“This is when I start feeling my age,\u201d says Anne Corcoran. She\u2019s a scientist at the Babraham Institute, a human biology research centre in Cambridge, UK. Corcoran leads a group that looks at how our genomes \u2013 the DNA coiled in almost every cell in our bodies \u2013 relate to our immune systems, and specifically to the antibodies we make to defend against infection.<\/p>\n
She is, in her own words, an \u201cold-school biologist\u201d, brought up on the skills of pipettes and Petri dishes and protective goggles, the science of experiments with glassware on benches \u2013 what\u2019s known as \u201cwet lab\u201d work. \u201cI knew what a gene looked like on a gel,\u201d she says, thinking back to her early career.<\/p>\n
These days that skill set is not enough. \u201cWhen I started hiring PhD students 15 years ago, they were entirely wet lab,\u201d Corcoran says. \u201cNow when we recruit them, the first thing we look for is if they can cope with complex bioinformatic analysis.\u201d To be a biologist, nowadays, you need to be a statistician, or even a programmer. You need to be able to work with algorithms.<\/p>\n
An algorithm, essentially, is a set of instructions \u2013 a series of predefined steps. A recipe could be seen as an algorithm, although a more obvious example is a computer program. You take your input (ingredients, numbers, or anything), run it through the algorithm\u2019s steps \u2013 which could be as simple as \u201cadd one to each number\u201d, or as complex as Google\u2019s search algorithm \u2013 and it provides an output: a cake, search results, or perhaps an Excel spreadsheet.<\/p>\n
Researchers like Corcoran need to use algorithms because, in the 17 years since she became a group leader, biology has changed. And the thing that has changed it is the vast \u2013 the overwhelmingly, dizzyingly vast \u2013 flood of data generated by new biomedical techniques, especially\u00a0next-generation sequencing<\/a>.<\/p>\nReference:<\/h4>\n
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