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Updated: May 27, 2026

Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions
Published on: August 2, 2015
Network approaches to the functional analysis of microbial proteins
J S Hallinan1, K James, A Wipat
1School of Computing Science, Newcastle University, Newcastle, UK.
Computational data integration creates biological networks from diverse microbial data, aiding systems-level understanding and protein function inference. This approach alleviates manual database searching for researchers.
Area of Science:
- Microbiology
- Bioinformatics
- Systems Biology
Background:
- Vast amounts of biological data are available in numerous online databases.
- Accessing and integrating this data for a systems-level view of microbial cells is challenging for researchers.
- Manual data retrieval from multiple sources is time-consuming and inefficient.
Purpose of the Study:
- To describe the construction and analysis of biological networks.
- To highlight the benefits of computational data integration for understanding microbial systems.
- To demonstrate the application of networks in inferring protein function.
Main Methods:
- Construction of biological networks from single or multiple data sources.
- Integration of diverse biological data into network views.
- Enrichment of networks with ontological annotations.
- Analysis of networks using web service interfaces.
Main Results:
- Development of methods for constructing and analyzing single-data source and integrated biological networks.
- Demonstration that integrated networks facilitate a systems-level view of microbial cells.
- Application of networks for inferring protein function in microbes.
Conclusions:
- Computational data integration and network visualization are powerful tools for microbiology.
- Integrated biological networks improve the understanding of microbial cell structure and function.
- Network analysis aids in the inference of gene and protein functions within microbial systems.
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