Thalia
Thalia (Text mining for Highlighting, Aggregating and Linking Information in Articles) is a semantic search engine that can recognise concepts occurring in biomedical abstracts indexed on Pubmed. It currently recognises eight types of concepts, namely: chemicals, diseases, drugs, genes, metabolites, proteins, species and anatomical entities.
User interface
Thalia is available through a web-based user interface at the following address: http://www.nactem.ac.uk/Thalia_BI/. More information on the system can be obtained by reading the manual or watching a short demonstration video:
API
Thalia can also be queried through a RESTful API. For more information, read the API manual. The queries should be sent to the following address: nactem-copious.man.ac.uk/thalia-wsgi/api
Project Team
Principal Investigator: Sophia AnaniadouResearchers: Axel Soto, Piotr Przybyła
Funding
This work has been supported by BBSRC, Enriching Metabolic PATHwaY models with evidence from the literature (EMPATHY) [Grant ID: BB/M006891/1], and The Manchester Molecular Pathology Innovation Centre (MMPathIC) [Grant ID: MR/N00583X/1].
Publications
- Axel J Soto, Piotr Przybyła and Sophia Ananiadou 2018. Thalia: Semantic search engine for biomedical abstracts. Bioinformatics.
- Piotr Przybyła, Axel J. Soto, and Sophia Ananiadou. 2017. Identifying Personalised Treatments and Clinical Trials for Precision Medicine using Semantic Search with Thalia, In Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2017), Gaithersburg, Maryland, USA.
Featured News
- Prof. Ananiadou gives talk as part of Women in AI speaker series
- Keynote Talk at the Festival of AI
- Prof. Ananiadou appointed as Senior Area Chair for ACL 2023
- Recent funding successes for Prof. Sophia Ananiadou
- New article on using neural architectures to aggregate sequence labels from multiple annnotators
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