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- Publisher Website: 10.1016/j.automatica.2021.109630
- Scopus: eid_2-s2.0-85103734043
- WOS: WOS:000663420500009
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Article: Discrimination of Attractors with Noisy Nodes in Boolean Networks
| Title | Discrimination of Attractors with Noisy Nodes in Boolean Networks |
|---|---|
| Authors | |
| Keywords | Observability Boolean networks Attractors Genetic networks Biomarkers |
| Issue Date | 2021 |
| Publisher | Elsevier. The Journal's web site is located at http://www.elsevier.com/locate/automatica |
| Citation | Automatica, 2021, v. 130, p. article no. 109630 How to Cite? |
| Abstract | Observing the internal state of the whole system using a small number of sensor nodes is important in analysis of complex networks. Here, we study the problem of determining the minimum number of sensor nodes to discriminate attractors under the assumption that each attractor has at most noisy nodes. We present exact and approximation algorithms for this minimization problem. The effectiveness of the algorithms is also demonstrated by computational experiments using both synthetic data and realistic biological data. |
| Persistent Identifier | http://hdl.handle.net/10722/300929 |
| ISSN | 2021 Impact Factor: 6.150 2020 SCImago Journal Rankings: 3.132 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Cheng, X | - |
| dc.contributor.author | Ching, WK | - |
| dc.contributor.author | GUO, S | - |
| dc.contributor.author | Akutsu, T | - |
| dc.date.accessioned | 2021-07-06T03:12:11Z | - |
| dc.date.available | 2021-07-06T03:12:11Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.citation | Automatica, 2021, v. 130, p. article no. 109630 | - |
| dc.identifier.issn | 0005-1098 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/300929 | - |
| dc.description.abstract | Observing the internal state of the whole system using a small number of sensor nodes is important in analysis of complex networks. Here, we study the problem of determining the minimum number of sensor nodes to discriminate attractors under the assumption that each attractor has at most noisy nodes. We present exact and approximation algorithms for this minimization problem. The effectiveness of the algorithms is also demonstrated by computational experiments using both synthetic data and realistic biological data. | - |
| dc.language | eng | - |
| dc.publisher | Elsevier. The Journal's web site is located at http://www.elsevier.com/locate/automatica | - |
| dc.relation.ispartof | Automatica | - |
| dc.subject | Observability | - |
| dc.subject | Boolean networks | - |
| dc.subject | Attractors | - |
| dc.subject | Genetic networks | - |
| dc.subject | Biomarkers | - |
| dc.title | Discrimination of Attractors with Noisy Nodes in Boolean Networks | - |
| dc.type | Article | - |
| dc.identifier.email | Ching, WK: wching@hku.hk | - |
| dc.identifier.authority | Ching, WK=rp00679 | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1016/j.automatica.2021.109630 | - |
| dc.identifier.scopus | eid_2-s2.0-85103734043 | - |
| dc.identifier.hkuros | 323251 | - |
| dc.identifier.volume | 130 | - |
| dc.identifier.spage | article no. 109630 | - |
| dc.identifier.epage | article no. 109630 | - |
| dc.identifier.isi | WOS:000663420500009 | - |
| dc.publisher.place | United Kingdom | - |