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Network Ontology Analysis

Network Ontology Analysis (NOA) (abbreviated to NOA) is a freely available collection of Gene Ontology tools aiming to analyze functions of gene network instead of gene list. Network rewiring facilitates the function changes between conditions even with the same gene list. Therefore, it is necessary to annotate the specific function of networks by considering the fundamental roles of interactions from the viewpoint of systems biology. NOA is such a novel functional enrichment analysis method capable to handle both dynamic and static networks. The application of NOA in biological networks shows that NOA can not only capture changing functions in rewiring networks but also find more relevant and specific functions in traditional static networks. Platform: Online tool

URL: http://app.aporc.org/NOA/

Resource ID: nlx_149105     Resource Type: Resource     Version: Latest Version

Keywords

gene, ontology, ontology or annotation browser, statistical analysis, term enrichment, browser

Funding Information

National Natural Science Foundation of China, Chinese Academy of Sciences; Beijing; China, NSF Shanghai, 60873205, 10801131, 60970091, kjcs-yw-s7, 2009CSP002, KSCX2-EW-R-01, 61072149, 91029301, 11ZR1443100, 60873205

Additional Resource Types

Data Analysis Service

Availability

Open unspecified license - Free for academic use

Related To

GO

Abbreviation

NOA

Parent Organization

Synonyms

Network Ontology Analysis (NOA)

Comment

GO data updates: no fixed update schedule

Listed By

Gene Ontology Tools

Supercategory

Resource

Original Submitter

Anonymous

Version Status

Curated

Submitted On

12:00am June 28, 2012

Originated From

SciCrunch

Changes from Previous Version

    No Changes

    Version 4

    Created 1 week ago by Christie Wang

    Version 3

    Created 2 weeks ago by Christie Wang

    Version 2

    Created 2 weeks ago by Christie Wang

    Version 1

    Created 3 years ago by Anonymous

    NOA: a novel Network Ontology Analysis method.

    • Wang J
    • Nucleic Acids Res.
    • 2011 25

    Gene ontology analysis has become a popular and important tool in bioinformatics study, and current ontology analyses are mainly conducted in individual gene or a gene list. However, recent molecular network analysis reveals that the same list of genes with different interactions may perform different functions. Therefore, it is necessary to consider molecular interactions to correctly and specifically annotate biological networks. Here, we propose a novel Network Ontology Analysis (NOA) method to perform gene ontology enrichment analysis on biological networks. Specifically, NOA first defines link ontology that assigns functions to interactions based on the known annotations of joint genes via optimizing two novel indexes 'Coverage' and 'Diversity'. Then, NOA generates two alternative reference sets to statistically rank the enriched functional terms for a given biological network. We compare NOA with traditional enrichment analysis methods in several biological networks, and find that: (i) NOA can capture the change of functions not only in dynamic transcription regulatory networks but also in rewiring protein interaction networks while the traditional methods cannot and (ii) NOA can find more relevant and specific functions than traditional methods in different types of static networks. Furthermore, a freely accessible web server for NOA has been developed at http://www.aporc.org/noa/.