A propagation-based seed-centric local community detection for multilayer environment: The case study of colon adenocarcinoma

A propagation-based seed-centric local community detection for multilayer environment: The case study of colon adenocarcinoma

Blog Article

Regardless of all efforts on community discovery algorithms, it is still an open and challenging subject in network science.Recognizing communities in a multilayer network, where there are several layers (types) of connections, is even more complicated.Here, we concentrated on a specific type of communities called seed-centric local communities in the multilayer environment and developed a novel method based Acoustic Bronze on the information cascade concept, called PLCDM.

Our simulations on three datasets (real and artificial) signify that the suggested method outstrips two known earlier seed-centric local methods.Additionally, we compared it with other global multilayer and single-layer methods.Eventually, we applied our method on a biological two-layer network of Colon Adenocarcinoma (COAD), reconstructed from Brogue Lace Up Boots transcriptomic and post-transcriptomic datasets, and assessed the output modules.

The functional enrichment consequences infer that the modules of interest hold biomolecules involved in the pathways associated with the carcinogenesis.