BioModelKit - An Integrative Framework for Multi-Scale Biomodel-Engineering

J Integr Bioinform. 2018 Sep 6;15(3):20180021. doi: 10.1515/jib-2018-0021.

Abstract

While high-throughput technology, advanced techniques in biochemistry and molecular biology have become increasingly powerful, the coherent interpretation of experimental results in an integrative context is still a challenge. BioModelKit (BMK) approaches this challenge by offering an integrative and versatile framework for biomodel-engineering based on a modular modelling concept with the purpose: (i) to represent knowledge about molecular mechanisms by consistent executable sub-models (modules) given as Petri nets equipped with defined interfaces facilitating their reuse and recombination; (ii) to compose complex and integrative models from an ad hoc chosen set of modules including different omic and abstraction levels with the option to integrate spatial aspects; (iii) to promote the construction of alternative models by either the exchange of competing module versions or the algorithmic mutation of the composed model; and (iv) to offer concepts for (omic) data integration and integration of existing resources, and thus facilitate their reuse. BMK is accessible through a public web interface (www.biomodelkit.org), where users can interact with the modules stored in a database, and make use of the model composition features. BMK facilitates and encourages multi-scale model-driven predictions and hypotheses supporting experimental research in a multilateral exchange.

Keywords: Petri nets; model composition; model database; model mutation; spatiotemporal modelling.

MeSH terms

  • Algorithms*
  • Animals
  • Bioengineering / methods*
  • Databases, Factual*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Models, Biological
  • Software*
  • Systems Biology / methods

Grants and funding

This work has been partly supported by the Germany Federal Ministry of Education and Research, Funder Id: 10.13039/501100002347 (FKZ0315449F, FKZ0316177D).