Finding Biological Data Automatically
Author Information
Author(s): Christian Blaschke, Alfonso Valencia
Primary Institution: National Centre for Biotechnology, CNB-CSIC
Hypothesis
Can bibliographic pointers for known biological data be found automatically?
Conclusion
The study found that only 30% of known protein interactions could be linked to supporting sentences in Medline abstracts.
Supporting Evidence
- Only 30% of the known protein interactions had corresponding sentences in Medline abstracts.
- The study identified new relations between proteins that were not previously documented.
- Problems with protein name standardization complicated the identification process.
- Many interactions were not explicitly mentioned in the abstracts, making them undetectable.
Takeaway
The researchers tried to find connections between proteins using computer searches of scientific papers, but they only found links for about one in three interactions.
Methodology
The study used information retrieval technology to search Medline abstracts for sentences that support known protein interactions.
Limitations
The main limitations were the lack of standard protein names and the analysis of abstracts instead of full papers.
Digital Object Identifier (DOI)
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