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Journal Article
Naama Menda and others
Database, Volume 2025, 2025, baaf020, https://doi.org/10.1093/database/baaf020
Published: 21 March 2025
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Published: 21 March 2025
Figure 1. Database schema diagram of the tables required for storing post-composed ontology terms.
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Published: 21 March 2025
Figure 4. Post-composing traits using orthogonal ontologies by crop. Percentage of usage of each orthogonal ontology ( y -axis) by crop ( x -axis). Time of year and event ontologies are common for all crops, while treatment, cycle, plant section, and plant level are crop-specific.
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Published: 21 March 2025
Figure 6. Percentage and total number of unique post-composed and unique pre-composed traits by crop (cassava, banana, yam, and sweet potato) and trait group (A, B, and C).
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Published: 21 March 2025
Figure 2. The user interface for post-composing traits from SweetPotatoBase. Selecting the trait ontology term CO_331:0000294 along with time terms “month 1, month 2, month 3, and month 4” and the breeding event term “after harvest.” The interface shows one of the combinations is already stored in the databas
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Published: 21 March 2025
Figure 3. Ratios of post-composed/pre-composed trait annotations by crop. (a) cassava, yam, and sweet potato. (b) Banana. The numeric values for this graph are listed in Table 1
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Published: 21 March 2025
Figure 5. Most used orthogonal ontology terms ( x -axis) by percentage usage ( y -axis) in each Breedbase crop.
Journal Article
Swier Garst and others
Database, Volume 2025, 2025, baaf016, https://doi.org/10.1093/database/baaf016
Published: 19 March 2025
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Published: 19 March 2025
Figure 1. (a–c) show results on MNIST datasets, (d–f) show the various distributions for the MNIST2 dataset (IID, SI, and CI, respectively), and (g–h) show heatmaps resembling model updates throughout training on the IID and CI distributions, respectively.
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Published: 19 March 2025
Figure 2. The aggressive CI distribution for the fashion MNIST dataset (a), with the results for both IID and CI distributions reported in (b).
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Published: 19 March 2025
Figure 5. (a) and (b) show distributions of the MNM dataset, originally and after redistribution, respectively, with (c) showing the accuracy curve of ResNet 34 on the distribution from (b) (bs = batch size).
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Published: 19 March 2025
Figure 3. AUC performance of the five classifiers across different splits of dataset A2 across 10 clients in (a), FNN results when all three AML datasets A1–A3 are used with the original data are shown in (b), and (c) shows the FNN results on A1–A3 using the locally scaled data.
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Published: 19 March 2025
Figure 4. (a) and (d) show data distributions, (b) and (e) show t-distributed stochastic neighbor embedding plots (every dot is a molecule, and color indicates study), and (c) and (f) show performance results for the different classifiers for the central and federated setting.
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Published: 11 March 2025
Figure 5. VarGuideAtlas home page. The home page provides a user-friendly interface for searching and exploring the curated collection of variant interpretation guidelines.
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Published: 11 March 2025
Figure 6. Results of the “developmental” search in VarGuideAtlas.
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Published: 11 March 2025
Figure 1. Data acquisition process pipeline.
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Published: 11 March 2025
Figure 2. Query structure for the PubMed literature search.
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Published: 11 March 2025
Figure 4. Summary of the data acquisition results.
Journal Article
Mireia Costa and others
Database, Volume 2025, 2025, baaf017, https://doi.org/10.1093/database/baaf017
Published: 11 March 2025
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Published: 11 March 2025
Figure 3. Architecture VarGuideAtlas.