FunNet (1.00-12)

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Integrative Functional Analysis of Transcriptional Networks.

http://corneliu.henegar.info/FunNet.htm
http://www.geneontology.org/GO.tools.microarray.shtml#funnet
http://www.funnet.info
http://www.funnet.ws
http://cran.r-project.org/web/packages/FunNet

FunNet is an integrative tool for analyzing gene co-expression networks built from microarray expression data. The analytic model implemented in this library involves two abstraction layers: transcriptional and functional (biological roles). A functional profiling technique using Gene Ontology & KEGG annotations is applied to extract a list of relevant biological themes from microarray expression profiling data. Afterwards multiple-instance representations are built to relate significant themes to their transcriptional instances (i.e. the two layers of the model). An adapted non-linear dynamical system model is used to quantify the proximity of relevant genomic themes based on the similarity of the expression profiles of their gene instances. Eventually an unsupervised multiple-instance clustering procedure, relying on the two abstraction layers, is used to identify the structure of the co-expression network composed from modules of functionally related transcripts. Functional and transcriptional maps of the co-expression network are provided separately together with detailed information on the network centrality of related transcripts and genomic themes.

Maintainer: Corneliu Henegar
Author(s): Corneliu Henegar <corneliu@henegar.info>

License: GPL (>= 2)

Uses: ade4, Cairo, cluster, Hmisc, nlme, sna

Released over 8 years ago.


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