Modelling techniques for biomolecular networks

TL;DR

This paper reviews various network modelling methods in systems biology, emphasizing logical models like Boolean networks, their advantages, conversions, mathematical frameworks, software tools, standards, and the distinction between quantitative and qualitative models.

Contribution

It provides a comprehensive overview of logical network modelling techniques, their mathematical foundations, tools, and standards, highlighting the advantages of Boolean models over mechanistic approaches.

Findings

Boolean networks offer advantages over differential equation models.

Conversion methods connect different model types.

Standards and ontologies support logical systems biology models.

Abstract

First we shortly review the different kinds of network modelling methods for systems biology with an emphasis on the different subtypes of logical models, which we review in more detail. Then we show the advantages of Boolean networks models over more mechanistic modelling types like differential equation techniques. Then follows an overlook about connections between different kinds of models and how they can be converted to each other. We also give a short overview about the mathematical frameworks for modelling of logical networks and list available software packages for logical modelling. Then we give an overview about the available standards and ontologies for storing such logical systems biology models and their results. In the end we give a short review about the difference between quantitative and qualitative models and describe the mathematics that specifically deals with qualitative modelling.