The Biotechnology and Biological Sciences Research Council (BBSRC) encourages research that will yield the next generation of new computational technologies, methodologies and resources within our strategic research priorities, as well as more broad bioscience areas.
The complexity and scale of biological data is continually increasing, which places demands on the ability of biologists to manage and analyse data.
Innovative computational approaches are needed for the integration, analysis and interpretation of new and repurposed biological data to enable bioscientists to gain value and scientific leads from the enormous quantities and diversity of data available.
For a project to address the data-driven biology priority, a significant focus of the work must involve the initiation or further development of advanced computational tools, resources or methodologies relevant to our remit.
Projects may develop entirely new applications, employ cutting-edge computational methods to better exploit data resources, or provide innovative functionality and improvements to an existing computational tool or resource.
Under this priority, examples of broad data-driven research challenges that projects might address include:
- integration, interrogation and analysis of large or complex datasets, such as those generated by multiple omics technologies
- investigating links between phenotypic traits and variation in biological systems or processes
- extracting quantitative information from large or complex image sets
- supporting knowledge discovery from biological data – for example, developing platforms for data-sharing and integration, or new data visualisation approaches.
The data-driven biology priority also seeks to encourage exploitation of advanced computing technologies and approaches, for example:
- semantic computing
- high performance computing
- cloud computing
Also within the priority are activities that support the maturation of the biological data landscape, such as:
- the development of community data standards
- ontologies and data management tools
- enhancement and maturation of existing research software.
Data-driven biology complements the technology development priority by providing a focus on the computational tools, resources and methods that are essential to derive maximum value from bioanalytical or biological-based technologies.
Also covered by this priority are projects that combine computational approaches with the development of data-generating bioanalytical or biological technologies – for example, to enhance analysis or automate metadata generation and manipulation.
Proposals in data-driven biology (informatics tools development) should describe how they will fulfil an unmet need, or needs, in the biosciences. It is expected that new informatics tools and resources developed under this priority area will be designed, as much as possible and practical, with end users in mind. Evidence of end-user engagement may be provided in support of applications.
Many of the most exciting advances in biology are likely to occur at the interface with other disciplines through truly multidisciplinary approaches. Proposals involving strong multidisciplinary partnerships between bioscientists and researchers in the physical sciences, engineering and information technology disciplines are therefore particularly welcome.
Projects focused primarily on the use of an existing tool or minor developments of existing tools do not fall within this priority area.
Proposals should comply with our data sharing policy. Proposals developing informatics tools should make such tools available to the wider user and developer community with as few restrictions as possible, ideally using open source best practices, for example Creative Commons or Open Source Initiative recommended licences.
However, we recognise that, at times, the creators’ intellectual property rights may need to be protected before any sharing takes place. Such protection should not unduly delay the release of any data or tools arising from BBSRC funding.