twa: The World Avatar Python package for dynamic knowledge graphs and its application in reticular chemistry
The open-source Python package ‘twa’ streamlines knowledge-graph-driven chemical data integration and workflow automation, unifying fragmented data and expanding the OntoMOPs knowledge graph with 799 new MOPs. It is available via ‘pip install twa’.
Authors
- Jiaru Bai (ORCID: https://orcid.org/0000-0002-1246-1993)
- Xinhong Deng
- George Brownbridge (ORCID: https://orcid.org/0000-0002-9054-0558)
- Aleksandar Kondinski (ORCID: https://orcid.org/0000-0002-0559-0172)
- Sebastian Mosbach (ORCID: https://orcid.org/0000-0001-7018-9433)
- Markus Kraft (ORCID: https://orcid.org/0000-0002-4293-8924)
- Jethro Akroyd (ORCID: https://orcid.org/0000-0002-2143-8656)
- Simon D. Rihm (ORCID: https://orcid.org/0000-0001-8342-7269)
- Fabio Saluzf
Institutions
- University of Cambridge (GB)
- Graz University of Technology (AT)
- The Cambridge Centre for Advanced Research and Education in Singapore (SG)
- CMCL Innovations (United Kingdom) (GB)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00069f
- Citations
- 6
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 4.84
Funders
- National Research Foundation