ppiPre v1.7

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by Yue Deng

Predict Protein-Protein Interactions Based on Functional and Topological Similarities

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 are derived from R package GOSemSim authored by Guangchuang Yu.

Functions in ppiPre

Name Description
ComputeAllEvidences Compute the Biological and Topological Similarities Between Protein Pairs
IntelliGOGeneSim IntelliGO Semantic Similarity Between two Genes
ppiPre-internal Internal ppiPre objects
TCSSGeneSim Topological Clustering Semantic Similarity(TCSS) Between two Genes
SVMPredict Predict false interactions using a training set
TopologicSims Compute topological similarities from user input file
GOKEGGSimsFromFile GO- and KEGG- based Similarities Between two Genes
RASim Compute Resource Allocation Index Between Two Nodes in PPI Network
ppiPre-package Predicting protein-protein interactions
JaccardSim Compute Jaccard Index Between Two Nodes in PPI Network
FNPre Predict false negative interactions based on topological similarities
SVMTrain Using Golden Standard Data Sets to Train an SVM Classifier
AASim Compute Adamic-Adar Index Between Two Nodes in PPI Network
GOKEGGSims GO- and KEGG- based Similarities Between two Genes
KEGGSim KEGG Semantic Similarity Between two Genes
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