The need for more mature techniques to extract and manage information from the literature in biomedicine is rapidly growing, as we begin to see an increasing number of field experts who are potential users of such techniques. We present, in this special issue, advances in the field, ranging from biomedical-named entity recognition, identifying pairs of terms that are related in ways that are not predicted in advance, using machine learning in two phases for enhanced extraction of biological event information, extracting contrastive information through the analysis of negation, and terminology-based knowledge mining for novel knowledge discovery.
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