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Journal Article
PhaLP 2.0: extending the community-oriented phage lysin database with a SUBLYME pipeline for metagenomic discovery Open Access
Database, Volume 2026, 2026, baag033, https://doi.org/10.1093/database/baag033
Published: 05 June 2026
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Correlation matrix derivation. Modelled predicted probabilities were used t... Open Access
Published: 05 June 2026
Figure 1
Correlation matrix derivation. Modelled predicted probabilities were used to compute Spearman correlations for each pairwise combination of publication types. Diagram showing how predictive scores for individual articles are converted to similarity correlation values pairwise across different pub
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Distribution of pairwise correlations for PTs. Spearman correlation was com... Open Access
Published: 05 June 2026
Figure 2
Distribution of pairwise correlations for PTs. Spearman correlation was computed among model-predicted probabilities for assignment of 72 publication types forming a 72 × 72 correlation matrix. The distribution of the correlation coefficients is bimodal with one mode centred around zero, the other a
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Study overview. (A) Training SUBLYME. A first model was trained on a datase... Open Access
Published: 05 June 2026
Figure 1
Study overview. (A) Training SUBLYME. A first model was trained on a dataset of lysins (from PhaLP) and non-lysin phage proteins (from INPHARED) to distinguish between these two classes. Then, a second model was trained, using just the lysins in PhaLP, to classify lysins as endolysins or virion-asso
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Evaluation of SUBLYME. Distribution of the precision and recall of models t... Open Access
Published: 05 June 2026
Figure 2
Evaluation of SUBLYME. Distribution of the precision and recall of models trained during repeated k-fold cross-validation as a function of the decision threshold used by models to make predictions. A total of 100 models (10 repeats with 10 folds per repeat) were trained and tested for the lysin pred
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Predicted lysins in the Fernández-Ruiz dataset. (A) t-SNE projection of pro... Open Access
Published: 05 June 2026
Figure 3
Predicted lysins in the Fernández-Ruiz dataset. (A) t-SNE projection of protein embeddings for all predicted lysins. In blue, lysins predicted by SUBLYME; in red, endolysins identified by Fernández-Ruiz et al . [ 29 ]; in yellow, endolysins identified by both methods. (B) Number of occurrences of t
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Lysins identified in the EnVhog database. (A) The number of proteins, stand... Open Access
Published: 05 June 2026
Figure 4
Lysins identified in the EnVhog database. (A) The number of proteins, standard clusters (30% sequence identity), and remote homology clusters predicted by SUBLYME, split according to lysin type (endolysin and virion associated lysin—VAL). (B) Number of representative endolysins (one per standard clu
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Domain architecture occurrences in PhaLP 2.0. More specific annotations are... Open Access
Published: 05 June 2026
Figure 5
Domain architecture occurrences in PhaLP 2.0. More specific annotations are listed below the principal architecture; only the most frequent ones are listed. Enzymatically active domains (EADs) are presented in red, cell wall-binding domains (CBDs) in blue, and miscellaneous domains in yellow. Sch
Journal Article
A similarity metric, rubric, and unified hierarchy for biomedical publication types and study designs Open Access
Database, Volume 2026, 2026, baag022, https://doi.org/10.1093/database/baag022
Published: 05 June 2026
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Hierarchical clustering of publication types by model-inferred probabilitie... Open Access
Published: 05 June 2026
Figure 3
Hierarchical clustering of publication types by model-inferred probabilities. Publication type clusters derived from pairwise model score correlations and grouped with hierarchical clustering. Cut points were chosen to delineate 13 low-level categories and 5 broader categories. Diagram showing th
Journal Article
GUTAID: a curated database linking gut microbial antigens to autoimmune mechanisms Open Access
Database, Volume 2026, 2026, baag029, https://doi.org/10.1093/database/baag029
Published: 03 June 2026
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Framework for developing GUTAID. For image description, please refer to ... Open Access
Published: 03 June 2026
Figure 1
Framework for developing GUTAID. For image description, please refer to the figure legend and surrounding text.
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The graphical user interface of GUTAID. (A) The Home page of GUTAID. (B) Th... Open Access
Published: 03 June 2026
Figure 2
The graphical user interface of GUTAID. (A) The Home page of GUTAID. (B) The search page of GUTAID. The user can search for antigens via antigen name or mechanism or both. (C) The Download page of GUTAID allows the user to download antigen sequences by mechanism. (D) The About page of GUTAID. For
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Parallels between natural language statements and data schemata. (A) A natu... Open Access
Published: 02 June 2026
Figure 2
Parallels between natural language statements and data schemata. (A) A natural language statement is structured by syntactic and grammatical conventions into syntactic positions of phrases of a syntax tree. (B) The syntax tree corresponding to the natural language statement from (A). (C) The formali
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From a formalized natural language statement to the corresponding light ver... Open Access
Published: 02 June 2026
Figure 5
From a formalized natural language statement to the corresponding light version of the RDF Rosetta Statement metamodel. (A) A formalized statement with its syntactic positions and associated semantic roles highlighted in color. (B) The light version of the RDF-based Rosetta Statement metamodel from
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Schema cross-walks from the light version Rosetta Statement schema for a me... Open Access
Published: 02 June 2026
Figure 8
Schema cross-walks from the light version Rosetta Statement schema for a measurement statement to four other schemata. Middle: The light version Rosetta Statement RDF schema for a measurement statement. Top left: The OBI schema. Top right: Relational database schema. Bottom left: The schema of the Q
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Input form for specifying a new RDF Rosetta Statement schema and accompanyi... Open Access
Published: 02 June 2026
Figure 9
Input form for specifying a new RDF Rosetta Statement schema and accompanying Rosetta Statement ontology class. Users provide a label (A) and a definition or description (B) for the corresponding Rosetta Statement class, together with some example sentences (C). An overview of the editing progress i
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Step-wise procedure for knowledge graph construction to lower the barrier f... Open Access
Published: 02 June 2026
Figure 11
Step-wise procedure for knowledge graph construction to lower the barrier from the semantic parsing burden. In the first step, the Rosetta Statement approach to knowledge graph construction is applied, using Wikidata as the underlying controlled vocabulary, resulting in a FAIR and CLEAR knowledge gr
Journal Article
Rosetta Statements: simplifying FAIR knowledge graph construction with a user-centred approach Open Access
Database, Volume 2026, 2026, baag030, https://doi.org/10.1093/database/baag030
Published: 02 June 2026
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Comparison of a human-readable statement with its machine-actionable and it... Open Access
Published: 02 June 2026
Figure 1
Comparison of a human-readable statement with its machine-actionable and its human-actionable representation. Top: A human-readable statement about the observation that a particular apple weighs 241.68 g, with a 95% confidence interval of 241.31–242.05 g. Middle: A machine-actionable representation
