{"id":7695,"date":"2022-06-08T09:04:35","date_gmt":"2022-06-08T09:04:35","guid":{"rendered":"https:\/\/www.booksofall.com\/es\/?post_type=product&#038;p=7695"},"modified":"2022-06-08T09:04:36","modified_gmt":"2022-06-08T09:04:36","slug":"the-briefing-big-data-in-science","status":"publish","type":"product","link":"https:\/\/www.booksofall.com\/es\/the-briefing-big-data-in-science\/","title":{"rendered":"The Briefing: Big data in science"},"content":{"rendered":"<h4 id=\"standfirst\" class=\"article__standfirst\">A lot of research goes into our stories. Here are some of the resources we used to put together our story on how big data is changing science.<\/h4>\n<aside class=\"article__aside\">\n<div class=\"article__aside__section article__share-buttons\" role=\"group\">\n<div class=\"share-buttons\" role=\"group\">\n<div class=\"paragraph paragraph--text\">\n<p>New biomedical techniques, like next-generation genome sequencing, are creating vast amounts of data and transforming the scientific landscape. They\u2019re leading to unimaginable breakthroughs \u2013 but leaving researchers racing to keep up. <a href=\"https:\/\/mosaicscience.com\/story\/how-big-data-changing-science-algorithms-research-genomics\">In this feature for Mosaic<\/a>, Tom Chivers meets the biologists \u2013\u00a0junior and senior \u2013 who are learning to work with algorithms.<\/p>\n<p>If you want to dive deeper into this topic, here\u2019s some further reading. We\u2019ve broken things down into key subtopics, but otherwise these links aren\u2019t listed in any particular order \u2013 so feel free to dip in and out.<\/p>\n<\/div>\n<div class=\"paragraph paragraph--subheading\">\n<h2>Big data in research \u2013 an overview<\/h2>\n<\/div>\n<div class=\"paragraph paragraph--text\">\n<p>Emily Dreyfuss\u2019s article\u00a0<a href=\"https:\/\/www.wired.com\/2017\/03\/biologists-teaching-code-survive\/\">\u2018Want to make it as a biologist? Better learn to code\u2019<\/a>\u00a0reflects on the limitations facing expert researchers who were never taught programming skills.<\/p>\n<p>This\u00a0<a href=\"https:\/\/www.forbes.com\/sites\/gregsatell\/2014\/07\/18\/how-data-will-transform-science\/#4b68b5497c00\">2014\u00a0<em>Forbes\u00a0<\/em>article<\/a>\u00a0anticipates how data might transform science: \u201cIt is as if we are back in the days of Leeuwenhoek, staring into a microscope for the first time and just beginning to understand the possibilities.<\/p>\n<\/div>\n<div class=\"paragraph paragraph--subheading\">\n<h2>Wet and dry labs<\/h2>\n<\/div>\n<div class=\"paragraph paragraph--text\">\n<p><a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5459257\/\">This 2017 study<\/a>\u00a0compares students\u2019 perceptions of wet and dry labs. The results, after comparing two experiments, found that students considered the wet-lab work to be more like \u201creal science\u201d, although they found \u201cmore scientific tasks\u201d to be involved in the database work.<\/p>\n<p>David Heckerman\u2019s 2012 speech\u00a0<a href=\"https:\/\/www.youtube.com\/watch?v=SrFpUHmnt2Y\">\u2018Biology: from wet to dry\u2019<\/a>\u00a0details how biology has progressed from using one-off experiments that generated small amounts of data to having so much data readily available that a hypothesis can be tested without any collaboration with a wet lab whatsoever.<\/p>\n<p>In\u00a0<a href=\"http:\/\/science.sciencemag.org\/content\/349\/6248\/662\">this 2015 interview<\/a>, Sarah Teichmann, who works at the Wellcome Sanger Institute, explains how she combines computational methods with lab experimentation.<\/p>\n<p>In\u00a0<a href=\"https:\/\/mosaicscience.com\/story\/how-big-data-changing-science\">Tom Chivers\u2019s article for Mosaic<\/a>, Professor Gil McVean observes that research labs 15 years ago were typically 90 per cent wet but are today 90 per cent computing. This has resulted in excess empty research space. For instance, the\u00a0<a href=\"https:\/\/www.businessreport.com\/article\/lsu-wet-lab-space-converted-class-office-space\">Greater Baton Rouge Business Report recently announced<\/a>\u00a0that 16,000 square feet of underutilised wet-lab space at Louisiana State University would be sold and converted into office space.<\/p>\n<\/div>\n<div class=\"paragraph paragraph--subheading\">\n<h2>Early criticisms and challenges<\/h2>\n<\/div>\n<div class=\"paragraph paragraph--text\">\n<p>The 2013 article\u00a0<a href=\"https:\/\/www.sciencenews.org\/blog\/context\/why-big-data-bad-science\">\u2018Why big data is bad for science\u2019<\/a>\u00a0claims that big data samples take longer to analyse, with an increased risk of spurious correlations or flukes.<\/p>\n<p><a href=\"https:\/\/academic.oup.com\/bioscience\/article\/58\/8\/747\/381179\">This paper from 2008<\/a>\u00a0explores the difficulties of daily cooperation between wet and dry researchers, in what is dubbed \u201cthe moist zone\u201d.<\/p>\n<p>Timo Hannay, former managing director of Digital Science, claimed in 2014 that the world of research was not doing enough to embrace the power of information. Read the details in his article\u00a0<a href=\"https:\/\/www.wired.com\/insights\/2014\/08\/sciences-big-data-problem\/\">\u2018Science\u2019s big data problem\u2019<\/a>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/aside>\n","protected":false},"excerpt":{"rendered":"<p><iframe style=\"width: 100%; height: 750px; border: none;\" src=\"https:\/\/online.visual-paradigm.com\/share\/book\/the-briefing-big-data-in-science-zbayga2fl?enforceShowPromotionBar=true\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n","protected":false},"featured_media":7700,"template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"Improve your content marketing with flipbooks like this. 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