Robust signalling entropy estimation for biological process characterisation
Here, we investigate how the topology of distinct protein interaction networks can alter the entropy calculation. We examine the entropy derived from different protein interaction networks. Additionally, we systematically evaluate different correction strategies, outlining their benefits and drawbacks along with identifying the most effective approaches for specific types of data and biological scenarios. This protocol outlines how to optimize the reliability of entropy calculations and ultimately leads to a deeper comprehension of biological processes and disease mechanisms.
Authors
- Hans A. Kestler (ORCID: https://orcid.org/0000-0002-4759-5254)
- Johann M. Kraus (ORCID: https://orcid.org/0000-0002-9534-6295)
- Nensi Ikonomi (ORCID: https://orcid.org/0000-0003-0780-5832)
- Ana Stolnicu (ORCID: https://orcid.org/0000-0003-3936-5851)
- Peter Bellmann (ORCID: https://orcid.org/0000-0003-0182-4469)
Institutions
- Universität Ulm (DE)
Publication Details
- Journal
- Briefings in Bioinformatics
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1093/bib/bbaf269
- Primary Topic
- Gene Regulatory Network Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung