Novosti iz biotehnologije

Global Bioinformatics Market Projected to Reach USD 9.1 Billion in 2018

Projected to record double-digit growth, the global informatics market will have the highest revenue contribution from the platforms segment.

The global bioinformatics market, estimated at USD 2.3 billion in 2012, is forecasted to reach a market size of USD 9.1 billion in 2018, at a compounded annual growth rate (CAGR) of 25.4% from 2012-2018, according to Transparency Market Research (Albany, NY, USA; www.transparencymarketresearch.com). The market growth is motivated by a rise in applications across a range of industries. The major contribution to the market demand is from fields such as pharmaceutical research and development, agriculture biotechnology, medical and clinical diagnostics, and other life-sciences related industries.


The services market currently holds a comparatively smaller market share; however, it is expected to increase considerably over the forecast period. The bioinformatics platform segment is the fastest growing market and is expected to contribute 54% of the total market growth during the same period.

Research outsourcing by pharmaceutical giants in the fields comprising bioinformatics content is a significant driver of the global bioinformatics market. These companies, in efforts to decrease time and costs on R&D activities involved in the development of new medicines and new applications for existing drugs, are looking for outsourcing services for bioinformatics knowledge and management tools, platforms, and services.

North America holds the largest share among the regional markets; it, however, is forecasted to be superseded by Europe as the leading market shareholder in 2018, because of rapid growth seen by major European markets such as the United Kingdom and Germany. Europe is predicted to be the fastest growing region, with growth chiefly driven by mounting government support for R&D activities in the region. The bioinformatics services market in Europe and North America is well established and organized, while it is still in an early growth phase in emerging markets of Asia Pacific region.




 

ENCODE delivers the data - Major scientific effort inspires a new publishing model

On 5 September, the hundreds of scientists working on the ENCODE project revealed a surprising level of activity in the human genome. The project generated so much new information about gene function that it required a new publishing model in which open-access articles and datasets are interconnected. Just as the Human Genome Project revolutionised biomedical research, ENCODE is driving new understanding and opening new avenues for biomedical science. Led by EMBL-EBI and the National Human Genome Research Institute (NHGRI) in the US, it sets out to create an encyclopedia of DNA elements. Its detailed map of genome function now identifies four million genetic ‘switches’, and provides an essential reference to help researchers pinpoint specific areas of research for human disease. The findings are published in 30 connected, open-access papers appearing in three science journals: Nature, Genome Biology and Genomem Research. Nature also developed an iPad app to help users navigate the data on the go. The ENCODE publications sparked a huge amount of interest, making front-page news in the Guardian, New York Times and Washington Post, headlining on BBC television news in the UK and featuring in thousands of and websites around the world. But for many scientists, one of the most interesting features of the ENCODE publications was an innovation in reporting: a ‘virtual machine’ that allows readers to explore the precise analysis methods themselves. ENCODE combined the efforts of 442 scientists in 32 labs in the UK, US, Spain, Singapore and Japan. They generated and analysed more than 15 terabytes (15 trillion bytes) of raw data – which is publicly available. The study used the equivalent of around 300 years of computer time studying 147 tissue types to determine what turns specific genes on and off, and how that ‘switch’ differs between cell types.