Investigations
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In biomedical text mining, named entity recognition (NER) is an important task used to extract information from biomedical articles. Improving the NER’s performance will directly have a positive impact on extracting relations between those entities. In recent years, deep learning has become the main research direction of NER due to the development of effective models. Language transformer models like e.g. BERT are frequently used because they enable the specialisation of models by domain-specific ...
Submitter: Christoff Odendaal
Studies: Model analysis, Model construction, Model validation, Sequestration of CoA and adaptation of CoA metabolism in MCAD-knockout c...
Assays: ACAD activity partitioning, Comparing acyl-CoA dehydrogenase deficiencies, Computational model (in silico), HepG2 cells (in vitro), HepG2 oxygen consumption, Kinetics Minireviews, MCADD patient personalised modelling, MCADD rescue titration, Metabolic control analysis, Mice (in vivo), Models, Predicting urinary acylcarnitines under metabolic decompensation., Whole-body ketogenic flux
