Abstract
Knowledge of regulation relations is widely applied by biomedical researchers in for example experiment design
on regulatory pathways and in systems biology. Such knowledge has typically been represented very roughly as
simple graphs or very expressively in simulations of pathways.
In the work presented here, we analyze 6 frequently used verbs denoting the regulation relations regulates,
positively regulates and negatively regulates through corpus analysis, and propose a formal representation of the
acquired knowledge as domain speci¯c semantic frames. The acquired knowledge patterns can thus be used to
identify and reason over knowledge represented in texts from the biomedical domain.
on regulatory pathways and in systems biology. Such knowledge has typically been represented very roughly as
simple graphs or very expressively in simulations of pathways.
In the work presented here, we analyze 6 frequently used verbs denoting the regulation relations regulates,
positively regulates and negatively regulates through corpus analysis, and propose a formal representation of the
acquired knowledge as domain speci¯c semantic frames. The acquired knowledge patterns can thus be used to
identify and reason over knowledge represented in texts from the biomedical domain.
| Original language | English |
|---|---|
| Publication date | 25 Oct 2011 |
| Number of pages | 6 |
| Publication status | Published - 25 Oct 2011 |
| Externally published | Yes |
| Event | 4th International Symposium on Semantic Mining in Biomedicine - European Bioinformatics Institute (EBI), Hinxton, United Kingdom Duration: 25 Oct 2010 → 26 Oct 2010 http://www.smbm.eu/Home |
Conference
| Conference | 4th International Symposium on Semantic Mining in Biomedicine |
|---|---|
| Location | European Bioinformatics Institute (EBI) |
| Country/Territory | United Kingdom |
| City | Hinxton |
| Period | 25/10/2010 → 26/10/2010 |
| Internet address |