Development of Data Evaluation Supporting System for Large-Scale Experimental Results

With recent advancements of both biological and computer technologies, large-scale experiments are on the point of being undertaken. However, it is unlikely that the experiments will be sufficient to replace traditional studies where a single molecule is examined. For instance, several methods attempt to reconstruct a gene regulatory network from expression measurement data do not explore the prior biological knowledge at all by the limitation of the precision. The use of the available biological knowledge would be essential for the evaluation of the experimental data. Unfortunately, the volume of the data is too large for biological researchers to entirely evaluate them. An effective way is required. We propose a system that can aid the work by visualizing the experimental results and the related biological knowledge and/or the experimental results derived from similar experiments performed by other researchers. With use of the system, users can intuitively confirm which experimental results has been observed or supported by the prior biological knowledge. We show that the system effectively aid the evaluation of the results of large-scale yeast two hybrid screens [2].