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Protein complexes detection based on node local properties and gene expression in PPI weighted networks

BACKGROUND: Identifying protein complexes from protein–protein interaction (PPI) networks is a crucial task, and many related algorithms have been developed. Most algorithms usually employ direct neighbors of nodes and ignore resource allocation and second-order neighbors. The effective use of such...

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Detalles Bibliográficos
Autores principales: Yu, Yang, Kong, Dezhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734347/
https://www.ncbi.nlm.nih.gov/pubmed/34991441
http://dx.doi.org/10.1186/s12859-021-04543-4
Descripción
Sumario:BACKGROUND: Identifying protein complexes from protein–protein interaction (PPI) networks is a crucial task, and many related algorithms have been developed. Most algorithms usually employ direct neighbors of nodes and ignore resource allocation and second-order neighbors. The effective use of such information is crucial to protein complex detection. RESULT: Based on this observation, we propose a new way by combining node resource allocation and gene expression information to weight protein network (NRAGE-WPN), in which protein complexes are detected based on core-attachment and second-order neighbors. CONCLUSIONS: Through comparison with eleven methods in Yeast and Human PPI network, the experimental results demonstrate that this algorithm not only performs better than other methods on 75% in terms of f-measure+, but also can achieve an ideal overall performance in terms of a composite score consisting of five performance measures. This identification method is simple and can accurately identify more complexes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04543-4.