EasyModel: user-friendly tool for building and analysis of simple mathematical models in systems biology

Summary EasyModel is a new user-friendly web application that contains ready-for-simulation versions of the BioModels Database, and allows for the intuitive creation of new models. Its main target audience is the experimental biologist and students of bioinformatics or systems biology without programming skills. Expert users can also benefit from it by implementing basic models quickly and downloading the code for further tailoring. Availability and implementation Freely available on the web at https://easymodel.udl.cat. Implementation is described in its own section.

Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit

The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchiveToolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.

Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit

The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchiveToolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.

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

Repositories, such as the BioModels Database and the Physiome Model Repository support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection allows users to study the history of models but also helps in the detection of errors and inconsistencies. However, current repositories lack suitable methods to track a model’s development over time. Consequently, researchers have problems to grasp the differences between models and their versions. Focusing on SBML and CellML, we developed an algorithm to accurately detect and describe differences between versions of a model with respect to (i) the models’ encoding, (ii) the structure of biological networks, and (iii) mathematical expressions. Our method is implemented in a comprehensive and open library called BiVeS. Our work facilitates the reuse and extension of existing models. It also supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance. Our algorithm is the first tailor-made detector of differences between versions of computational models in standard formats.

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

Repositories, such as the BioModels Database and the Physiome Model Repository support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection allows users to study the history of models but also helps in the detection of errors and inconsistencies. However, current repositories lack suitable methods to track a model’s development over time. Consequently, researchers have problems to grasp the differences between models and their versions. Focusing on SBML and CellML, we developed an algorithm to accurately detect and describe differences between versions of a model with respect to (i) the models’ encoding, (ii) the structure of biological networks, and (iii) mathematical expressions. Our method is implemented in a comprehensive and open library called BiVeS. Our work facilitates the reuse and extension of existing models. It also supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance. Our algorithm is the first tailor-made detector of differences between versions of computational models in standard formats.