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Conference Paper: Predicting metabolic pathways from metabolic networks with limited biological knowledge

TitlePredicting metabolic pathways from metabolic networks with limited biological knowledge
Authors
KeywordsBuilding block
Conseved metabolic pathways
Metabolic network
Issue Date2010
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001585
Citation
The 2nd International Workshop on Graph Theoretic Analysis of Biological Networks (IWBNA 2010) in conjunction with IEEE International Conference on Bioinformatics & Biomedicine Workshops (BIBMW 2010), Hong Kong, 18-21 December 2010. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010, p. 1-7 How to Cite?
AbstractUnderstanding the metabolism of new species (e.g. endophytic fungi that produce fuel) have tremendous impact on human lives. Based on predicted proteins and existing reaction databases, one can construct the metabolic network for the species. Next is to identify critical metabolic pathways from the network. Existing computational techniques identify conserved pathways based on multiple networks of related species, but have the following drawbacks. Some do not rely on additional information, so only locate short (of length at most 5), but not necessarily interesting, conserved paths. The others require extensive information (the complete pathway on one species). In reality, researchers usually know only partial information of a metabolic pathway and may not have a conserved pathway in a related species. The Conserved Metabolic Pathway (CMP) problem is to find conserved pathways from the networks with partial information on the initial substrates and final products of the target pathways. Experimental results show that our algorithm CMPFinder can predict useful metabolic pathways with acceptable accuracy. ©2010 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/139984
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorLeung, SYen_HK
dc.contributor.authorLeung, HCMen_HK
dc.contributor.authorXiang, CLen_HK
dc.contributor.authorYiu, SMen_HK
dc.contributor.authorChin, FYLen_HK
dc.date.accessioned2011-09-23T06:04:25Z-
dc.date.available2011-09-23T06:04:25Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 2nd International Workshop on Graph Theoretic Analysis of Biological Networks (IWBNA 2010) in conjunction with IEEE International Conference on Bioinformatics & Biomedicine Workshops (BIBMW 2010), Hong Kong, 18-21 December 2010. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010, p. 1-7en_HK
dc.identifier.isbn978-1-4244-8302-0-
dc.identifier.urihttp://hdl.handle.net/10722/139984-
dc.description.abstractUnderstanding the metabolism of new species (e.g. endophytic fungi that produce fuel) have tremendous impact on human lives. Based on predicted proteins and existing reaction databases, one can construct the metabolic network for the species. Next is to identify critical metabolic pathways from the network. Existing computational techniques identify conserved pathways based on multiple networks of related species, but have the following drawbacks. Some do not rely on additional information, so only locate short (of length at most 5), but not necessarily interesting, conserved paths. The others require extensive information (the complete pathway on one species). In reality, researchers usually know only partial information of a metabolic pathway and may not have a conserved pathway in a related species. The Conserved Metabolic Pathway (CMP) problem is to find conserved pathways from the networks with partial information on the initial substrates and final products of the target pathways. Experimental results show that our algorithm CMPFinder can predict useful metabolic pathways with acceptable accuracy. ©2010 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001585-
dc.relation.ispartof2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2010en_HK
dc.rightsProceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops. Copyright © IEEE.-
dc.rights©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBuilding blocken_HK
dc.subjectConseved metabolic pathwaysen_HK
dc.subjectMetabolic networken_HK
dc.titlePredicting metabolic pathways from metabolic networks with limited biological knowledgeen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLeung, HCM:cmleung2@cs.hku.hken_HK
dc.identifier.emailYiu, SM:smyiu@cs.hku.hken_HK
dc.identifier.emailChin, FYL:chin@cs.hku.hken_HK
dc.identifier.authorityLeung, HCM=rp00144en_HK
dc.identifier.authorityYiu, SM=rp00207en_HK
dc.identifier.authorityChin, FYL=rp00105en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/BIBMW.2010.5703765en_HK
dc.identifier.scopuseid_2-s2.0-79952012345en_HK
dc.identifier.hkuros192244en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79952012345&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage7en_HK
dc.identifier.epage12en_HK
dc.publisher.placeUnited States-
dc.description.otherThe 2nd International Workshop on Graph Theoretic Analysis of Biological Networks (IWBNA 2010) in conjunction with IEEE International Conference on Bioinformatics & Biomedicine Workshops (BIBMW 2010), Hong Kong, 18-21 December 2010. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010, p. 1-7-
dc.identifier.scopusauthoridLeung, SY=36995731700en_HK
dc.identifier.scopusauthoridLeung, HCM=35233742700en_HK
dc.identifier.scopusauthoridXiang, CL=36996159200en_HK
dc.identifier.scopusauthoridYiu, SM=7003282240en_HK
dc.identifier.scopusauthoridChin, FYL=7005101915en_HK

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