Biomedical event extraction (EE) systems have already been integrated with a number of applications, such as semantic search, association mining for knowledge discovery, bioprocess extraction and pathway reconstruction (Ananiadou et al., 2010; Björne et al., 2010; Tsuruoka et al., 2011; Wang et al., 2011).
At a time of societal urgency surrounding ecological crises from depleted fisheries to mineral extraction and potential pathways towards environmental and ecological justice, this book re-examines ecologically unequal exchange (EUE) from a historical and comparative perspective.
We have developed a system, PWTEES, which extracts pathway interactions from the literature utilizing an existing event extraction tool (TEES) and pathway named entity recognition (PathNER).
DDV: study design, RNA extraction, gene expression and pathway analysis, manuscript preparation.
GB conducted all of the microarray experiments, carried out the data extraction and performed the pathway interaction analysis.
The recognition of chemical entities is also crucial for other subsequent text processing tasks, such as detection of drug-protein interactions [2], adverse effects of chemical compounds and their associations to toxicological endpoints, or the extraction of pathway and metabolic reaction relations and so on.
For this purpose, we developed a computational tool (Pathway Extraction and Reduction Algorithm [PERA]) that automatically extracts priors from the Pathway Commons signaling information resource (Demir et al., 2010; Cerami et al., 2011).
While the applicability of the results produced by IE methods employing relation representations is closely tied to the specific relation type targeted (i.e. PPI or gene disease), event representations have wider potential in supporting applications ranging from PPI to semantic search and pathway extraction (Kim et al., 2009).
The recognition of such names are crucial for biomedical text processing tasks, e.g., detection of drug-protein interactions, adverse effects of chemical compounds and their associations to toxicological endpoints or extraction of pathway and metabolic reaction relations.
Simultaneously, it is also important to note that the accuracy and the reliability of this procedure depend on the intelligence of human resources, who are involved in the manual curation and extraction of pathway information from the large pool of experimental data.
Pathway Extraction and Reduction Algorithm (PERA) was developed to automatically extract prior information from multiple signaling databases and generate a prior information network.
