Protein Interaction Network Analysis (PINA) platform is an integrated platform for protein interaction network construction, filtering, analysis, visualization, and management. It integrates protein-protein interaction (PPI) data from public curated databases and builds a complete, non-redundant protein interaction dataset for six model organisms. In particular, it provides a variety of built-in tools to filter and analyze the networks for gaining biological and functional insights into the network.
PINA v2.0  Mining interactome modules.
PINA v3.0   Revealing tumour type-specific insights from PPI networks.

News:
26 Sept. 2020 : The normalization strategy of mRNA expression data was updated to be comparable with other published studies, and the tutorial step-by-step case study was updated accordingly. The Data & Statistics page was redesigned to be more informative.

Network construction supports generating a protein-protein interaction network from:

• a single protein
• a set of proteins
• a list of protein interactions
• two sets of proteins

Integrated network viewer is an interactive and multi-functional tool to view, highlight, filter, show cancer context, analyze, and download a PPI network seamlessly.

Cancer Context provides a number of new analysis and visualization utilities by integrating PPI data with TCGA and CPTAC datasets:

• to infer network proteins with tumor type expression specificity.
• to identify candidate prognosis biomarkers, putative mutational cancer drivers, and therapeutic targets in a network, for a specific cancer type.
• to identify pairs of co-expressing interacting proteins across cancer types.

Network analysis includes:

• Interaction Correlation distribution
• enriched GO term identification
• topology feature calculation
• identification of topologically important proteins in the interaction network
• identification of common interacting proteins

Interactome modules provide multiple collections of network modules identified from Interactomes by applying several clustering algorithms with different parameter settings.

• The identified modules have been comprehensively annotated with known knowledge from Gene Ontology, KEGG pathways, PFAM domains, and MSigDB.
• Users can either simply search modules or identify enriched modules from the list of query proteins.

User space allows users to upload/edit interaction networks and to save on the server with account protection. The saved networks can be used as the input of the analysis tools.

Check the online Tutorial for a more detailed explanation of theuser interface and results.

Du, Y., Cai, M., Xing, X., Ji, J., Yang, E. and Wu, J. (2021) PINA 3.0: mining cancer interactome. Nucleic Acids Res, 49, D1351-D1357. [Full text]
Cowley, M.J., Pinese, M., Kassahn, K.S., Waddell, N., Pearson, J.V., Grimmond, S.M., Biankin, A.V., Hautaniemi, S. and Wu, J. (2012) PINA v2.0: mining interactome modules. Nucleic Acids Res, 40, D862-865. [Full text]
Wu, J., Vallenius, T., Ovaska, K., Westermarck, J., Makela, T.P. and Hautaniemi, S. (2009) Integrated network analysis platform for protein-protein interactions, Nature methods, 6, 75-77. [Abstract]

Protein-protein interaction data from IntAct, MINT, BioGRID, DIP, HPRD
Protein annotations from UniProt, Ensembl, WormBase, BioMart