NaCTeM Service Systems
If one of the services does not appear to be working, please check our Service Status and scheduled maintenance page before contacing us to report an error.
- TerMine
Term management system.
- Web Demonstration: integrated system for lightweight uses
- Batch Service: for processing documents larger than 2MB (request access)
- SOAP Service: for integrating TerMine with your applications (request access)
- TerMine Plugin for Protégé: access TerMine from within Protégé to help populate your OWL ontologies (request access)
- AcroMine
Find distinct expanded forms of acronyms from Medline. - AcroMine Disambiguator: Disambiguate abbreviations in text with their correct full forms.
- Kleio – an advanced information retrieval system providing knowledge enriched searching for biomedicine.
- Clinical Trial Protocols (ASCOT) – An efficient search application customised for clinical trials.
- EUPMC Evidence Finder – Searching for facts in full text articles.
- New! - EUPMC Evidence Finder for Anantomical entities with meta-knowledge – Searching for facts relating to anatomical entities in full text articles. Facts can be filtered according to various aspects of their interpretation (e.g., negation, certainly level, novelty)
- FACTA+ – a MEDLINE search engine for finding associations between biomedical concepts.
- FACTA+ Visualizer – helps intuitive understanding of FACTA+ search results through graphical visualization of the search results.
- History of Medicine (HOM) – A semantic search system over historical medical archives
- RobotAnalyst — A tool to minimise the human workload involved in the study identification phase of systematic reviews.
- Thalia — A semantic search engine for Pubmed abstracts.
Other Services
- MEDIE
An intelligent search engine, retrieving biomedical events from Medline. Medie is based on the analysis of Enju which performs deep parsing of biomedical text.- If you download and use this Web Service, please let us know by email and cite the paper: Miyao, Yusuke, Tomoko Ohta, Katsuya Masuda, Yoshimasa Tsuruoka, Kazuhiro Yoshida, Takashi Ninomiya and Jun'ichi Tsujii (2006) Semantic Retrieval for the Accurate Identification of Relational Concepts in Massive Textbases. In the Proceedings of COLING-ACL 2006. Sydney, Australia, pp. 1017--1024.
- Info-Pubmed
Helps biologists to understand complex networks of protein-protein interactions. It lists the proteins which interact with a given protein. It uses a dictionary with 200,000 gene/protein names and deep-parse results of all sentences in Medline [user guide] - Firefox required
Help using NaCTeM services
- Help: nactem@manchester.ac.uk
- Request access to NaCTeM services
- Service Status and scheduled maintenance
Feedback
If you have used TerMine or AcroMine, please complete a questionnaire to tell us how useful you found the service. Your feedback is important as it helps us to improve our services to better meet the needs of the community.
Featured News
- Vacancy for Research Fellow in Natural Language Processing
- Keynote speaker at APBC2021
- BioNLP 2021 - First call for papers
- Outstanding paper designation for NaCTeM paper at Coling 2020
- New article in BMJ Open examining change over time of women’s health in clinical studies
- CfP: Special issue on Semantic Resources and Text Mining
- New article describing neural nested event extraction model
- New article describing syntactically-informed word representations