Evidence map›Paper›PMID 30562900›Full record

ArticleIn silico biology2019

Modeling cell population dynamics.

Daniel A Charlebois, Gábor Balázsi

Abstract read
In one paragraph

Article in In silico biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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  18. Basic Methods of Cell Cycle Analysis.International journal of molecular sciences · 2023
    Review
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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

2 authors.

Daniel A CharleboisThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, NY, USA.
Gábor BalázsiThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, NY, USA.

Funding

Dynamics and evolution of synthetic and natural gene regulatory networksR35GM122561 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI BALAZSI, GABOR · 2017 to 2025
$4.2M
NIGMS NIH HHS R35 GM122561
6 · The paper itself

Abstract

Quantitative modeling is quickly becoming an integral part of biology, due to the ability of mathematical models and computer simulations to generate insights and predict the behavior of living systems. Single-cell models can be incapable or misleading for inferring population dynamics, as they do not consider the interactions between cells via metabolites or physical contact, nor do they consider competition for limited resources such as nutrients or space. Here we examine methods that are commonly used to model and simulate cell populations. First, we cover simple models where analytic solutions are available, and then move on to more complex scenarios where computational methods are required. Overall, we present a summary of mathematical models used to describe cell population dynamics, which may aid future model development and highlights the importance of population modeling in biology.

Indexed as

Cell Physiological PhenomenaModels, BiologicalAlgorithmsCell DifferentiationCell DivisionCell ProliferationMarkov ChainsMonte Carlo Methodcell population dynamicsevolutionMathematical modelingmultiscale simulation algorithms

Identifiers

PMID30562900
PMCPMC6598210

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.