Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7446
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dc.contributor.authorCheng, Lixinen_US
dc.contributor.authorLiu, Pengfeien_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-02T06:24:54Z-
dc.date.available2023-03-02T06:24:54Z-
dc.date.issued2017-
dc.identifier.citationACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics pp. 754-755en_US
dc.identifier.isbn978-145034722-8-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7446-
dc.description.abstractWe propose a novel procedure, Subcellular Module Identification with Localization Expansion (SMILE), to identify super modules that consist of several subcellular modules performing specific biological functions among cell compartments. These super modules identified by SMILE are more functionally diverse and have been verified to be more associated with known protein complexes and biological pathways compared with the modules identified from the global protein interaction networks in both the ComPPI and InWeb_InBioMap protein interaction datasets. Our results reveal that subcellular localization is a principal feature of functional modules and offers important guidance in detecting biologically meaningful results.en_US
dc.language.isoenen_US
dc.titleSMILE: A novel procedure for subcellular module identification with localization expansionen_US
dc.typeConference Paperen_US
dc.relation.conferenceACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informaticsen_US
dc.identifier.doi10.1145/3107411.3110415-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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