Protein Interaction Network Analysis (PINA)

Category Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract The 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 data from six (6) public curated databases (see below...) and builds a complete, non-redundant protein interaction dataset for six (6) model organisms (see below...).

Moreover, it provides a variety of built-in tools to filter and analyze the network for gaining insight into the network.

At the same time, PINA allows users to either edit the network generated from the public data, or combine these with uploaded private data to build more complete protein-protein interaction (PPI) networks.

The six (6) public curated databases are -- Molecular INTeraction database (MINT), IntAct (protein interaction data), Database of Interacting Proteins (DIP), Biological General Repository for Interaction Datasets (BioGRID);

Human Protein Reference Database (HPRD), and the Munich Information Center for Protein Sequences (MIPS)/MPact - MPact provides a common access point to interaction resources at MIPS.

The six (6) model organisms are -- Homo sapiens, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, and Rattus norvegicus.

PINA features/capabilities:

1) Network Construction: Generate PPI networks from flexible query options --

Network construction generates the protein-protein interaction network from a) a single protein, b) a list of proteins, c) a list of protein pairs or d) two lists of proteins.

• a) Query a protein - to study your favorite protein. Gene name, UniProt accession number and other database identifiers including Ensembl Gene, Ensembl Protein, NCBI Gene, UniGene, etc. are supported.
• If the “extend search” option is checked, the system will also search and show interactions between interacting proteins of the query protein.
• b) Query a list of proteins - to study a list of proteins that are part of your research interest.
• c) Query a list of interactions - to rapidly identify whether homemade interactions (for example, generated by a yeast two-hybrid screening) are already publicly known or novel.
• Moreover, if the “extended search” is selected, PINA will show you all publicly known interactions between proteins (for example, interactions between preys) in the list besides query interactions.
• d) Query two (2) lists of proteins - to study two (2) lists of proteins that have biological correlation, to see whether there is any correlation in the protein interaction level.

For example, input a list of up-regulated genes and a list of down-regulated genes from a microarray experiment.

2) Network Filter: Get a more credible network by different criteria --

The Network filter selects interactions from an existing network by specific criteria including a) detection method, b) interaction type, c) reference publication, d) user comment and e) semantic similarity of Gene Ontology (GO) terms.

The Network Filter (Annotation) selects interactions from the existing network by the following criteria:

• a) Detection method - categorizes interactions by interaction detection methods;
• b) Interaction type - categorizes interactions by the type of interactions;
• c) PubMed - lists interactions identified by the specified publication;
• d) My comment - lists interactions based on my comment.
• e) Network Filter (GO) analysis - identifies interactions based on the semantic similarity score between annotated GO terms of interacting proteins. And, it offers two (2) methods:
• e1) Combine method - is the strategy of combining semantic similarity scores of multiple GO terms associated with a protein.
• e2) Metric - is the method to calculate the semantic similarity measure.

3) Network Analysis: Gain the insight of the network --

Network analysis includes a) enriched GO term identification, b) topology feature calculation, c) identification of topologically important proteins in the interaction network, and d) identification of common interacting proteins.

• a) Network Function analysis - identifies enriched GO terms in the PPI network by comparing GO frequencies in the given network against the background distribution, i.e. the distribution of GO terms of the whole organism.
• GO is structured as a hierarchical directed acyclic graph (DAG), which was taken into account when counting the number of annotated proteins.
• A protein is thought to be associated with a certain GO term if it is annotated with the term itself or a child of the term.
• b) Network Topology - gives an overview of network topological features including diameter, degree distribution, shortest path distribution and clustering coefficient of the interaction network.
• c) Topologically Important Proteins analysis - applies centrality measures to identify topologically important proteins in the interaction network.
• Four (4) centrality measures including eigenvector centrality, betweenness centrality, closeness centrality, and degree centrality are implemented in PINA to determine the relative importance of a node (protein) within the graph (interaction network).
• d) Common Interacting Proteins analysis - identifies proteins that interact with at least two (2) of the query proteins in the network.

4) Network Visualization: an interactive environment to view and edit a network --

Network visualization - provides an interactive tool to view, edit and analyze an interaction network. It can be launched in the query result page, “My networks” or “Shared networks”.

5) Network Download --

An interaction network can be downloaded to a local disk in the GraphML format, MITAB format or PINA tab-delimited format.

GraphML - GraphML is a XML format for graph representation. Node elements describe gene name, protein name, UniProt AC, GO terms of proteins; edge elements describe the interaction of proteins.

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

7) User community -- allows registered users (registration is free...) to write comments on interactions and share comments/networks with other users in PINA.

8) Data Integration: Non-redundant and more complete --

• a) You can integrate data from the 6 public protein-protein interaction databases (see above...) to get a more complete dataset.
• b) You can identify the same interaction records in the different databases to build a non-redundant dataset.
• c) You can use BioMart, and UniProt to annotate each protein with the same high quality information because some of the original records have limited annotation.

System Requirements

Contact manufacturer.

Manufacturer

• Genome-Scale Biology Program
• Institute of Biomedicine
• University of Helsinki
• Haartmaninkatu 8, Helsinki 00014, Finland

Manufacturer Web Site PINA

Price Contact manufacturer.

G6G Abstract Number 20706

G6G Manufacturer Number 104278