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BBSRC Pumps $9M into Data-driven Bioscience Resources

NEW YORK (GenomeWeb News) – The Biotechnology and Biological Sciences Research Council has awarded £5.5 million ($8.7 million) to fund 10 projects aimed at developing data-driven life sciences research infrastructure, resources, and analytical capabilities at universities and institutes across the UK.

The awards are supported under the Bioinformatics and Biological Resources fund, which seeks to provide resources such as databases, software tools, and libraries, BBSRC said today.

"Developing new tools and techniques to allow us to make the most of the vast amounts of data that bioscience produces is a vital and often underappreciated aspect of research. Projects like these are allowing scientists to make major insights and solve previously intractable puzzles at unprecedented speed," BBSRC Chief Executive Douglas Kell said in a statement.

One of the funded projects, at the University of Dundee, will seek to provide researchers in 140 countries with the tools to take raw sequence data and make predictions about the structure and function of the proteins that they encode, enabling them to better use the "enormous volumes" of DNA data generated by modern sequencing methods.

A project led by the European Bioinformatics Institute (EMBL-EBI) will provide a central repository that will biologists involved in synthetic biology, drug discovery, and other fields to share, browse, and download models through a central website.

The program also will fund a community resource in wheat transformation at the National Institute of Agricultural Botany, BBSRC said.

Other projects include an effort at EMBL-EBI to support a central database of non-coding RNAs; University of London projects, including the Protein Circular Dichroism Data Bank, the DichroWeb Server, and ValiDichro, Data Sharing, Analysis, and Standards Resources for CD Spectroscopy; and a joint effort between the University of Edinburgh and EMBL-EBI to develop a rapid processing pipeline and graph-based visualization for the analysis of next-generation sequencing data.

Also being funded are an Imperial College London project to maintain and extend PHYRE2 for predicting the structure and/or function of a protein and to deliver an internationally-recognized resource for protein models; an EMBL-EBI project called DAS in the data-driven research era; a University of Manchester effort to support an open source software for advanced biochemical modeling; and a University of Edinburgh project focused on the Sprint approach to network biology.

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