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一种用于检测和传达描述生物系统的计算模型差异的算法。

An algorithm to detect and communicate the differences in computational models describing biological systems.

作者信息

Scharm Martin, Wolkenhauer Olaf, Waltemath Dagmar

机构信息

Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany and.

Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany and Stellenbosch Institute for Advanced Study, Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa.

出版信息

Bioinformatics. 2016 Feb 15;32(4):563-70. doi: 10.1093/bioinformatics/btv484. Epub 2015 Oct 21.

Abstract

MOTIVATION

Repositories support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available in repositories, such as the BioModels database or the Physiome Model Repository, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection not only allows users to study the history of models but also helps in the detection of errors and inconsistencies. Existing repositories lack algorithms to track a model's development over time.

RESULTS

Focusing on SBML and CellML, we present an algorithm to accurately detect and describe differences between coexisting versions of a model with respect to (i) the models' encoding, (ii) the structure of biological networks and (iii) mathematical expressions. This algorithm is implemented in a comprehensive and open source library called BiVeS. BiVeS helps to identify and characterize changes in computational models and thereby contributes to the documentation of a model's history. Our work facilitates the reuse and extension of existing models and supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance.

AVAILABILITY AND IMPLEMENTATION

The workflow described in this article is implemented in BiVeS. BiVeS is freely available as source code and binary from sems.uni-rostock.de. The web interface BudHat demonstrates the capabilities of BiVeS at budhat.sems.uni-rostock.de.

摘要

动机

模型库支持模型的重用,并确保与这些模型相关的出版物中结果的透明度。在诸如生物模型数据库或生理组模型库等模型库中,有成千上万的模型,因此一个跟踪模型及其版本之间差异的框架对于比较和组合模型至关重要。差异检测不仅允许用户研究模型的历史,还有助于检测错误和不一致之处。现有的模型库缺乏跟踪模型随时间发展的算法。

结果

我们专注于SBML和CellML,提出了一种算法,用于准确检测和描述模型共存版本之间在以下方面的差异:(i)模型编码;(ii)生物网络结构;(iii)数学表达式。该算法在一个名为BiVeS的全面开源库中实现。BiVeS有助于识别和描述计算模型中的变化,从而有助于记录模型的历史。我们的工作促进了现有模型的重用和扩展,并支持协作建模。最后,它有助于提高建模结果的可重复性,并应对模型溯源方面的挑战。

可用性和实现

本文中描述的工作流程在BiVeS中实现。BiVeS可从sems.uni - rostock.de免费获取源代码和二进制文件。网络界面BudHat在budhat.sems.uni - rostock.de展示了BiVeS的功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5dd1/4743622/1756e98e4323/btv484f1p.jpg

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