Design patterns for the construction of computational biological models

Author:

Herajy Mostafa1,Liu Fei2,Heiner Monika3

Affiliation:

1. Department of Mathematics and Computer Science, Faculty of Science, Port Said University , 42521 Port Said , Egypt

2. School of Software Engineering, South China University of Technology , 510006 Guangzhou , China

3. Computer Science Institute, Brandenburg University of Technology , 03013 Cottbus , Germany

Abstract

Abstract Computational biological models have proven to be an invaluable tool for understanding and predicting the behaviour of many biological systems. While it may not be too challenging for experienced researchers to construct such models from scratch, it is not a straightforward task for early stage researchers. Design patterns are well-known techniques widely applied in software engineering as they provide a set of typical solutions to common problems in software design. In this paper, we collect and discuss common patterns that are usually used during the construction and execution of computational biological models. We adopt Petri nets as a modelling language to provide a visual illustration of each pattern; however, the ideas presented in this paper can also be implemented using other modelling formalisms. We provide two case studies for illustration purposes and show how these models can be built up from the presented smaller modules. We hope that the ideas discussed in this paper will help many researchers in building their own future models.

Publisher

Oxford University Press (OUP)

Reference52 articles.

1. Fighting fire with fire: deploying complexity in computational modeling to effectively characterize complex biological systems;Prybutok;Curr Opin Biotechnol,2022

2. Computational systems biology;Kitano;Nature,2002

3. Mini-batch optimization enables training of ode models on large-scale datasets;Stapor;Nat Commun,2022

4. Efficient parameter estimation enables the prediction of drug response using a mechanistic pan-cancer pathway model;Fröhlich;Cell Syst,2018

5. Modeling the temporal dynamics of master regulators and CtrA proteolysis in Caulobacter crescentus cell cycle;Chunrui;PLoS Comput Biol,2022

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