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Real-Time Text Mining For The Biomedical Literature- A Collaboration Between DiscoveryNet and myGrid

The aim of this focused project proposal is to develop a unified real-time e-Science text-mining infrastructure that leverages the technologies and methods developed by both the Discovery Net and myGrid pilot projects. Both projects have already developed complimentary methods that enable the analysis and mining of information extracted from biomedical text data sources using grid infrastructures, with myGrid developing methods based on linguistic analysis and DiscoveryNet developing methods based on data mining and statistical analysis. In this project we aim to jointly develop a common inter-operability framework between the tools and methods developed within both projects. Whereas existing grid technologies and e-science application integration effort provide generic low level inter-operability framework, our effort in this project will be dedicated to providing high-level integration methods specific to the access, integration and composition of grid-based text mining services. To achieve our goals we will develop a common grid-based text mining framework (data model, meta-data model and API) based on our shared expertise. We will drive our efforts and demonstrate their success through both the use of case studies from our existing end user biologists who use text mining, and through the development of a new gene ontology annotation tool that will be provided as an executable service to the UK e-Sicence community.

Maturity: Initial Research
Region: UK
Type: Pilot
Grant Value: £76,764.00
Start Date: 01/10/2004
End Date: 30/09/2006
Project Status: funded
Funding Agency:

Project Members
Prof Yike Guo

Collaborating Organisations
Imperial College London

Component(s) Project Develops
This project is not associated with any components at present.

Application Area(s) associated with Project
This project is not associated with any application areas at present.


Last Updated: 22 Jun 12 11:02
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