Functional module search in protein networks based on semantic similarity improves the analysis of proteomics data.

ABSTRACT: The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules w

SUBMITTER: Boyanova D 

PROVIDER: S-EPMC4083122 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature