Automated relation extraction (RE) from biomedical literature is critical for many downstream
text mining applications in both research and real-world settings. However, most existing …

Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …

Abstract Information encoded in natural language in biomedical literature publications is
only useful if efficient and reliable ways of accessing and analyzing that information are …

Motivation: Despite the central role of diseases in biomedical research, there have been
much fewer attempts to automatically determine which diseases are mentioned in a text …

The automatic extraction of chemical information from text requires the recognition of
chemical entity mentions as one of its key steps. When developing supervised named entity …

One effective way to improve the state of the art is through competitions. Following the
success of the Critical Assessment of protein Structure Prediction (CASP) in bioinformatics …

Named Entity Linking (nel) grounds entity mentions to their corresponding node in a
Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity …

The automatic recognition of gene names and their associated database identifiers from
biomedical text has been widely studied in recent years, as these tasks play an important …

Background The goal of the first BioCreAtIvE challenge (Critical Assessment of Information
Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of …

Abstract Biomedical Entity Linking (BEL) is the task of mapping of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …