In silico Protein Interaction Network Analysis

In silico protein interaction network analysis is a featured service at our Protein Interactome Platform, which specializes in global protein-protein interaction using various functional genomics methodologies. With the advent of huge volumes of protein interaction datasets derived from various proteomic experiments, such as yeast-two-hybrid, Co-immunoprecipitation, Bimolecular Fluorescence Complementation, Chemical crosslinking, Affinity electrophoresis, Tandem affinity purification, Strep-protein interaction experiment, quantitative mass spectrometry, Protein-protein docking and so on, protein network analysis has become increasingly important for elucidating the function of a particular protein.

Participating in Human Proteinpedia and Human Proteome Organization, and working for the leading protein-protein interaction programs, such as Human Protein Reference Database, Human Liver Proteome Project and Proteomics Standards Initiative, our staff scientist have extensive experience in analyzing and presenting protein-protein interaction in a proteome-wide manner.

The integrated knowledge-based Protein Interactome Platform for network and pathway analysis has been well established for a single query gene, a gene list, an OMICS dataset or a network derived from a yeast two-hybrid system screen. From protein to protein interaction, from interaction network to pathway, professional services are provided at each level.
 

Featured services on protein analysis level:

1. Predicting protein interaction sites

Predict and visualize the interaction domains and the amino acids on the protein interface. These sites might be good drug targets.

2. Gene Ontology analysis

Annotate the query gene lists by Gene Ontology. Identify enriched GO terms in the query gene lists by comparing their GO frequencies against the background distribution.
 

Featured services on protein interaction level:

1. Mining the protein interaction in literature

Manually mine the protein interactions deposited in databases and literature.

2. Predict the potential interactors

Predict the potential interactions with multiple lines of evidence to ensure the confidence of the results.

3. Interaction retrieval

Test whether the interactions are already publicly known or novel by manual literature mining or database retrieval.
 

Featured services on interaction network level:

1. Network construction

Starting from query gene lists, construct the protein interaction network by literature mining and computational prediction. In particular, protein interaction data derived from yeast two-hybrid screening are frequently integrated.

2. Network confidence evaluation

Protein interactions from high-throughput screens are of false positives, therefore, computational approaches are employed to assess network’s confidence and filter out high-confidence subnet.

3. Network topology analysis

Present an overview of network topological features, such as diameter, degree distribution, shortest path distribution and clustering coefficient, and identify topologically important proteins in the network.

4. Gene function prediction

Predict the function of the unknown genes from the network context.

5. Specific network identification

Apply disease, tissue, functional process and sub-cellular localization filters to focus a network on relevant information
 

Featured services on pathway level:

1. Pathway map construction

Present the high quality manually created pathway maps to help understand the drug action mechanisms,

2. Comparison of protein interaction network and biological pathway

By comparing the network of the query genes with the known pathway databases, analyze the query gene lists in the context of pathways, check pathways related to the protein interaction network, present the pathway modules in the protein interaction network, and identify the potential interactions in pathway and the crosstalk proteins between signaling pathways.