CANTATA—prediction of missing links in Boolean networks using genetic programming

• DOI: 10.1093/bioinformatics/btac623
• Publication Date: 2022-09-10T00:38:12Z
• Authors: Christoph Müssel; Nensi Ikonomi; Silke D Werle; Felix M Weidner; Markus Maucher; Julian D Schwab; Hans A Kestler
• Keywords: Robustness; Gene regulatory network

Abstract Motivation Biological processes are complex systems with distinct behaviour. Despite the growing amount of available data, knowledge is sparse and often insufficient to investigate regulatory behaviour these systems. Moreover, different cellular phenotypes possible under varying conditions. Mathematical models attempt unravel mechanisms by investigating dynamics networks. Therefore, a major challenge combine regulations phenotypical information as well underlying mechanisms. To predict links in models, we established an approach called CANTATA support integration into networks retrieve potential regulations. This achieved optimizing both static dynamic properties Results Initial results show that algorithm predicts missing interactions recapitulating known while preserving original topology robustness model. The resulting allow for hypothesizing about biological impact certain dependencies. Availability implementation Source code application, example files at https://github.com/sysbio-bioinf/Cantata. Supplementary data Bioinformatics online.