Finding value in complex biological data – integrated ‘omics
Posted on 08/11/2016
Transformative innovations in bioscience will increasingly come from systems approaches, which are critically dependent on new computational technologies, methodologies and resources.
Biology is a data-rich science with studies at cellular and progressively more at sub-cellular level, generating increasingly large volumes of information, yielding unprecedented views of cellular systems. This abundance presents the problem of how to extract value and biological meaning from complex multiple ‘omics data sets (for example, genomics, proteomics or metabolomics).
Transformative innovations in bioscience will increasingly come from systems approaches, which are critically dependent on new computational technologies, methodologies and resources. The scale and complexity of biological data is continually increasing and this places demands on the ability of life-scientists to manage and analyse data. Innovative computational approaches are needed for the integration, analysis and interpretation of new and repurposed biological data. Technologies centred around the integration of ‘omics data could play a crucial role in unlocking challenges in the development, production and regulation of increasingly sophisticated bio-based products and services.
Mathematical modelling is also becoming increasingly important in order to predict behaviour of biological systems and reduce and refine experimental work, as are tools to visualise data for non-technical decision makers.
However, the ability to integrate these elements is currently under-developed and turnkey solution platforms have yet to mature. As a consequence the full potential of innovation investments in biosciences is not being exploited.
We expect SME and micro companies to play a crucial role in developing scalable and internationally competitive technology offerings that can power uptake of data driven biology across emerging and existing technology sectors as well as being major economic growth opportunities themselves.