Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information
<p>Abstract</p> <p>Background</p> <p>The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest.</p> <p>Results</p> <p>T...
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doaj-32e09bd862a54c27a27b0cc2b9fdab3e2020-11-25T01:56:59ZengBMCBMC Bioinformatics1471-21052005-06-016114310.1186/1471-2105-6-143Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical informationKershenbaum AaronCooper James W<p>Abstract</p> <p>Background</p> <p>The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest.</p> <p>Results</p> <p>This paper reports a scalable method for the discovery of protein-protein interactions in Medline abstracts, using a combination of text analytics, statistical and graphical analysis, and a set of easily implemented rules. Applying these techniques to 12,300 abstracts, a precision of 0.61 and a recall of 0.97 were obtained, (f = 0.74) and when allowing for two-hop and three-hop relations discovered by graphical analysis, the precision was 0.74 (f = 0.83).</p> <p>Conclusion</p> <p>This combination of linguistic and statistical approaches appears to provide the highest precision and recall thus far reported in detecting protein-protein relations using text analytic approaches.</p> http://www.biomedcentral.com/1471-2105/6/143 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kershenbaum Aaron Cooper James W |
spellingShingle |
Kershenbaum Aaron Cooper James W Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information BMC Bioinformatics |
author_facet |
Kershenbaum Aaron Cooper James W |
author_sort |
Kershenbaum Aaron |
title |
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
title_short |
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
title_full |
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
title_fullStr |
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
title_full_unstemmed |
Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
title_sort |
discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2005-06-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest.</p> <p>Results</p> <p>This paper reports a scalable method for the discovery of protein-protein interactions in Medline abstracts, using a combination of text analytics, statistical and graphical analysis, and a set of easily implemented rules. Applying these techniques to 12,300 abstracts, a precision of 0.61 and a recall of 0.97 were obtained, (f = 0.74) and when allowing for two-hop and three-hop relations discovered by graphical analysis, the precision was 0.74 (f = 0.83).</p> <p>Conclusion</p> <p>This combination of linguistic and statistical approaches appears to provide the highest precision and recall thus far reported in detecting protein-protein relations using text analytic approaches.</p> |
url |
http://www.biomedcentral.com/1471-2105/6/143 |
work_keys_str_mv |
AT kershenbaumaaron discoveryofproteinproteininteractionsusingacombinationoflinguisticstatisticalandgraphicalinformation AT cooperjamesw discoveryofproteinproteininteractionsusingacombinationoflinguisticstatisticalandgraphicalinformation |
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