Eolas focuses much of its R&D effort on solutions to very difficult problems in the bioinformatics area -- in the process, creating new technologies that tend to have a far broader applicability.
Some of our current such projects include:
SAGA proposes a different approach to study gene expression and other biological activity that will allow such data to be precisely localized in order to be used to create, for example, 3-D mappings of gene expression activity against a background of the actual tissue structure where the expression activity is taking place. This approach has the potential to solve several data processing and management problems that researchers are facing in trying to analyze massive data sets and provide a competitive advantage to researchers in developing diagnostic tools and identifying treatment protocols.
Neognos seeks to provide for the first time a secure, collaborative work environment that allows biomedical researchers to collect, collate, analyze, store, share, discuss and present information and to coordinate both internal and external software resources using a dynamic information flow model. In the sense that a spreadsheet dynamically flows information as it recalculates, in order to propagate data changes across cells and across linked spreadsheets, imagine if your applications could do the same sort of thing, propagating data changes and new information seamlessly across applications on your desktop and among collaborating users' applications across the network, regardless of the platform being used, whether it be a desktop, laptop or smart phone. That is what Neognos will enable.
The Oligonucleotide Distributed Information Network (ODIN) seeks to provide a bioinformatics computing platform for the data processing, management, and analysis of gene expression data. Although we are addressing a single very specific application area with our initial design, our plan is to build a system that will be able to be easily adapted for more general use in the future. This system will represent new approach to grid computing. It will be designed as a volunteer grid system, but highly structured in its organization. It will be dynamically reconfigurable, borrowing concepts from mesh networks. Because we intend to build the ODIN system using tools that provide seamless portability across a wide array of hardware platforms, the final system will require a minimum of fixed infrastructure. Combining the ease of running the node software on a wide array of inexpensive hardware with an economic model to provide financial incentives for providing host machines, and a system architecture that allows self-propagating growth and organization of the network, we intend the ODIN system to have the capability to expand the horizons of grid computing far beyond their current limitations.
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