Maximizing local information transfer in Boolean networks
We study a Boolean network model such that rules governing the time evolution of states are not given a priori but emerge from the maximization process of local information transfer and are stabilized if possible. We mathematically derive the class of rules that can be stabilized. With the presence...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2018-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/aadbc3 |
| _version_ | 1797750606803238912 |
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| author | T Haruna K Nakajima |
| author_facet | T Haruna K Nakajima |
| author_sort | T Haruna |
| collection | DOAJ |
| description | We study a Boolean network model such that rules governing the time evolution of states are not given a priori but emerge from the maximization process of local information transfer and are stabilized if possible. We mathematically derive the class of rules that can be stabilized. With the presence of small noise, those stabilized are such that their output depends on a unique input. We confirm the prediction of the theory by numerical simulation. We argue that the stabilized rules have generic properties of real-world gene regulatory networks, being both critical and highly canalized. |
| first_indexed | 2024-03-12T16:35:17Z |
| format | Article |
| id | doaj.art-3380b581d493475788254bc342c91341 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:35:17Z |
| publishDate | 2018-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-3380b581d493475788254bc342c913412023-08-08T14:53:35ZengIOP PublishingNew Journal of Physics1367-26302018-01-0120808304610.1088/1367-2630/aadbc3Maximizing local information transfer in Boolean networksT Haruna0K Nakajima1https://orcid.org/0000-0001-5589-4054Department of Information and Sciences, Tokyo Woman’s Christian University , 2-6-1 Zempukuji, Suginami-ku, Tokyo 167-8585, JapanGraduate School of Information Science and Technology, The University of Tokyo , Bunkyo-ku, Tokyo 113-8656, Japan; PRESTO, Japan Science and Technology Agency (JST) , 4-1-8 Honcho Kawaguchi, Saitama, JapanWe study a Boolean network model such that rules governing the time evolution of states are not given a priori but emerge from the maximization process of local information transfer and are stabilized if possible. We mathematically derive the class of rules that can be stabilized. With the presence of small noise, those stabilized are such that their output depends on a unique input. We confirm the prediction of the theory by numerical simulation. We argue that the stabilized rules have generic properties of real-world gene regulatory networks, being both critical and highly canalized.https://doi.org/10.1088/1367-2630/aadbc3mutual informationBayesian inferencegene regulatory networkscanalizationcriticality |
| spellingShingle | T Haruna K Nakajima Maximizing local information transfer in Boolean networks New Journal of Physics mutual information Bayesian inference gene regulatory networks canalization criticality |
| title | Maximizing local information transfer in Boolean networks |
| title_full | Maximizing local information transfer in Boolean networks |
| title_fullStr | Maximizing local information transfer in Boolean networks |
| title_full_unstemmed | Maximizing local information transfer in Boolean networks |
| title_short | Maximizing local information transfer in Boolean networks |
| title_sort | maximizing local information transfer in boolean networks |
| topic | mutual information Bayesian inference gene regulatory networks canalization criticality |
| url | https://doi.org/10.1088/1367-2630/aadbc3 |
| work_keys_str_mv | AT tharuna maximizinglocalinformationtransferinbooleannetworks AT knakajima maximizinglocalinformationtransferinbooleannetworks |