Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data)
Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks (GRNs), which have also been widely studied as abstract models of complex systems and have been used to simulate different phenomena. We define the “common sea” (CS) as the set of nodes that take the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/3/311 |
| _version_ | 1797471731226509312 |
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| author | Marco Villani Gianluca D’Addese Stuart A. Kauffman Roberto Serra |
| author_facet | Marco Villani Gianluca D’Addese Stuart A. Kauffman Roberto Serra |
| author_sort | Marco Villani |
| collection | DOAJ |
| description | Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks (GRNs), which have also been widely studied as abstract models of complex systems and have been used to simulate different phenomena. We define the “common sea” (CS) as the set of nodes that take the same value in all the attractors of a given network realization, and the “specific part” (SP) as the set of all the other nodes, and we study their properties in different ensembles, generated with different parameter values. Both the CS and of the SP can be composed of one or more weakly connected components, which are emergent intermediate-level structures. We show that the study of these sets provides very important information about the behavior of the model. The distribution of distances between attractors is also examined. Moreover, we show how the notion of a “common sea” of genes can be used to analyze data from single-cell experiments. |
| first_indexed | 2024-03-09T19:52:22Z |
| format | Article |
| id | doaj.art-a02eda95ff6043e18caef812e1d7fdba |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T19:52:22Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-a02eda95ff6043e18caef812e1d7fdba2023-11-24T01:06:40ZengMDPI AGEntropy1099-43002022-02-0124331110.3390/e24030311Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data)Marco Villani0Gianluca D’Addese1Stuart A. Kauffman2Roberto Serra3Department of Physics, Informatics and Mathematics, Modena and Reggio Emilia University, 41125 Modena, ItalyDepartment of Physics, Informatics and Mathematics, Modena and Reggio Emilia University, 41125 Modena, ItalyInstitute for Systems Biology, Seattle, WA 98109, USADepartment of Physics, Informatics and Mathematics, Modena and Reggio Emilia University, 41125 Modena, ItalyRandom Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks (GRNs), which have also been widely studied as abstract models of complex systems and have been used to simulate different phenomena. We define the “common sea” (CS) as the set of nodes that take the same value in all the attractors of a given network realization, and the “specific part” (SP) as the set of all the other nodes, and we study their properties in different ensembles, generated with different parameter values. Both the CS and of the SP can be composed of one or more weakly connected components, which are emergent intermediate-level structures. We show that the study of these sets provides very important information about the behavior of the model. The distribution of distances between attractors is also examined. Moreover, we show how the notion of a “common sea” of genes can be used to analyze data from single-cell experiments.https://www.mdpi.com/1099-4300/24/3/311Random Boolean Networksgene regulatory networkscritical systemscriticality principleattractorssingle-cell data |
| spellingShingle | Marco Villani Gianluca D’Addese Stuart A. Kauffman Roberto Serra Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) Entropy Random Boolean Networks gene regulatory networks critical systems criticality principle attractors single-cell data |
| title | Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) |
| title_full | Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) |
| title_fullStr | Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) |
| title_full_unstemmed | Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) |
| title_short | Attractor-Specific and Common Expression Values in Random Boolean Network Models (with a Preliminary Look at Single-Cell Data) |
| title_sort | attractor specific and common expression values in random boolean network models with a preliminary look at single cell data |
| topic | Random Boolean Networks gene regulatory networks critical systems criticality principle attractors single-cell data |
| url | https://www.mdpi.com/1099-4300/24/3/311 |
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