Package: FunNet
Version: 1.00-8
Date: 2010-02-02
Title: Integrative Functional Analysis of Transcriptional Networks
Author: Corneliu Henegar <corneliu@henegar.info>
Maintainer: Corneliu Henegar <corneliu@henegar.info>
Depends: R (>= 2.6.0), ade4, cluster, Hmisc, nlme, sna, Cairo
Description: 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.
License: GPL (>= 2)
URL: http://corneliu.henegar.info/FunNet.htm,
http://www.geneontology.org/GO.tools.microarray.shtml#funnet,
http://www.funnet.info, http://www.funnet.ws
Packaged: 2010-02-02 20:04:28 UTC; chenegar
Repository: CRAN
Date/Publication: 2010-02-03 10:09:01

Package: FunNet
Version: 1.00-9
Date: 2010-06-27
Title: Integrative Functional Analysis of Transcriptional Networks
Author: Corneliu Henegar <corneliu@henegar.info>
Maintainer: Corneliu Henegar <corneliu@henegar.info>
Depends: R (>= 2.6.0), ade4, cluster, Hmisc, nlme, sna, Cairo
Description: 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.
License: GPL (>= 2)
URL: http://corneliu.henegar.info/FunNet.htm,
http://www.geneontology.org/GO.tools.microarray.shtml#funnet,
http://www.funnet.info, http://www.funnet.ws
Packaged: 2010-06-27 06:06:38 UTC; CH
Repository: CRAN
Date/Publication: 2010-06-27 19:00:20