R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 3 of 3 found.
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BUS : Gene network reconstruction

Package: BUS
Type: Package
Title: Gene network reconstruction
Depends: R (>= 2.3.0), minet
Imports: stats, infotheo
Version: 1.28.0
Date: 2010-04-19
Author: Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini
Maintainer: Yuanhua Liu <liuyuanhua@picb.ac.cn>
Description: This package can be used to compute associations among genes (gene-networks) or between genes and some external traits (i.e. clinical).
License: GPL-3
biocViews: Preprocessing
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2016-05-04 03:15:04 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Preprocessing
● 0 images, 7 functions, 3 datasets
● Reverse Depends: 0

netresponse : Functional Network Analysis

Package: netresponse
Type: Package
Title: Functional Network Analysis
Version: 1.32.2
Date: 2016-04-05
Author: Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen
Maintainer: Leo Lahti <leo.lahti@iki.fi>
Description: Algorithms for functional network analysis. Includes an
implementation of a variational Dirichlet process Gaussian
mixture model for nonparametric mixture modeling.
License: GPL (>=2)
Depends: R (>= 2.15.1), Rgraphviz, methods, minet, mclust, reshape2
Imports: dmt, ggplot2, graph, igraph, parallel, plyr, qvalue,
RColorBrewer
URL: https://github.com/antagomir/netresponse
BugReports: https://github.com/antagomir/netresponse/issues
biocViews: CellBiology, Clustering, GeneExpression, Genetics, Network,
GraphAndNetwork, DifferentialExpression, Microarray,
Transcription
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-05-16 02:34:25 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CellBiology, Clustering, DifferentialExpression, GeneExpression, Genetics, GraphAndNetwork, Microarray, Network, Transcription
● 1 images, 73 functions, 2 datasets
● Reverse Depends: 0

geNetClassifier : Classify diseases and build associated gene networks using gene expression profiles

Package: geNetClassifier
Type: Package
Title: Classify diseases and build associated gene networks using gene
expression profiles
Version: 1.12.0
Date: 2015-05-05
Author: Sara Aibar, Celia Fontanillo and Javier De Las Rivas.
Bioinformatics and Functional Genomics Group. Cancer Research
Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain.
Maintainer: Sara Aibar <saibar@usal.es>
Depends: R (>= 2.10.1), Biobase (>= 2.5.5), EBarrays, minet, methods
Imports: e1071, graphics
Suggests: leukemiasEset, RUnit, BiocGenerics
Enhances: RColorBrewer, igraph, infotheo
Description: Comprehensive package to automatically train and validate a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier.
License: GPL (>= 2)
ZipData: no
URL: http://www.cicancer.org
LazyLoad: yes
Collate: class.GenesRanking.R class.GenesNetwork.R
class.GeneralizationError.R class.GeNetClassifierReturn.R
functions.private.R functions.public.R function.main.R
biocViews: Classification, DifferentialExpression, Microarray
NeedsCompilation: no
Packaged: 2016-05-04 04:54:56 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Classification, DifferentialExpression, Microarray
● 14 images, 33 functions, 0 datasets
● Reverse Depends: 0