamics in response to small perturbations. Previous approaches to stability have assumed…

Molecular Networks · Quantitative Biology 2015-05-13 Andrew Pomerance , Edward Ott , Michelle Girvan , Wolfgang Losert

Cancer is a complex genetic disease involving uncontrolled cell growth and proliferation, and necessitates effective targeting of dysregulated cellular pathways underlying cancer progression. Multiple genetic and epigenetic alterations…

Other Quantitative Biology · Quantitative Biology 2026-01-28 Manish Kumar

The regulation of the cell state is a complex process involving several components. These complex dynamics can be modeled using Boolean networks, allowing us to explain the existence of different cell states and the transition between them.…

Molecular Networks · Quantitative Biology 2010-01-28 Elke K. Markert , Nils Baas , Arnold J. Levine , Alexei Vazquez

Interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions (from molecules in gene regulatory…

Molecular Networks · Quantitative Biology 2023-10-20 Jordan C. Rozum , Colin Campbell , Eli Newby , Fatemeh Sadat Fatemi Nasrollahi , Reka Albert