2008年12月23日星期二

Bookmarks From Group Collaboration 12/23/2008

  • [we used]...a new method we named whole-genome shotgun sequencing, which worked by randomly selecting and sequencing DNA fragments from the organism's genome, then computationally reassembling it

    independence has continued to be an essential aspect of my science's progress

    It is not hard to understand why investigators, particularly young scientists, are satisfied being data generators, as government agencies and some foundations continue to pay out hundreds of millions of dollars for just DNA sequencing or, even worse, microarrays, creating huge datasets but seldom any real scientific insight

    I was certain, after all of our success with our new whole-genome shotgun sequencing method, that the Human Genome Project would adopt our methods, but the federal human genome project was bureaucratically moribund and unable to change. In truth there was no incentive to change. The scientists in the various genome centers benefited hugely- some on the order of $100 million per year or more- from a process that was essentially a decentralized, widely distributed public-works project

    data generation without big questions and computational approaches capable of answering them is only of trivial value. My team now has continued to apply the random selection and shotgun sequencing methods as a major discovery engine, exploring environmental research through "metagenomic studies," investigating life in the Sargasso Sea and also in the human gut

    It has recently been argued that the generation of large data sets is the new science. I agree only insofar as the data sets are used to ask and answer unique questions about life. It is clear to me, for example, that the only hope we have for understanding our own biology is to generate thousands of complete human genomes together with well-defined phenotypic data from the same individuals. Such data will reveal much about what is nature and what is nurture in our species. Likewise, extensive metagenomic analysis of the microorganisms associated with each of those individuals.

    Tags: science, big_science, biology, genetics, innovation, technology, business, model, collaboration, biodiversity, evolution, genome-environment_interaction, data

  • gavin.dudeney@theconsultants-e.com

    Tags: no_tag


Posted from Diigo. The rest of Collaboration group favorite links are here.

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