Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A hybrid cellular automaton model of clonal evolution in cancer: the emergence of the glycolytic phenotype.

Journal of theoretical biology - 21 Feb 2008

Gerlee P, Anderson A R A

Abstract excerpt

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cell Proliferation
Share to Cell Transformation, Neoplastic
Share to Extracellular Matrix

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Glycolysis

Share to Models, Biological

Share to Neoplasms

Share to Neoplastic Stem Cells

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 18068192
DOI: 10.1016/j.jtbi.2007.10.038
PMCID: PMC2846650

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A hybrid cellular automaton model of clonal evolution in cancer: the emergence of the glycolytic phenotype.PMID 18068192Read ↗

An evolutionary hybrid cellular automaton model of solid tumour growth.Semantic proximity Read ↗

Modelling evolutionary cell behaviour using neural networks: application to tumour growth.Semantic proximity Read ↗

Computational analysis of the influence of the microenvironment on carcinogenesis.Semantic proximity Read ↗

Evolution of cell motility in an individual-based model of tumour growth.Semantic proximity Read ↗

Microenvironmental variables must influence intrinsic phenotypic parameters of cancer stem cells to affect tumourigenicity.Semantic proximity Read ↗

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.Semantic proximity Read ↗

A fully continuous individual-based model of tumor cell evolution.Semantic proximity Read ↗

'Go or grow': the key to the emergence of invasion in tumour progression?Semantic proximity Read ↗

Cellular automata coupled with steady-state nutrient solution permit simulation of large-scale growth of tumours.Semantic proximity Read ↗

A Mathematical Dissection of the Adaptation of Cell Populations to Fluctuating Oxygen Levels.Semantic proximity Read ↗

A Mathematical Study of the Influence of Hypoxia and Acidity on the Evolutionary Dynamics of Cancer.Semantic proximity Read ↗

Modelling cell adaptation using internal variables: Accounting for cell plasticity in continuum mathematical biology.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.