PEtab.jl: advancing the efficiency and utility of dynamic modelling.

IF 5.4

Bioinformatics (Oxford, England) Pub Date : 2025-09-01 DOI:10.1093/bioinformatics/btaf497

Sebastian Persson, Fabian Fröhlich, Stephan Grein, Torkel Loman, Damiano Ognissanti, Viktor Hasselgren, Jan Hasenauer, Marija Cvijovic

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Abstract

Summary: Dynamic models represent a powerful tool for studying complex biological processes, ranging from cell signalling to cell differentiation. Building such models often requires computationally demanding modelling workflows, such as model exploration and parameter estimation. We developed two Julia-based tools: SBMLImporter.jl, an SBML importer, and PEtab.jl, an importer for parameter estimation problems in the PEtab format, designed to streamline modelling processes. These tools leverage Julia's high-performance computing capabilities, including symbolic pre-processing and advanced ODE solvers. PEtab.jl aims to be a Julia-accessible toolbox that supports the entire modelling pipeline from parameter estimation to identifiability analysis.

Availability and implementation: SBMLImporter.jl and PEtab.jl are implemented in the Julia programming language. Both packages are available on GitHub (github.com/sebapersson/SBMLImporter.jl and github.com/sebapersson/PEtab.jl) as officially registered Julia packages, installable via the Julia package manager. Each package is continuously tested and supported on Linux, macOS, and Windows.

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PEtab。[1]：提高动态建模的效率和效用。

摘要：动态模型是研究复杂生物过程的有力工具，范围从细胞信号传导到细胞分化。建立这样的模型通常需要计算要求很高的建模工作流，比如模型探索和参数估计。我们开发了两个基于julia的工具：SBMLImporter。jl，一个SBML导入器，以及PEtab。jl，用于PEtab格式的参数估计问题的导入器，旨在简化建模过程。这些工具利用Julia的高性能计算能力，包括符号预处理和高级ODE求解器。PEtab。jl旨在成为一个julia可访问的工具箱，支持从参数估计到可识别性分析的整个建模管道。可用性和实现：SBMLImporter。jl和PEtab。jl是用Julia编程语言实现的。这两个包都可以在GitHub （github.com/sebapersson/SBMLImporter.jl和github.com/sebapersson/PEtab.jl）上作为正式注册的Julia包获得，可以通过Julia包管理器安装。每个包都在Linux、macOS和Windows上持续测试和支持。补充信息：补充数据可在生物信息学在线获取。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bioinformatics (Oxford, England)

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