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Biomedical pre-trained language models (BioPLMs) have been achieving state-of-the-art results for various biomedical text mining tasks. However, prevailing fine-tuning approaches naively train BioPLMs on targeted datasets without considering the class distributions. This is problematic, especially with dealing with imbalanced biomedical gold-standard datasets for named entity recognition (NER). Regardless of the high-performing SOTA fine-tuned NER models, they are biased towards other (O) tags ...

Submitter: Ghadeer Mobasher

Investigation: Biomedical named entity recognition

Assays: No Assays

Photothermal model for Arabidopsis development, as published, converted to Simile format by Yin-Hoon Chew. Note that the XML file is just a dummy SBML file, the .SML is the working model file. Simile can read csv files (as attached) for meteorological data (hourly temperature, sunrise, sunset). Users only need to change the directory of the input variables. I have also attached the set of parameter values for each genotype.Related PublicationsWilczek et al. (2009). Effects of Genetic Perturbation ...

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