Some will involve the integration of data from different sources, the development of structures of data to enable more efficient querying, the development of better ways of interrogating databases and presenting the information, etc. Other approaches will involve the development of better ways of modelling data, including whole systems. For example, fitting the sequence into a metabolic, regulatory or developmental system so as to aid the design of suitable experiments to evaluate its contribution to the phenotype. These approaches will need to be holistic in nature, taking in as much of the whole picture as possible. This in turn will require the development and application of new systems modelling methods.
Current databases tend to store and present information about single genomes.
However, researchers need to be able to compare and analyse the organisation and evolution of genomes amongst organisms. Such analyses could uncover relationships between model organisms, crops, domestic animals and humans and facilitate the exploitation of synteny. Tools and techniques need to be developed to conduct these analyses, including the development of graphical displays to visualise the results of the comparisons. There are developing areas of Computer Science and IT research which have yet to be confronted with problems of the complexity of biological data. There is a need to investigate the feasibility of such techniques in the biological context and how helpful they are likely to be.