Changing the Biological Data Visualisation World
News Sep 04, 2015
Existing open-source biological data repositories are littered with abandoned projects that have failed to gain the support needed to continue on past the initial funding and enthusiasm. Therefore, with BioJS, buy-in from the lifesciences community is critical; to present such a suite of tools capable of displaying biological data requires expertise and capacity that is beyond working in isolated groups.
BioJS was initially developed in 2013 through a collaboration between TGAC and the European Bioinformatics Institute (EMBL-EBI). Starting of as a small set of individual graphical components in a bespoke register, it has evolved to a suite of over a 100 data visualisation tools with a combined download of near to 185k. A community of 41 code contributors spread across four continents, a Google Group forum with more than 150 members, and 15 published papers with multiple citations.
To promote the project, TGAC recently held the first BioJS conference as an open event to potential developers and users of the online data repository. Followed by a hackathon to allow participant to integrate the toolset into the larger Galaxy network, an open, web-based platform for data intensive biological research.
Manuel Corpas, BioJS community lead and Project Leader at TGAC, said: BioJS has become a robust international project within a short period of time by fostering the right skills and technical expertise to develop the community. Contributors are rewarded to ensure members are motivated and to increase our impact.
“Time spent on promoting, evangelising and networking is one of the most fruitful investments in the BioJS community. We believe that BioJS will set an example for other to have the confidence to build their similarly robust open source projects and communities.”
Unlike most cells in the rest of our body, the DNA (the genome) in each of our brain cells varies from cell to cell, caused by somatic changes. But much remains unknown, including when these changes arise, their size and locations, and whether they are random or regulated. Now, researchers have developed new techniques allowing the detection of CNVs smaller than one million base pairs.