PPI Finder: A Tool for Mining Protein-Protein Interactions
Author Information
Author(s): He Min, Wang Yi, Li Wei
Primary Institution: Key Laboratory of Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences
Hypothesis
Hybrid methods combining co-occurrence and rule-based approaches may perform better in predicting protein-protein interactions (PPIs).
Conclusion
PPI Finder provides a useful tool for biologists to uncover potential novel PPIs.
Supporting Evidence
- Only 28% of co-occurred pairs in PubMed abstracts appeared in known PPI databases.
- 69% of known PPIs in HPRD showed co-occurrences in the literature.
- PPI Finder uses a hybrid text mining approach combining statistical and computational linguistic methods.
Takeaway
PPI Finder helps scientists find connections between proteins by looking at research papers and finding words that suggest they interact.
Methodology
Developed a web-based tool to mine human PPIs from PubMed abstracts using co-occurrence and interaction words, validated against known PPI databases.
Limitations
The data used are offline and need to be updated regularly; the tool currently only processes literature related to Homo sapiens.
Digital Object Identifier (DOI)
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