Evidence map›Paper›PMID 31455206›Full record

ArticleBMC bioinformatics2019

Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study.

Markos Antonopoulos, Dimitra Dionysiou, Georgios Stamatakos, Nikolaos Uzunoglu

Erratum issuedAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Markos AntonopoulosInstitute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece. markosan@central.ntua.gr.ORCID http://orcid.org/0000-0001-9052-0293
Dimitra DionysiouInstitute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
Georgios StamatakosInstitute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
Nikolaos UzunogluInstitute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.

Funding

Seventh Framework Programme 600841
6 · The paper itself

Abstract

backgroundContemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the means for conducting in silico experiments, which are cheaper and less tedious than real laboratory experiments.

resultsThis paper aims at developing an extensible and computationally efficient framework for in silico modeling of tumor growth in a 3-dimensional, inhomogeneous and time-varying chemical environment. The resulting model consists of a set of mathematically derived and algorithmically defined operators, each one addressing the effects of a particular biological mechanism on the state of the system. These operators may be extended or re-adjusted, in case a different set of starting assumptions or a different simulation scenario needs to be considered.

conclusionIn silico modeling provides an alternative means for testing hypotheses and simulating scenarios for which exact biological knowledge remains elusive. However, finer tuning of pertinent methods presupposes qualitative and quantitative enrichment of available biological evidence. Validation in a strict sense would further require comprehensive, case-specific simulations and detailed comparisons with biomedical observations.

Indexed as

Models, BiologicalModels, TheoreticalAlgorithmsCell ProliferationComputer SimulationDiffusionGlucoseGlycolysisHumansNecrosisNeoplasmsNeovascularization, PathologicOxygenTime FactorsVascular RemodelingGlucoseOxygenCellular diffusionChemical diffusionComputational modelingIn silico modelingTumor growth

Identifiers

PMID31455206
PMCPMC6712764

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.