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

An evolutionary hybrid cellular automaton model of solid tumour growth.

Journal of theoretical biology - 21 Jun 2007

Gerlee P, Anderson A R A

Abstract excerpt

We propose a cellular automaton model of solid tumour growth, in which each cell is equipped with a micro-environment response network. This network is modelled using a feed-forward artificial neural network, that takes environmental variables as an input and from these determines the cellular behaviour as the output. The response of the network is determined by connection weights and thresholds in the network,...

Read the complete abstract on PubMed

Topics

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

Share to Apoptosis
Share to Cell Division
Share to Cell Physiological Phenomena

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Chimera

Share to Neoplasms

Share to Neural Networks, Computer

Share to Oxygen

Source

Open in PubMed Open full text

Identifiers

PMID: 17374383
DOI: 10.1016/j.jtbi.2007.01.027
PMCID: PMC2652069

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

An evolutionary hybrid cellular automaton model of solid tumour growth.PMID 17374383Read ↗

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

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

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

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

Evolving homeostatic tissue using genetic algorithms.Semantic proximity Read ↗

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

Spatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment.Semantic proximity Read ↗

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

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

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

Biophysical models of tumour growthSemantic 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.