ChemRecon: a Consolidated Meta-Database Platform for Biochemical Data Integration
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910020894982144 |
|---|---|
| author | Eriksen, Casper Asbjørn Andersen, Jakob Lykke Fagerberg, Rolf Merkle, Daniel |
| author_facet | Eriksen, Casper Asbjørn Andersen, Jakob Lykke Fagerberg, Rolf Merkle, Daniel |
| contents | In this paper, we present ChemRecon, a meta-database and Python interface for integrating and exploring biochemical data across multiple heterogeneous resources by consolidating compounds, reactions, enzymes, molecular structures, and atom-to-atom maps from several major databases into a single, consistent ontology. ChemRecon enables unified querying, cross-database analysis, and the construction of graph-based representations of sets of related database entries by the traversal of inter-database connections. This facilitates information extraction which is impossible within any single database, including deriving consensus information from conflicting sources, of which identifying the most probable molecular structure associated with a given compound is just one example. The Python interface is available via pip from the Python Package Index (https://pypi.org/project/chemrecon/). ChemRecon is open-source and the source code is hosted at GitLab (https://gitlab.com/casbjorn/chemrecon). Documentation and additional information is available at https://chemrecon.org. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_12310 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ChemRecon: a Consolidated Meta-Database Platform for Biochemical Data Integration Eriksen, Casper Asbjørn Andersen, Jakob Lykke Fagerberg, Rolf Merkle, Daniel Quantitative Methods In this paper, we present ChemRecon, a meta-database and Python interface for integrating and exploring biochemical data across multiple heterogeneous resources by consolidating compounds, reactions, enzymes, molecular structures, and atom-to-atom maps from several major databases into a single, consistent ontology. ChemRecon enables unified querying, cross-database analysis, and the construction of graph-based representations of sets of related database entries by the traversal of inter-database connections. This facilitates information extraction which is impossible within any single database, including deriving consensus information from conflicting sources, of which identifying the most probable molecular structure associated with a given compound is just one example. The Python interface is available via pip from the Python Package Index (https://pypi.org/project/chemrecon/). ChemRecon is open-source and the source code is hosted at GitLab (https://gitlab.com/casbjorn/chemrecon). Documentation and additional information is available at https://chemrecon.org. |
| title | ChemRecon: a Consolidated Meta-Database Platform for Biochemical Data Integration |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2602.12310 |