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微风险实验室:一款用于预测微生物学的在线免费软件。

Microrisk Lab: An Online Freeware for Predictive Microbiology.

机构信息

University of Shanghai for Science and Technology, Shanghai, China.

出版信息

Foodborne Pathog Dis. 2021 Aug;18(8):607-615. doi: 10.1089/fpd.2020.2919. Epub 2021 Jun 30.


DOI:10.1089/fpd.2020.2919
PMID:34191593
Abstract

Microrisk Lab is an R-based online modeling freeware designed to realize parameter estimation and model simulation in predictive microbiology. A total of 36 peer-reviewed models were integrated for parameter estimation (including primary models of bacterial growth/inactivation under static and nonisothermal conditions, secondary models of specific growth rate, and competition models of two-flora growth) and model simulation (including integrated models of deterministic or stochastic bacterial growth/inactivation under static and nonisothermal conditions) in Microrisk Lab. Each modeling section was designed to provide numerical and graphical results with comprehensive statistical indicators depending on the appropriate data set and/or parameter setting. In this study, six case studies were reproduced in Microrisk Lab and compared in parallel with DMFit, GInaFiT, IPMP 2013/GraphPad Prism, Bioinactivation FE, and @Risk, respectively. The estimated and simulated results demonstrated that the performance of Microrisk Lab was statistically equivalent to that of other existing modeling systems. Microrisk Lab allows for a friendly user experience when modeling microbial behaviors owing to its interactive interfaces, high integration, and interconnectivity. Users can freely access this application at https://microrisklab.shinyapps.io/english/ or https://microrisklab.shinyapps.io/chinese/.

摘要

微风险实验室是一个基于 R 的在线建模免费软件,旨在实现预测微生物学中的参数估计和模型模拟。共有 36 个经过同行评审的模型被整合用于参数估计(包括静态和非等温条件下细菌生长/失活动力学的基本模型、比生长率的二次模型以及两种菌群生长的竞争模型)和模型模拟(包括静态和非等温条件下确定性或随机性细菌生长/失活动力学的综合模型)。每个建模部分都旨在根据适当的数据集和/或参数设置提供带有综合统计指标的数值和图形结果。在这项研究中,我们在微风险实验室中重现了六个案例研究,并分别与 DMFit、GInaFiT、IPMP 2013/GraphPad Prism、Bioinactivation FE 和@Risk 进行了并行比较。估计和模拟结果表明,微风险实验室的性能在统计学上与其他现有建模系统相当。由于其交互界面、高度集成和互连接性,微风险实验室在进行微生物行为建模时具有友好的用户体验。用户可以在 https://microrisklab.shinyapps.io/english/ 或 https://microrisklab.shinyapps.io/chinese/ 自由访问此应用程序。

相似文献

[1]
Microrisk Lab: An Online Freeware for Predictive Microbiology.

Foodborne Pathog Dis. 2021-8

[2]
IPMP 2013--a comprehensive data analysis tool for predictive microbiology.

Int J Food Microbiol. 2013-11-23

[3]
Bioinactivation: Software for modelling dynamic microbial inactivation.

Food Res Int. 2017-3

[4]
Bioinactivation FE: A free web application for modelling isothermal and dynamic microbial inactivation.

Food Res Int. 2018-6-25

[5]
IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

Int J Food Microbiol. 2017-12-4

[6]
GInaFiT, a freeware tool to assess non-log-linear microbial survivor curves.

Int J Food Microbiol. 2005-6-25

[7]
Introducing optimal experimental design in predictive modeling: a motivating example.

Int J Food Microbiol. 1999-10-1

[8]
Predictive microbiology models vs. modeling microbial growth within Listeria monocytogenes risk assessment: what parameters matter and why.

Food Microbiol. 2010-6-12

[9]
MONALISA for stochastic simulations of Petri net models of biochemical systems.

BMC Bioinformatics. 2015-7-10

[10]
'MicroHibro': A software tool for predictive microbiology and microbial risk assessment in foods.

Int J Food Microbiol. 2018-10-10

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