We present a maximum-entropy based system incorporating a diverse set of features for identifying genes and proteins in biomedical s. This system was entered in the BioCreative co...
Jenny Rose Finkel, Shipra Dingare, Christopher D. ...
Background: Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple syn...
Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevis...
Background: The increasing amount of published literature in biomedicine represents an immense source of knowledge, which can only efficiently be accessed by a new generation of a...
Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been deve...
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...