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: www.nactem.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
- BioNLP 2024 accepted as workshop at ACL 2024
- Prof. Ananiadou appointed as Senior Area Chair for ACL 2023 and IJCNLP-AACL 2023
- New Knowledge Transfer Partnership with 10BE5
- Chinese Government AwardAward for PhD student Tianlin Zhang
- Advances in Data Science and AI Conference 2023
- Talk at Open Data Science Conference (ODSC)
- BioLaySumm 2023 - Shared Task @ BioNLP 2023
- Junichi Tsujii awarded Order of the Sacred Treasure, Gold Rays with Neck Ribbon