Jump to main content
Jump to site search
PLANNED MAINTENANCE Close the message box

Scheduled maintenance work on Wednesday 27th March 2019 from 11:00 AM to 1:00 PM (GMT).

During this time our website performance may be temporarily affected. We apologise for any inconvenience this might cause and thank you for your patience.

Issue 4, 2016
Previous Article Next Article

Network stratification analysis for identifying function-specific network layers

Author affiliations


A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (NetSA), to stratify the whole biological network into various function-specific network layers corresponding to particular functions (e.g. KEGG pathways), which transform the network analysis from the gene level to the functional level by integrating expression data, the gene/protein network and gene ontology information altogether. The application of NetSA in yeast and its comparison with a traditional network-partition both suggest that NetSA can more effectively reveal functional implications of network rewiring and extract significant phenotype-related biological processes. Furthermore, for time-series or stage-wise data, the function-specific network layer obtained by NetSA is also shown to be able to characterize the disease progression in a dynamic manner. In particular, when applying NetSA to hepatocellular carcinoma and type 1 diabetes, we can derive functional spectra regarding the progression of the disease, and capture active biological functions (i.e. active pathways) in different disease stages. The additional comparison between NetSA and SPIA illustrates again that NetSA could discover more complete biological functions during disease progression. Overall, NetSA provides a general framework to stratify a network into various layers of function-specific sub-networks, which can not only analyze a biological network on the functional level but also investigate gene rewiring patterns in biological processes.

Graphical abstract: Network stratification analysis for identifying function-specific network layers

Back to tab navigation

Supplementary files

Publication details

The article was received on 14 Nov 2015, accepted on 06 Feb 2016 and first published on 08 Feb 2016

Article type: Paper
DOI: 10.1039/C5MB00782H
Citation: Mol. BioSyst., 2016,12, 1232-1240

  •   Request permissions

    Network stratification analysis for identifying function-specific network layers

    C. Zhang, J. Wang, C. Zhang, J. Liu, D. Xu and L. Chen, Mol. BioSyst., 2016, 12, 1232
    DOI: 10.1039/C5MB00782H

Search articles by author