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Literature DB >> 12463910

Discovering protein similarity using natural language processing.

Abstract

Extracting protein interaction relationships from textual repositories, such as MEDLINE, may prove useful in generating novel biological hypotheses. Using abstracts relevant to two known functionally related proteins, we modified an existing natural language processing tool to extract protein interaction terms. We were able to obtain functional information about two proteins, Amyloid Precursor Protein and Prion Protein, that have been implicated in the etiology of Alzheimer's Disease and Creutzfeldt-Jakob Disease, respectively.

Entities: Disease Species

Mesh：

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Year: 2002 PMID： 12463910 PMCID： PMC2244512

Source DB: PubMed Journal: Proc AMIA Symp ISSN： 1531-605X

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References

14 in total

Discovering protein similarity using natural language processing.

1. Mining molecular binding terminology from biomedical text.

2. Including biological literature improves homology search.

3. Bidirectional incremental parsing for automatic pathway identification with combinatory categorial grammar.

4. Detecting gene relations from Medline abstracts.

5. Event extraction from biomedical papers using a full parser.

6. Text-based discovery in biomedicine: the architecture of the DAD-system.

7. Creating knowledge repositories from biomedical reports: the MEDSYNDIKATE text mining system.

8. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.

9. Supporting discovery in medicine by association rule mining in Medline and UMLS.

Review 10. Automated extraction of information in molecular biology.