Entity
  • Portable Genomics, Inc.

    Created in 2013


  • Probably non active (C)
    Several signals show that this company is not active anymore
  • Social networks

    364
  • Activities

  • Technologies

  • Entity types

  • Location

    3210 Merryfield Row, San Diego, CA 92121, USA

    San Diego

    United States of America

  • Employees

    Scale: 2-10

    Estimated: 1

  • Engaged catalyst

    0
    0 0
  • Added in Motherbase

    6 years, 4 months ago
Description
  • Value proposition

    Portable Genomics Inc., La Jolla, CA, was created by Patrick Merel, PhD and a group of molecular biologists from Bordeaux, France, to design a mobile software platform for the use of genome data in personalized, predictive, preventive and participative medicine applications (P4TMMedicine).

    What makes Portable Genomics unique in the genomics space is a consumer-based approach to the visualization of genomic data.

    Portable Genomics platform, and IP, uses the digital music data structure to re-organise a genome data set and allows professionals and consumers to simply browse a genome in any MP3-compatible device from iPodsTM to mobile phones, from iWatchTM to digital TVs. Referred as the Genomics in iTunes Company, Portable Genomics facilitates the access, the understanding and the use of complex genomic data through very simple and very well-known graphical user interfaces.

    Also, Portable Genomics is building a new type of platform to facilitate the aggregation of lifestyle information and health data with genomic results. Our goal is to allow our users to securely share their data through a fair trade data sharing model, to promote a discovery service for IP development, in the genotype to phenotype space.

    Our graphical visualization tool will be at the core of this platform, as well a secure data storage solution and a new concept for the sharing and monetization of data. We are building a next generation of personal health data silo for people to remain the owners of their data, to decide when they want to share or not to share their data, and to associate them with the revenue if their data are being monetized.

    wireless healthcare, genomics, personalized medicine, medical applications, big data, data sharing, data monetization, data mining, genotype to phenotype correlations, and fair trade data sharing

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