Unknown

Dataset Information

Using Multilayer Heterogeneous Networks to Infer Functions of Phosphorylated Sites.


ABSTRACT: Mass spectrometry-based quantitative phosphoproteomics has become an essential approach in the study of cellular processes such as signaling. Commonly used methods to analyze phosphoproteomics datasets depend on generic, gene-centric annotations such as Gene Ontology terms, which do not account for the function of a protein in a particular phosphorylation state. Analysis of phosphoproteomics data is hampered by a lack of phosphorylated site-specific annotations. We propose a method that combines shotgun phosphoproteomics data, protein-protein interactions, and functional annotations into a heterogeneous multilayer network. Phosphorylation sites are associated to potential functions using a random walk on the heterogeneous network (RWHN) algorithm. We validated our approach against a model

SUBMITTER: Watson J 

PROVIDER: S-EPMC8256419 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature