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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://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 Ananiadou
Researchers: 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.