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ppiPre (version 1.9)

Predict Protein-Protein Interactions Based on Functional and Topological Similarities

Description

Computing similarities between proteins based on their GO annotation, KEGG annotation and PPI network topology. It integrates seven features (TCSS, IntelliGO, Wang, KEGG, Jaccard, RA and AA) to predict PPIs using an SVM classifier. Some internal functions to calculate GO semantic similarities are re-used from R package GOSemSim authored by Guangchuang Yu.

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Version

Install

install.packages('ppiPre')

Monthly Downloads

3

Version

1.9

License

GPL-2

Maintainer

Yue Deng

Last Published

July 28th, 2015

Functions in ppiPre (1.9)

SVMTrain

Using Golden Standard Data Sets to Train an SVM Classifier
ComputeAllEvidences

Compute the Biological and Topological Similarities Between Protein Pairs
AASim

Compute Adamic-Adar Index Between Two Nodes in PPI Network
TopologicSims

Compute topological similarities from user input file
GOKEGGSims

GO- and KEGG- based Similarities Between two Genes
GOKEGGSimsFromFile

GO- and KEGG- based Similarities Between two Genes
ppiPre-package

Predicting protein-protein interactions
ppiPre-internal

Internal ppiPre objects
SVMPredict

Predict false interactions using a training set
TCSSGeneSim

Topological Clustering Semantic Similarity(TCSS) Between two Genes
JaccardSim

Compute Jaccard Index Between Two Nodes in PPI Network
IntelliGOGeneSim

IntelliGO Semantic Similarity Between two Genes
FNPre

Predict false negative interactions based on topological similarities
RASim

Compute Resource Allocation Index Between Two Nodes in PPI Network
KEGGSim

KEGG Semantic Similarity Between two Genes