Cheng, LixinLixinChengLiu, PengfeiPengfeiLiuProf. LEUNG Kwong Sak2023-02-222023-02-222018IET Systems Biology ,2018, vol. 12(2), pp. 55-611751-88491751-8857http://hdl.handle.net/20.500.11861/7425Open accessComputational clustering methods help identify functional modules in protein–protein interaction (PPI) network, in which proteins participate in the same biological pathways or specific functions. Subcellular localisation is crucial for proteins to implement biological functions and each compartment accommodates specific portions of the protein interaction structure. However, the importance of protein subcellular localisation is often neglected in the studies of module identification. In this study, the authors propose a novel procedure, subcellular module identification with localisation 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 PPI networks in both the compartmentalised PPI and InWeb_InBioMap datasets. The authors’ results reveal that subcellular localisation is a principal feature of functional modules and offers important guidance in detecting biologically meaningful results.enCellular BiophysicsProteinsMolecular BiophysicsSubcellular Module IdentificationLocalisation ExpansionComputational Clustering methodsProtein-Protein Interaction networkBiological FunctionsProtein Interaction StructureProtein Subcellular LocalisationSubcellular ModulesInWeb-InBioMap DatasetsSubcellular LocalisationPeer Reviewed Journal Article10.1049/iet-syb.2017.0085