1-20 of 12118
Image
An overlap analysis of genetic variant associations across B12 traits. Open Access
Published: 01 October 2025
Figure 3.
An overlap analysis of genetic variant associations across B 12 traits.
Image
Distribution of genes reported to be associated with different B12 traits: ... Open Access
Published: 01 October 2025
Figure 4.
Distribution of genes reported to be associated with different B 12 traits: (a) total plasma/serum B 12 , (b) holoTC (active B 12), (c) holohaptocorrin (holoHC), (d) MMA, and (e) total transcobalamin (totalTC) levels. The number in parentheses next to each gene name represents the count of reported
Image
Screenshots of the CobVar database application featuring the Home page, and... Open Access
Published: 01 October 2025
Figure 5.
Screenshots of the CobVar database application featuring the Home page, and the different search query formats that can be used by the user.
Image
Screenshots of (a) the expanded database query results, (b) the detailed vi... Open Access
Published: 01 October 2025
Figure 6.
Screenshots of (a) the expanded database query results, (b) the detailed view of the Variant section, and (c) the Association section.
Image
A summary schematic of the key genes involved in the absorption, transport,... Open Access
Published: 01 October 2025
Figure 1.
A summary schematic of the key genes involved in the absorption, transport, and metabolic utilization of B 12 across different body compartments. TCN1: transcobalamin I (haptocorrin); TCN2: transcobalamin II; GIF: gastric intrinsic factor (IF); FUT2: fucosyltransferase 2; FUT6: fucosyltransferase 6
Image
A schematic workflow of data collection and database integration for CobVar... Open Access
Published: 01 October 2025
Figure 2.
A schematic workflow of data collection and database integration for CobVar database.
Journal Article
CobVar—a comprehensive resource of vitamin B12-associated genomic variants Open Access
Database, Volume 2025, 2025, baaf049, https://doi.org/10.1093/database/baaf049
Published: 01 October 2025
Journal Article
Navigating open-source waters: the pharmaceutical industry’s role in bioontology development Open Access
Database, Volume 2025, 2025, baaf066, https://doi.org/10.1093/database/baaf066
Published: 30 September 2025
Journal Article
Characterization and automated classification of sentences in the biomedical literature: a case study for biocuration of gene expression and protein kinase activity Open Access
Database, Volume 2025, 2025, baaf063, https://doi.org/10.1093/database/baaf063
Published: 30 September 2025
Image
Comparison of average F1 scores across different dataset sizes for the thre... Open Access
Published: 30 September 2025
Figure 3.
Comparison of average F1 scores across different dataset sizes for the three curation tasks: Task 1 (fully curatable), Task 2 (partially curatable), and Task 3 (language related) for the gene expression and protein kinase activity datasets.
Image
Current and planned integration of sentence classification output into cura... Open Access
Published: 30 September 2025
Figure 4.
Current and planned integration of sentence classification output into curation workflows. (A) Extracted sentences identified as fully or partially curatable are presented to professional curators via a dedicated interface, allowing for rapid evaluation and annotation of key data types. (B) Future i
Image
UMAP visualization of sentence embeddings for gene expression (left panel) ... Open Access
Published: 30 September 2025
Figure 1.
UMAP visualization of sentence embeddings for gene expression (left panel) and protein kinase activity (right panel). A detailed description of the sentence classes is reported in Table 1 .
Image
Barcharts representing the average F1 score for the different models tested... Open Access
Published: 30 September 2025
Figure 2.
Barcharts representing the average F1 score for the different models tested for the three curation tasks.
Image
Schematic representation of the development of VineColD. (a) Generation of ... Open Access
Published: 27 September 2025
Figure 1.
Schematic representation of the development of VineColD. (a) Generation of the new grapevine cold hardiness prediction model, NYUS.2.1; (b) curation of global and regional weather data; (c) computation of grapevine cold hardiness prediction; and (d) data processing and analysis of predicted grapevin
Image
Curation of temperature data for VineColD. (a) Distribution of weather stat... Open Access
Published: 27 September 2025
Figure 3.
Curation of temperature data for VineColD. (a) Distribution of weather stations in the global data curation process for historical grapevine cold hardiness tracing; (b) number of stations per year; (c) number of years recorded per station; (d) number of missing years per station; (e) number of stati
Image
Quantification of the impact of climate change on grapevine cold damage in ... Open Access
Published: 27 September 2025
Figure 5.
Quantification of the impact of climate change on grapevine cold damage in North America from 1960 to 2024. (a) Average seasonally minimum temperature across all the curated weather stations. The line in the middle represents the average of the 64 dormant seasons; (b) average seasonally maximum esti
Journal Article
VineColD: an integrative database for global historical tracing and real-time monitoring of grapevine cold hardiness Open Access
Database, Volume 2025, 2025, baaf055, https://doi.org/10.1093/database/baaf055
Published: 27 September 2025
Image
User interface of the R Shiny-based application containing VineColD. (a) Ho... Open Access
Published: 27 September 2025
Figure 4.
User interface of the R Shiny-based application containing VineColD. (a) Home page of the application; (b) composition of ‘Station data’ under ‘Historical data’ tab; (c) composition of ‘Bulk download’ under ‘Historical data’ tab; (d) composition of ‘North America long-term data viewer’ under ‘Histor
Image
Model selection, feature importance analysis, and model testing for the NYU... Open Access
Published: 27 September 2025
Figure 2.
Model selection, feature importance analysis, and model testing for the NYUS.2.1 model. (a) The performance (RMSE) of all models generated during the NYUS.2.1 training process; (b) distribution of SHAP value for the top 15 features in the final model, with feature importance ranked by the mean absol
Journal Article
Correction to: CardioHotspots: a database of mutational hotspots for cardiac disorders Open Access
Database, Volume 2025, 2025, baaf050, https://doi.org/10.1093/database/baaf050
Published: 25 September 2025
