Package: PPInfer 1.33.0
PPInfer: Inferring functionally related proteins using protein interaction networks
Interactions between proteins occur in many, if not most, biological processes. Most proteins perform their functions in networks associated with other proteins and other biomolecules. This fact has motivated the development of a variety of experimental methods for the identification of protein interactions. This variety has in turn ushered in the development of numerous different computational approaches for modeling and predicting protein interactions. Sometimes an experiment is aimed at identifying proteins closely related to some interesting proteins. A network based statistical learning method is used to infer the putative functions of proteins from the known functions of its neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions.
Authors:
PPInfer_1.33.0.tar.gz
PPInfer_1.33.0.zip(r-4.5)PPInfer_1.33.0.zip(r-4.4)PPInfer_1.33.0.zip(r-4.3)
PPInfer_1.33.0.tgz(r-4.4-any)PPInfer_1.33.0.tgz(r-4.3-any)
PPInfer_1.33.0.tar.gz(r-4.5-noble)PPInfer_1.33.0.tar.gz(r-4.4-noble)
PPInfer_1.33.0.tgz(r-4.4-emscripten)PPInfer_1.33.0.tgz(r-4.3-emscripten)
PPInfer.pdf |PPInfer.html✨
PPInfer/json (API)
NEWS
# Install 'PPInfer' in R: |
install.packages('PPInfer', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:PPInfer-1.33.0(bioc 3.21)PPInfer-1.32.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
softwarestatisticalmethodnetworkgraphandnetworkgenesetenrichmentnetworkenrichmentpathways
Last updated 2 months agofrom:d4d24bc527. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 30 2024 |
R-4.5-win | OK | Nov 30 2024 |
R-4.5-linux | OK | Nov 30 2024 |
R-4.4-win | NOTE | Nov 30 2024 |
R-4.4-mac | NOTE | Nov 30 2024 |
R-4.3-win | NOTE | Nov 30 2024 |
R-4.3-mac | NOTE | Nov 30 2024 |
Exports:enrich.netGSEA.barplotnet.infernet.infer.STnet.kernelORAORA.barplotppi.infer.humanppi.infer.mouseself.train.kernel
Dependencies:AnnotationDbiaskpassBHBiobaseBiocFileCacheBiocGenericsBiocParallelbiomaRtBiostringsbitbit64bitopsblobcachemcaToolschronclicodetoolscolorspacecowplotcpp11crayoncurldata.tableDBIdbplyrdigestdplyrfansifarverfastmapfastmatchfgseafilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggplot2gluegplotsgraphgsubfngtablegtoolshashhmshttrhttr2igraphIRangesisobandjsonliteKEGGRESTkernlabKernSmoothlabelinglambda.rlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrplotrixplyrpngprettyunitsprogressprotopurrrR6rappdirsRColorBrewerRcpprlangRSQLiteS4VectorsscalessnowsqldfSTRINGdbstringistringrsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrxml2XVectoryeastExpDatazlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Inferring functionally related proteins using protein interaction networks | PPInfer-package PPInfer |
Visualize network for the functional enrichment analysis | enrich.net |
Visualize the gene set enrichment analysis | GSEA.barplot |
Inferring functionally related proteins using networks | net.infer |
Inferring functionally related proteins with self training | net.infer.ST |
Kernel matrix for a graph | net.kernel |
Over-representation Analysis | ORA |
Visualize the over-representation analysis | ORA.barplot |
Inferring functionally related proteins using protein networks for human | ppi.infer.human |
Inferring functionally related proteins using protein networks for mouse | ppi.infer.mouse |
Self training for a kernel matrix | self.train.kernel |