1-20 of 9310
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
Image
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.
Image
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
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
Image
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
Image
Cross-walk from one schema to another for a weight measurement statement. T... Open Access
Published: 02 June 2026
Figure 3
Cross-walk from one schema to another for a weight measurement statement. The same weight measurement statement is modeled using two different schemata. Top: The weight measurement according to the schema of the Ontology for Biomedical Investigations [ 83 ] of the Open Biological and Biomedical Onto
Image
Structure of the full version of the Rosetta Statement metamodel. The RDF-b... Open Access
Published: 02 June 2026
Figure 6
Structure of the full version of the Rosetta Statement metamodel. The RDF-based Rosetta Statement schema for the statement from Fig. 5A), according to the full version of the Rosetta Statement metamodel. Compared to the light version (Fig. 5B), it introduces the possibility of having several statem
Image
Display of RDF Rosetta Statements in the ORKG UI in the view and the edit m... Open Access
Published: 02 June 2026
Figure 10
Display of RDF Rosetta Statements in the ORKG UI in the view and the edit mode, using the dynamic label. (A) The representation of a weight measurement statement of a particular orange using the measurement statement Rosetta Statement schema, without specifying a confidence level. Empty object-pos
Image
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
Image
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
Image
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
Image
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
Image
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
Image
From the structure of a natural language statement to the structure of an R... Open Access
Published: 02 June 2026
Figure 4
From the structure of a natural language statement to the structure of an RDF-based Rosetta Statement schema. (A) A natural language statement (token model) with the predicate has (measurement) . (B) The corresponding formalized natural language statement (metamodel), with the syntactic positions a
Image
Textual and graphical displays of a statement based on its Rosetta Statemen... Open Access
Published: 02 June 2026
Figure 7
Textual and graphical displays of a statement based on its Rosetta Statement schema. Middle: The RDF Rosetta Statement schema of a travels statement (here, applying the light version of the Rosetta Statement approach). Top: A textual display of the travels statement, i.e. a dynamic label that is ass
Image
Squamata (snakes and lizards) are the most represented order in Tox-Prot, a... Open Access
Published: 30 May 2026
Figure 2
Squamata (snakes and lizards) are the most represented order in Tox-Prot, accounting for roughly a third of all venom protein entries throughout two decades of database growth. The line chart tracks the number of entries for the five most represented taxonomic orders in Tox-Prot from 2005 to 2025. S
Image
Functional clustering of the 10 most abundant venom protein families in Tox... Open Access
Published: 30 May 2026
Figure 7
Functional clustering of the 10 most abundant venom protein families in Tox-Prot 2025 reveals distinct separation between short peptide toxins and large enzymatic families. Two-dimensional UMAP [ 21 ] projection of ProtT5 embeddings [ 19 ], where each point represents a venom protein coloured by pro
Journal Article
Quantitative analysis of growth and diversification in venom data using database metrics Open Access
Database, Volume 2026, 2026, baag032, https://doi.org/10.1093/database/baag032
Published: 30 May 2026
Image
Only 11 of 264 venom protein families are shared between terrestrial and ma... Open Access
Published: 30 May 2026
Figure 4
Only 11 of 264 venom protein families are shared between terrestrial and marine species, yet these families account for the majority of Tox-Prot entries. (A) Distribution of entries, species, and protein families by habitat in the 2025 Tox-Prot dataset. Terrestrial species (green, bottom) dominate i
Image
Short mature venom peptides of 26–75 amino acids (aa) dominate Tox-Prot, wi... Open Access
Published: 30 May 2026
Figure 5
Short mature venom peptides of 26–75 amino acids (aa) dominate Tox-Prot, with the database showing a strongly right-skewed length distribution across all three time points. The stacked histogram displays the mature peptide length distribution of Tox-Prot entries, in 25 aa bins, for 2005 (yellow, bot
