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    Toward the genomic-information society

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    Name:
    456 Takashi Gojobori Toward the Genomic-Information Society _ SpringerLink 2018.7.23.pdf
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    Type
    Conference Paper
    Authors
    Gojobori, Takashi cc
    KAUST Department
    Bioscience Program
    Computational Bioscience Research Center (CBRC)
    Biological and Environmental Sciences and Engineering (BESE) Division
    Date
    2018-07-22
    Online Publication Date
    2018-07-22
    Print Publication Date
    2018
    Permanent link to this record
    http://hdl.handle.net/10754/656534
    
    Metadata
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    Abstract
    In life science, strong needs for big data analysis and its related data-oriented methodologies such as AI (Artificial Intelligence) are acutely increasing in the recent years. These needs are recognized in not only medical sciences but also other disciplines in which genomic information plays a crucial role in understanding phenomena of interest and in conducting their innovative application to practical usages in the society. It eventually leads us to significant implication that our society will have undergone totally new experiences with enormous benefits from various advancements by research and development of genome information. On the basis of such observations, I would like to propose a future vision of our society as a “Genome-Information-Oriented Society (G-Society)” or “Genomic Information Society”.
    Citation
    Gojobori, T. (2018). Toward the Genomic-Information Society. Smart Societies, Infrastructure, Technologies and Applications, 195–196. doi:10.1007/978-3-319-94180-6_19
    Publisher
    Springer Verlag
    Conference/Event name
    1st International Conference on Infrastructure, Technologies and Applications, SCITA 2017
    DOI
    10.1007/978-3-319-94180-6_19
    Additional Links
    http://link.springer.com/10.1007/978-3-319-94180-6_19
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-319-94180-6_19
    Scopus Count
    Collections
    Conference Papers; Biological and Environmental Sciences and Engineering (BESE) Division; Bioscience Program; Computational Bioscience Research Center (CBRC)

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