10. Big data in science

10. Big data in science

Big data has recently become an integral part of working in science, with a good understanding of algorithms being an essential trait required of modern day biologists, physicists etc

Not long ago, sequencing an entire genome (determining the order of all 3 billion pairs of DNA letters in the helix) took years. The Human Genome Project, the first completed sequence of an entire human genome, took around 13 years from conception to its completion in 2003, and cost more than £2 billion. Today, next-generation sequencing can do the same thing in 24 hours for not much more than a thousand pounds.

This has completely changed how scientists work. It's not just that they get their hands dirty less often, nor simply that the required skills have changed. It's that the whole process of science – how you come by an idea and test it – has been upended.

This has left a lot of senior scientists needing to understand and supervise techniques that didn't exist when they trained. It's left universities playing catch-up, with many degrees not teaching the skills that modern biologists need. But above all, it's led to ground-breaking scientific discoveries – breakthroughs that simply wouldn't have been possible 20 or even 10 years ago.