Abstract Background 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. Results 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). Conclusion This combination of linguistic and statistical approaches appears...
With the rapid expansion in the number of published papers in the biomedical field, finding relevant...
Automatically extracting information from biomedical text holds the promise of easily consolidating ...
We present results from a variety of learned information extraction systems for identifying human pr...
Extracting information from a stack of data is a tedious task and the scenario is no different in pr...
During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experim...
Abstract Background Considerable efforts have been made to extract protein-protein interactions from...
BACKGROUND: We participated in three of the protein-protein interaction subtasks of the Second BioCr...
Motivation. The living cell is a complex machine, that depends on the proper functioning of its nume...
This paper presents the results of a largescale effort to construct a comprehensive database of know...
textabstractWe have developed a method that predicts Protein-Protein Interactions (PPIs) based on th...
Since researchers discovered that proteins do not function isolated in a cell but act in multi-prote...
MOTIVATION:Much effort has been invested in the identification of protein-protein interactions using...
Abstract-As research continues to generate vast amounts of data, pertaining to protein interactions,...
Background: The exponential increase of published biomedical literature prompts the use of text mini...
This is a poster of a paper from 4th Asia-Pacific Bioinformatics Conference 2006 published by Associ...
With the rapid expansion in the number of published papers in the biomedical field, finding relevant...
Automatically extracting information from biomedical text holds the promise of easily consolidating ...
We present results from a variety of learned information extraction systems for identifying human pr...
Extracting information from a stack of data is a tedious task and the scenario is no different in pr...
During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experim...
Abstract Background Considerable efforts have been made to extract protein-protein interactions from...
BACKGROUND: We participated in three of the protein-protein interaction subtasks of the Second BioCr...
Motivation. The living cell is a complex machine, that depends on the proper functioning of its nume...
This paper presents the results of a largescale effort to construct a comprehensive database of know...
textabstractWe have developed a method that predicts Protein-Protein Interactions (PPIs) based on th...
Since researchers discovered that proteins do not function isolated in a cell but act in multi-prote...
MOTIVATION:Much effort has been invested in the identification of protein-protein interactions using...
Abstract-As research continues to generate vast amounts of data, pertaining to protein interactions,...
Background: The exponential increase of published biomedical literature prompts the use of text mini...
This is a poster of a paper from 4th Asia-Pacific Bioinformatics Conference 2006 published by Associ...
With the rapid expansion in the number of published papers in the biomedical field, finding relevant...
Automatically extracting information from biomedical text holds the promise of easily consolidating ...
We present results from a variety of learned information extraction systems for identifying human pr...