Evidence map›Paper›PMID 28754122›Full record

ArticleBMC systems biology2017

Snoopy's hybrid simulator: a tool to construct and simulate hybrid biological models.

Mostafa Herajy, Fei Liu, Christian Rohr, Monika Heiner

Abstract read
In one paragraph

Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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  4. Formal verification confirms the role of p53 protein in cell fate decision mechanism.Theory in biosciences = Theorie in den Biowissenschaften · 2023
    Article
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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

4 authors.

Mostafa HerajyDepartment of Mathematics and Computer Science, Faculty of Science, Port Said University, Port Said, 42521, Egypt.
Fei LiuSchool of Software Engineering, South China University of Technology, Guangzhou, 510006, People's Republic of China. feiliu@scut.edu.cn.
Christian RohrComputer Science Institute, Brandenburg University of Technology, Cottbus, 10 13 44, Germany.
Monika HeinerComputer Science Institute, Brandenburg University of Technology, Cottbus, 10 13 44, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHybrid simulation of (computational) biochemical reaction networks, which combines stochastic and deterministic dynamics, is an important direction to tackle future challenges due to complex and multi-scale models. Inherently hybrid computational models of biochemical networks entail two time scales: fast and slow. Therefore, it is intricate to efficiently and accurately analyse them using only either deterministic or stochastic simulation. However, there are only a few software tools that support such an approach. These tools are often limited with respect to the number as well as the functionalities of the provided hybrid simulation algorithms.

resultsWe present Snoopy's hybrid simulator, an efficient hybrid simulation software which builds on Snoopy, a tool to construct and simulate Petri nets. Snoopy's hybrid simulator provides a wide range of state-of-the-art hybrid simulation algorithms. Using this tool, a computational model of biochemical networks can be constructed using a (coloured) hybrid Petri net's graphical notations, or imported from other compatible formats (e.g. SBML), and afterwards executed via dynamic or static hybrid simulation.

conclusionSnoopy's hybrid simulator is a platform-independent tool providing an accurate and efficient simulation of hybrid (biological) models. It can be downloaded free of charge as part of Snoopy from http://www-dssz.informatik.tu-cottbus.de/DSSZ/Software/Snoopy .

Indexed as

Models, BiologicalAlgorithmsSoftwareStochastic ProcessesHybrid biological modelsHybrid Petri netsHybrid simulationSnoopy

Identifiers

PMID28754122
PMCPMC5534078

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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.