Evidence map›Paper›PMID 33430767›Full record

ArticleBMC bioinformatics2021

Impact of explicit area scaling on kinetic models involving multiple compartments.

Pascal Holzheu, Ruth Großeholz, Ursula Kummer

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Pascal HolzheuDepartment of Modeling of Biological Processes, COS Heidelberg/Bioquant, Im Neuenheimer Feld 267, 69120, Heidelberg, Germany.
Ruth GroßeholzDepartment of Modeling of Biological Processes, COS Heidelberg/Bioquant, Im Neuenheimer Feld 267, 69120, Heidelberg, Germany.
Ursula KummerDepartment of Modeling of Biological Processes, COS Heidelberg/Bioquant, Im Neuenheimer Feld 267, 69120, Heidelberg, Germany. ursula.kummer@bioquant.uni-heidelberg.de.

Funding

Deutsche Forschungsgemeinschaft Open Access PublicationDeutsche Forschungsgemeinschaft SFB 1101
6 · The paper itself

Abstract

backgroundComputational modelling of cell biological processes is a frequently used technique to analyse the underlying mechanisms and to generally understand the behaviour of these processes in the context of a pathway, network or even the whole cell. The most common technique in this context is the usage of ordinary differential equations that describe the kinetics of the relevant processes in mechanistic detail. Here, it is usually assumed that the content of the cell is well-stirred and thus homogeneous - which is of course an over-simplification, but often worked in the past. However, many processes happen at membranes and thus not in 3D, but in 2D. The scaling of the rates of these processes poses a special problem, if volumes of compartments are changed. They will typically scale with an area, but not with the volume of the involved compartment. However, commonly, this is neglected when setting up models and/or volume scaling also sometimes automatically happens when using modelling software in the field.

resultsHere, we investigate generic as well as specific, realistic cases to find out, how strong the impact of the wrong scaling is for the outcome of simulations. We show that the importance of correct area scaling depends on the architecture of the reaction site and its changes upon volume alterations and it is hard to foresee, if it has a significant impact or not just by looking at the original model set-up. Moreover, scaled rates might exhibit more or less control over the behaviour of the system and therefore, accordingly, incorrect scaling will have more or less influence.

conclusionsWorking with multi-compartment reactions requires a careful consideration of the correct scaling of the rates when changing the volumes of the involved compartments. The error following incorrect scaling - often done by scaling with the volume of the respective compartments can lead to significant aberrations of model behaviour.

Indexed as

Models, BiologicalCellsComputer SimulationKineticsSoftwareArea scalingKinetic modelingSystems biology

Identifiers

PMID33430767
PMCPMC7798250

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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.