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- Publisher Website: 10.1109/TITB.2008.2007649
- Scopus: eid_2-s2.0-63349107248
- PMID: 19272861
- WOS: WOS:000264059200006
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Article: Mining, modeling, and evaluation of subnetworks from large biomolecular networks and its comparison study
Title | Mining, modeling, and evaluation of subnetworks from large biomolecular networks and its comparison study |
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Authors | |
Keywords | Probabilistic Boolean network (PBN) model Biomolecular network analysis State-space model subnetwork mining Fuzzy modeling |
Issue Date | 2009 |
Citation | IEEE Transactions on Information Technology in Biomedicine, 2009, v. 13, n. 2, p. 184-194 How to Cite? |
Abstract | In this paper, we present a novel method to mine, model, and evaluate a regulatory system executing cellular functions that can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to such a biomolecular network to obtain various subnetworks. Second, computational models are generated for the subnetworks and simulated to predict their behavior in the cellular context. We discuss and evaluate some of the advanced computational modeling approaches, in particular, state-space modeling, probabilistic Boolean network modeling, and fuzzy logic modeling. The modeling and simulation results represent hypotheses that are tested against high-throughput biological datasets (microarrays and/or genetic screens) under normal and perturbation conditions. Experimental results on time-series gene expression data for the human cell cycle indicate that our approach is promising for subnetwork mining and simulation from large biomolecular networks. © 2009 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/276662 |
ISSN | 2014 Impact Factor: 2.493 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Hu, Xiaohua | - |
dc.contributor.author | Ng, Michael | - |
dc.contributor.author | Wu, Fang Xiang | - |
dc.contributor.author | Sokhansanj, Bahrad A. | - |
dc.date.accessioned | 2019-09-18T08:34:17Z | - |
dc.date.available | 2019-09-18T08:34:17Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | IEEE Transactions on Information Technology in Biomedicine, 2009, v. 13, n. 2, p. 184-194 | - |
dc.identifier.issn | 1089-7771 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276662 | - |
dc.description.abstract | In this paper, we present a novel method to mine, model, and evaluate a regulatory system executing cellular functions that can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to such a biomolecular network to obtain various subnetworks. Second, computational models are generated for the subnetworks and simulated to predict their behavior in the cellular context. We discuss and evaluate some of the advanced computational modeling approaches, in particular, state-space modeling, probabilistic Boolean network modeling, and fuzzy logic modeling. The modeling and simulation results represent hypotheses that are tested against high-throughput biological datasets (microarrays and/or genetic screens) under normal and perturbation conditions. Experimental results on time-series gene expression data for the human cell cycle indicate that our approach is promising for subnetwork mining and simulation from large biomolecular networks. © 2009 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Information Technology in Biomedicine | - |
dc.subject | Probabilistic Boolean network (PBN) model | - |
dc.subject | Biomolecular network analysis | - |
dc.subject | State-space model subnetwork mining | - |
dc.subject | Fuzzy modeling | - |
dc.title | Mining, modeling, and evaluation of subnetworks from large biomolecular networks and its comparison study | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TITB.2008.2007649 | - |
dc.identifier.pmid | 19272861 | - |
dc.identifier.scopus | eid_2-s2.0-63349107248 | - |
dc.identifier.volume | 13 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 184 | - |
dc.identifier.epage | 194 | - |
dc.identifier.isi | WOS:000264059200006 | - |
dc.identifier.issnl | 1089-7771 | - |