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(a) The template for Constrained Augmentor. (b) Details of how Constrained ... Open Access
Published: 03 July 2025
Figure 4.
(a) The template for Constrained Augmentor. (b) Details of how Constrained Augmentor is applied in the BioRED dataset.
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Template for SemQ filter. Open Access
Published: 03 July 2025
Figure 5.
Template for SemQ filter.
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Constrained Augmentor applied in information retrieval task. Open Access
Published: 03 July 2025
Figure 6.
Constrained Augmentor applied in information retrieval task.
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Example of generated data in BioRED with semantic score. Highlights indicat... Open Access
Published: 03 July 2025
Figure 7.
Example of generated data in BioRED with semantic score. Highlights indicate modifications that preserve the same semantic meaning. Underlines denote the entities with unique tags around them.
Journal Article
CAS: enhancing implicit constrained data augmentation with semantic enrichment for biomedical relation extraction and beyond Open Access
Database, Volume 2025, 2025, baaf025, https://doi.org/10.1093/database/baaf025
Published: 03 July 2025
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(a) Results of generated data using traditional data augmentation approache... Open Access
Published: 03 July 2025
Figure 1.
(a) Results of generated data using traditional data augmentation approaches. (b) Results of generated data using our method. Text enclosed in rounded rectangles represents entity tags or components that should be preserved (corresponding to the highlighted text). Text that should have been preserve
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Constrained Augmentor applied in code completion task. Open Access
Published: 03 July 2025
Figure 9.
Constrained Augmentor applied in code completion task.
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(a) An example of a biomedical relation extraction task for a “Positive Cor... Open Access
Published: 03 July 2025
Figure 2.
(a) An example of a biomedical relation extraction task for a “Positive Correlation” relation between two types of entity, Gene and Chemical, being wrapped in entity type tagging. There will be a source entity (with “Src” tags) and a Target entity (with “Tgt” tag). The specific tags @/EntityType$
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Overall flow of the framework. Open Access
Published: 03 July 2025
Figure 3.
Overall flow of the framework.
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Example of generated data in Code Completion with semantic score. Highlight... Open Access
Published: 03 July 2025
Figure 8.
Example of generated data in Code Completion with semantic score. Highlights indicate modifications that preserve the same semantic meaning. Underlines denote the entities with unique tags around them. Bold text represents modifications that alter the semantic meaning.
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Artificial Intelligence Driven Predictive Framework for Analyzing Protein S... Open Access
Published: 30 May 2025
Figure 1.
Artificial Intelligence Driven Predictive Framework for Analyzing Protein Sequences Across Diverse Bioinformatics Tasks.
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Precise classification of unique protein sequence analysis tasks in 11 majo... Open Access
Published: 30 May 2025
Figure 3.
Precise classification of unique protein sequence analysis tasks in 11 major biological goals.
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A comprehensive methodical categorization of protein sequence analysis task... Open Access
Published: 30 May 2025
Figure 4.
A comprehensive methodical categorization of protein sequence analysis tasks into regression, binary classification, multi-class classification, multi-label classification, and clustering.
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Utilization of 15 different LLMs in diverse protein sequence analysis pipel... Open Access
Published: 30 May 2025
Figure 6.
Utilization of 15 different LLMs in diverse protein sequence analysis pipelines based on a variety of machine and deep learning algorithms
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Distribution of publishers involved in the publication of protein sequence ... Open Access
Published: 30 May 2025
Figure 8.
Distribution of publishers involved in the publication of protein sequence analysis literature.
Journal Article
Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models Open Access
Database, Volume 2025, 2025, baaf027, https://doi.org/10.1093/database/baaf027
Published: 30 May 2025
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Utilization of 22 different word embedding methods in diverse protein seque... Open Access
Published: 30 May 2025
Figure 5.
Utilization of 22 different word embedding methods in diverse protein sequence analysis pipelines based on a variety of machine and deep learning predictors
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Illustration of confusion matrix. Open Access
Published: 30 May 2025
Figure 7.
Illustration of confusion matrix.
