Background: In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and ...
The huge volumes of biomedical texts available online drives the increasing need for automated techniques to analyze and extract knowledge from these repositories of information. ...
We first analyzed protein names using various dictionaries and databases and found five problems with protein names; i.e., the treatment of special characters, the treatment of hom...
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...
Chemical named entities represent an important facet of biomedical text. We have developed a system to use character-based ngrams, Maximum Entropy Markov Models and rescoring to r...