ppiPre: 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 to calculate GO semantic similarities are re-used from R package GOSemSim authored by Guangchuang Yu.

Version: 1.9
Depends: R (≥ 3.1.0)
Imports: AnnotationDbi, igraph, e1071, GOSemSim, GO.db, stats, utils
Enhances: KEGG.db, org.Hs.eg.db, org.Sc.sgd.db, org.Ag.eg.db, org.Pt.eg.db, org.Rn.eg.db, org.Ss.eg.db, org.At.tair.db, org.Bt.eg.db, org.Ce.eg.db, org.Cf.eg.db, org.Dm.eg.db, org.Dr.eg.db, org.EcK12.eg.db, org.EcSakai.eg.db, org.Gg.eg.db, org.Mm.eg.db, org.Mmu.eg.db, org.Pf.plasmo.db, org.Xl.eg.db
Published: 2015-07-28
Author: Yue Deng, Rongjie Shao, Gang Wang and Yuanjun Sun
Maintainer: Yue Deng <anfdeng at 163.com>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: ppiPre results


Reference manual: ppiPre.pdf
Package source: ppiPre_1.9.tar.gz
Windows binaries: r-devel: ppiPre_1.9.zip, r-release: ppiPre_1.9.zip, r-oldrel: ppiPre_1.9.zip
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: ppiPre_1.9.tgz
Old sources: ppiPre archive


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