We show a quick prototype where Rapid is integrated with the Open Microscopy Environment developed in Dundee (http://www.openmicroscopy.org/) to allow analysis and visualisation of microscopy images on remote compute resources.
This presentation's focus is on the computer science research performed at the National e-Science Centre as part of the University of Edinburg and the University of Glasgow. Another submission reports on the community support offered by the National e-Science Centre.
This paper analyses strategies for research data with a particular emphasis on meeting researchers’ requirements. It identifies a need for innovation, categorises classes of research data and analyses the commonalities and differences in the provisions for researchers in each category. This analysis will identify research, investment and policy opportunities that should economically improve researcher satisfaction and productivity. The paper is being developed incrementally.
Final project report for JISC, with links to all individually created deliverables and progress posts. RapidSeis has produced a scientific gateway via a web portal that allows seismologist to pick up data from Orfeus—the central repository for earthquake data in Europe—and then run several analyses on these data. Advanced users can also create new analyses and share these with all the other users.
In order to maintain and integrate GridQTL with other resources we are requesting two full-time posts, one to be based at NeSC and the other at IEB. The principal tasks for these posts are outlined under the management structure. GridQTL, our existing project upon which GridQTL+ is based, is a collaborative project across three sites. The different expertise from each of these groups has been essential to the development of GridQTL and we wish to continue with this successful arrangement.
We invite the submission of papers related to various aspects of molecular and systems biology and portals. Suggested topics include, but are not limited to:
• Life science data producing methods, such as mass spectrometry
• Life science data processing methods, such as phylogenetic analyses
• Modeling protein-carbohydrate recognition
• Machine learning for computational immunomics