PANDA (Preferential Attachment based common Neighbor Distribution derived Associations) is designed to perform the following tasks in PPI networks: (1) identify significantly functionally associated protein pairs, (2) predict GO terms and KEGG pathways for proteins, (3) make a cluster of proteins based on the significant protein pairs, (4) identify subclusters whose members are enriched in KEGG pathways. For other types of biological networks, (1) and (3) can still be performed.
|Author||Hua Li and Pan Tong|
|Date of publication||2016-12-05 18:28:46|
|Maintainer||Hua Li <firstname.lastname@example.org>|
dfPPI: An example of protein-protein interaction data
GENE2GOtopLite: An example of GO annotation data for proteins
GENE2KEGG: An example of KEGG annotation data for proteins
GOpredict-methods: Predict GO annotations for proteins
KEGGID2NAME: KEGG pathway ID to KEGG pathway name
KEGGpredict-methods: Predict KEGG pathway annotations for proteins
ProteinCluster-methods: Cluster proteins based on significant protein pairs
SignificantPairs-methods: Identify functionally associated protein pairs
SignificantSubcluster-methods: Subclusters with KEGG annotations significantly enriched
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