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Topological effects of data incompleteness of gene regulatory networks

Submitted by Admin2 on 20/09/2022
Publication type
journalArticle
Autor
Body
The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly.
Año
2012
DOI
https://10.1186/1752-0509-6-110
ISSN
1752-0509
Journal
<_none>BMC Systems Biology