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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
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PINOT: an intuitive resource for integrating protein-protein interactions
James E Tomkins1, Raffaele Ferrari2, Nikoleta Vavouraki1
1School of Pharmacy, University of Reading, Whiteknights, Reading, RG6 6AP, UK.
Cell Communication and Signaling : CCS
|June 13, 2020
Summary
PINOT is a new web tool that simplifies collecting and analyzing protein-protein interaction (PPI) data. It helps researchers build biological networks by providing quality-controlled, confidence-scored PPI information from curated literature.
Area of Science:
- Bioinformatics
- Systems Biology
- Computational Biology
Background:
- Omics data, including protein-protein interaction (PPI) data, is crucial for understanding biological systems in health and disease.
- Existing databases curate PPI information from peer-reviewed literature, but integrating this data is challenging and time-consuming.
Purpose of the Study:
- To present PINOT (Protein Interaction Network Online Tool), a user-friendly web resource for optimizing the collection and processing of PPI data.
- To facilitate the construction of human and Caenorhabditis elegans PPI networks.
Main Methods:
- PINOT accepts user queries with lists of proteins of interest.
- It downloads, merges, and quality-assesses PPI data from IMEx consortium repositories and WormBase.
- Interactions are confidence-scored based on detection methods and publication history.
Main Results:
- PINOT extracts and processes PPI data efficiently, handling large queries.
- It applies quality control filters, reducing the need for manual inspection.
- Results are provided in a customizable table format, suitable for network visualization software.
Conclusions:
- PINOT offers an innovative solution for surveying curated literature and extracting PPI data.
- It provides valuable information on interaction detection methods and publication history.
- The tool streamlines the process of building and analyzing biological networks.
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