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The research informatics group is an inter-disciplinary team who apply innovative computer science techniques to solve cutting edge systems biology challenges. The group uses the expertise of both academic researchers and computing professionals to develop the flexible software solutions that are required to enable systems biology investigations. The mixture of skills within the group allows for the development of creative solutions to problems that current software and methodologies are unable to solve. The group uses commercial software management practices to ensure the systems are robust and maintainable, and academic research experience to develop the appropriate adaptive systems for the integration and analysis of scientific data.
We are always interested in hearing from talented computing professionals who wish to apply their expertise in a research environment, and from researchers who wish to apply professional software practices to their work.
If you are interested in finding out more about the group, or are interested in working within the group then please contact us at: informaticscore [at] systemsbiology.org.
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| The Research Informatics group collaborates with the high throughput instrumentation facilities (Proteomics, Genomics, Microfluidics and Imaging) at the Institute for Systems Biology to ensure that the data that is generated can be used by scientists in a flexible and non constrained manner. The group works within the Computational Biology group to ensure that analysis tools can be rapid developed and deployed for use by both bench scientists and computational biologists. |
Strategy
The group builds adaptive solutions that are designed to work within the rapidly changing world of biomedical research. At the ISB there exist a large number of multi disciplinary teams of scientists, who are using state of the art high throughput technologies to investigate integrated systems approaches to the life sciences. The informatics group provides the solutions that these scientists require by:
- Using an enterprise software system to support the large scale data processing of high throughput experiments and the integration of semantically rich heterogeneous data. By adopting standardized componentized enterprise architecture, 3rd party solutions can be used which saves on development time and ensures that the system is reliable. To support the plethora of tools and languages that are used within a research environment, we deliver data and analysis tools using suitable interoperable mechanisms.
- Using appropriate computing technologies, generally chosen from various open-source projects. These solutions are used in innovative ways to solve specific problems, and if required we extend the solutions to ensure their usefulness to the research community. Such adoption means that we are able to build robust standardized systems quickly, and are not continually repeating work already done by others. The systems we adopt are chosen for their flexibility, and include state machines, application servers, content repositories, and registry and resolution services.
- Using modern programming practices and techniques to ensure that the systems we build are adaptable. We develop systems through which different facets of scientific data can be dynamically explored, and so do not rely on the development of restrictive data models. We believe that the modeling of scientific information, and the use of associated top-down development practices, is highly unsuitable for research. Instead of using formal modeling methodologies, techniques designed to allow for the ready adaption of code to new and unspecified usages have been adopted (e.g. based upon late and dynamic binding, data abstraction, content based-models, and the scripting of top-down structures on bottom-up solutions).
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