Publications by authors named "Lin-Lung Ying"
Article Synopsis
- Biomedical Named Entity Recognition (bio NER) is advanced by a new model that incorporates external contexts for better identification of entities in biomedical texts.
- The model retrieves relevant sentences from PubMed, ranks them, and combines them with original input sequences to improve feature representation using PubMedBERT and a BiLSTM layer.
- Experiments show that this approach outperforms existing methods, highlighting that context improves entity recognition, with PubMed being more effective than Google for relevant information.
Systematic evolution of ligands by exponential (SELEX) is a revolutionary technology that integrates combinatorial chemistry with high throughput screening to generate from synthesized nucleic acid ligand libraries the high affinity nucleic acid ligands (aptamers) for interesting targets. Recently, the SELEX experiments have advanced from targeting the ligand libraries by a single purified target to multiple heterogeneous target samples. Having the potential of bringing enormous technical and economical advantages to drug discovery, the new application suffers from unpredictable performances.
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