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Digital surveillance in Latin American diseases outbreaks: information extraction from a novel Spanish corpus
BackgroundIn order to detect threats to public health and to be well-prepared for endemic and pandemic illness outbreaks, countries usually rely on...
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Machine learning-based donor permission extraction from informed consent documents
BackgroundWith more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing...
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Extract antibody and antigen names from biomedical literature
BackgroundThe roles of antibody and antigen are indispensable in targeted diagnosis, therapy, and biomedical discovery. On top of that, massive...
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A representation and deep learning model for annotating ubiquitylation sentences stating E3 ligase - substrate interaction
BackgroundUbiquitylation is an important post-translational modification of proteins that not only plays a central role in cellular coding, but is...
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A Combined Manual Annotation and Deep-Learning Natural Language Processing Study on Accurate Entity Extraction in Hereditary Disease Related Biomedical Literature
We report a combined manual annotation and deep-learning natural language processing study to make accurate entity extraction in hereditary disease...
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Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis
Here we demonstrate that the large language model GPT-4 can accurately annotate cell types using marker gene information in single-cell RNA...
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Southern spatial stories: interdisciplinary perceptions of shifting spatial awareness and values
ContextConsideration of historical maps for ecological research requires a bidirectional understanding of human-nature relationships. We investigated...
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The protein-protein interaction ontology: for better representing and capturing the biological context of protein interaction
BackgroundWith the rapid increase in the amount of Protein-Protein Interaction (PPI) data, the establishment of an event-centered PPI ontology that...
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Deep learning-enabled natural language processing to identify directional pharmacokinetic drug–drug interactions
BackgroundDuring drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the...
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Improving the recall of biomedical named entity recognition with label re-correction and knowledge distillation
BackgroundBiomedical named entity recognition is one of the most essential tasks in biomedical information extraction. Previous studies suffer from...
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A Gated Recurrent Unit based architecture for recognizing ontology concepts from biological literature
BackgroundAnnotating scientific literature with ontology concepts is a critical task in biology and several other domains for knowledge discovery....
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GPDminer: a tool for extracting named entities and analyzing relations in biological literature
PurposeThe expansion of research across various disciplines has led to a substantial increase in published papers and journals, highlighting the...
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Mining microbe–disease interactions from literature via a transfer learning model
BackgroundInteractions of microbes and diseases are of great importance for biomedical research. However, large-scale of microbe–disease interactions...
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Concept recognition as a machine translation problem
BackgroundAutomated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and...
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An analysis of entity normalization evaluation biases in specialized domains
BackgroundEntity normalization is an important information extraction task which has recently gained attention, particularly in the...
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Automatic consistency assurance for literature-based gene ontology annotation
BackgroundLiterature-based gene ontology (GO) annotation is a process where expert curators use uniform expressions to describe gene functions...
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Diversity and potentiality of multi-criteria decision analysis methods for agri-food research
There is a growing demand for moving towards sustainable agri-food systems which per nature covers a complex network of activities and domains; such...
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GO2Sum: generating human-readable functional summary of proteins from GO terms
Understanding the biological functions of proteins is of fundamental importance in modern biology. To represent a function of proteins, Gene Ontology...
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HEC-ASD: a hybrid ensemble-based classification model for predicting autism spectrum disorder disease genes
PurposeAutism spectrum disorder (ASD) is the most prevalent disease today. The causes of its infection may be attributed to genetic causes by 80% and...
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