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The system implements a bounded state machine with explicit termination cri...
Published: 13 August 2026
Figure 1
The system implements a bounded state machine with explicit termination criteria. Given a question, MedHopper: (i) routes it to one of four strategies (direct, definition, intersection, and multi-hop) and predicts answer type; (ii) constructs strategy-dependent queries; (iii) retrieves dense candida
Journal Article
MedHopper: an agentic RAG-LLM system for multi-hop biomedical QA
Rustam Ruslanovich Taktashov,
Nadezhda Yurievna Biziukova,
Alexander Viktorovich Dmitriev,
Olga Aleksandrovna Tarasova
Database, Volume 2026, 2026, baag047, https://doi.org/10.1093/database/baag047
Published: 13 August 2026
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Distribution of disagreement scores; computation details are provided in A...
Published: 13 August 2026
Figure 2
Distribution of disagreement scores; computation details are provided in Appendix A.1 . For image description, please refer to the figure legend and surrounding text.
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Main function navigation of scRiskDB. (A) Main navigation bar of scRiskDB. ...
Published: 05 August 2026
Figure 3
Main function navigation of scRiskDB. (A) Main navigation bar of scRiskDB. (B) Drop-down menus for selecting tissues and cell types in each exploration module. (C) Example output tables from the SNV to Risk Genes (top) and SNV to Risk CREs (bottom) section. (D) The Explore SNVs page allows use
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Case studies demonstrating multi-level regulatory exploration using scRiskD...
Published: 05 August 2026
Figure 4
Case studies demonstrating multi-level regulatory exploration using scRiskDB. (A) Gene exploration in brain tissue identifies schizophrenia (SCZ)-associated GRIN family genes (e.g. GRIN2A) and provides integrated access to external validation resources such as Open Targets and LDexpress. (B) The Ex
Journal Article
scRiskDB: a single-cell epigenomic resource linking complex traits to regulatory mechanisms across human tissues
Gefei Zhao,
Xianfeng Ping,
Binbin Lai
Database, Volume 2026, 2026, baag048, https://doi.org/10.1093/database/baag048
Published: 05 August 2026
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Variants to SNV framework of scRiskDB. scRiskDB implements a systematic var...
Published: 05 August 2026
Figure 1
Variants to SNV framework of scRiskDB. scRiskDB implements a systematic variant-to-function framework that integrates single-cell data and GWAS data to functionally interpret disease-associated single nucleotide variants (SNVs). The platform compiles multimodal single-cell datasets across over 200 h
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Database contents. The multiple functions supported by scRiskDB and the spe...
Published: 05 August 2026
Figure 2
Database contents. The multiple functions supported by scRiskDB and the specific entries contained in each function. For image description, please refer to the figure legend and surrounding text.
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Illustrative structures from the front page of the database pointing to cla...
Published: 31 July 2026
Figure 1
Illustrative structures from the front page of the database pointing to classes 1, 2, and 3 with the corresponding phylogenetic trees; numbers indicate the phylogenetic families within each class. Six-panel Fig. showing ribbon structures and phylogenetic trees for the three classes of asparaginas
Journal Article
The Asparaginase Database: a comprehensive resource and classification of l-asparaginases
Max Štětina,
Aleš Křenek,
Guglielmo Tedeschi,
Filip Krása,
Vojtěch Spiwok,
Eva Benešová
Database, Volume 2026, 2026, baag045, https://doi.org/10.1093/database/baag045
Published: 31 July 2026
Journal Article
RUM/FILH: a standardized operational capability model for biodiversity databases
Miklós Bán
Database, Volume 2026, 2026, baag044, https://doi.org/10.1093/database/baag044
Published: 28 July 2026
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ExositeDB Confidence Scoring System and Quality Assessment. (a) Distributio...
Published: 28 July 2026
Figure 3
ExositeDB Confidence Scoring System and Quality Assessment. (a) Distribution of overall confidence scores across 525 validated entries, showing tier classification: Low (< 0.60), Medium (0.60–0.79), and High ( 0.80). Vertical lines indicate mean (0.634) and median (0.671) values. (b) Component s
Journal Article
STING-ExositeDB: An AI-assisted curated database of protein exosites for drug discovery
Folorunsho Bright Omage,
Ivan Mazoni,
Inácio Henrique Yano,
Goran Neshich
Database, Volume 2026, 2026, baag031, https://doi.org/10.1093/database/baag031
Published: 28 July 2026
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Conceptual framework of protein exosites and ExositeDB development. (a) Fun...
Published: 28 July 2026
Figure 1
Conceptual framework of protein exosites and ExositeDB development. (a) Fundamental distinction between exosites and allosteric sites: exosites primarily recruit macromolecular partners while allosteric sites regulate catalytic activity. (b) Clinical validation through thrombin exosite I targeting v
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Interactive Web Platform Architecture and Features. (a) System architecture...
Published: 28 July 2026
Figure 4
Interactive Web Platform Architecture and Features. (a) System architecture showing three-tier design with React frontend, FastAPI backend, and MySQL database, enabling RESTful API access and interactive 3D visualization. (b) Screenshot of search interface demonstrating faceted filtering across prot
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Database Coverage and Temporal Analysis. (a) Exosite-specific entry counts ...
Published: 28 July 2026
Figure 5
Database Coverage and Temporal Analysis. (a) Exosite-specific entry counts across databases: ExositeDB (525 entries), PDB full-text search (98 entries), and UniProt keyword search (82 entries), demonstrating 5.4 larger coverage compared to existing resources. (b) Temporal distribution showing ann
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AI-assisted curation pipeline for ExositeDB. The six-stage workflow proceed...
Published: 28 July 2026
Figure 2
AI-assisted curation pipeline for ExositeDB. The six-stage workflow proceeds from structured PubMed literature mining (Stage 1) through three-pass GPT-4o extraction (Stage 2), PDB-based structural validation with SIFTS residue mapping (Stage 3), four-component confidence scoring (Stage 4), expert re
Journal Article
TogoMCP: natural language querying of life-science knowledge graphs via schema-guided LLMs and the Model Context Protocol
Akira R Kinjo,
Yasunori Yamamoto,
Samuel Bustamante-Larriet,
Jose-Emilio Labra-Gayo,
Takatomo Fujisawa
Database, Volume 2026, 2026, baag042, https://doi.org/10.1093/database/baag042
Published: 24 July 2026
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Sample collection and processing workflow. Butterflies were captured in the...
Published: 24 July 2026
Figure 1
Sample collection and processing workflow. Butterflies were captured in the field and immediately placed in labelled envelopes inside a cooler bag to prevent dehydration and to anesthetize them. Freezing does not generally damage butterfly wings that are coloured by pigments but can damage structura
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Correlation between wing brightness measured under sunlight and artificial ...
Published: 24 July 2026
Figure 5
Correlation between wing brightness measured under sunlight and artificial illumination. Nine butterfly species were imaged under natural sunlight and under the artificial illumination (i.e. Exo Terra bulb). Multispectral image stacks were generated using MICA toolbox in ImageJ [ 49 ]. Identical col
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