Affiliations: [a] Department of Information Technologies, Åbo Akademi University, Finland. [email protected]
| [b] Department of Mathematics and Statistics, University of Turku, Finland. National Institute of Research and Development for Biological Sciences, Romania. [email protected]
Correspondence:
[†]
Address for correspondence: Department of Mathematics and Statistics, University of Turku, Finland
Note: [*] This work was initiated as part of Patric Gustafsson’s master thesis project at Åbo Akademi University (ÅA) in 2019. Patric is no longer affiliated with ÅA.
Abstract: Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous.
