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    Home > Biochemistry News > Biotechnology News > Science: 215 petabytes of data are stored in 1 g of DNA.

    Science: 215 petabytes of data are stored in 1 g of DNA.

    • Last Update: 2020-09-11
    • Source: Internet
    • Author: User
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    A recent study published in the journal Science surprised us.
    using a mobile video streaming algorithm to demonstrate how to maximize the storage potential of USDD.
    their method was able to store 215 petabytes (1pb, 1024TB) of data in a 1 g of DNA, almost twice the amount of data on Google and Facebook servers.
    figure is 100 times bigger than previously thought.
    addition, the researchers stored an operating system and a movie code in DNA and successfully obtained data from DNA sequences without any errors.
    humans produce 2.5 quiteillion (three times a million squares) of data per day, and that's accelerating.
    ibm estimates that 90 percent of the world's data is now generated in the past two years.
    as more and more digital storage is used in human life, this trend will only continue to grow.
    storage devices are no longer able to meet the demands of huge amounts of data, so people are starting to think about DNA.
    dna is often referred to as the "blueprint of life" for obvious reasons.
    cells in the human body are encoded by a base sequence (A, G, C and T, nucleotide base).
    since James Watson discovered DNA in the 1950s, scientists quickly realized that it could store huge amounts of data in several molecules at high densities.
    addition, DNA can be preserved steadily over a long period of time, and recent studies have recovered DNA from human ancestors 430,000 years ago.
    Erlich and colleagues at the NYGC in New York chose six files to write DNA: a complete operating system, an 1895 film, a $50 Amazon gift card, a computer virus, plaques on board the Vanguard spacecraft, and information scientist Claude Shannon in a 1948 study.
    Yaniv Erlich and Dina Zielinski of the New York Genome Center are compressed into one file and then split into short binary strings.
    researchers used fountain yards to make reading and writing more efficient.
    using this algorithm, they mapped 1 and 0 to nucleotide bases A, G, C and T.
    algorithm is necessary to access data because it corrects and removes combinations of letters that can lead to errors.
    they eventually produced a text file consisting of 72,000 200 base-length DNA strands.
    they sent the document to a San Francisco startup called Twist Bioscience, which converts all digital data into biological data by synthesized DNA.
    two weeks later, Erlich received a small bottle containing DNA, and all the information was encoded inside.
    researchers successfully extracted data using common DNA sequencing tools and a special software that converts bases into binary.
    process went very smoothly and there were no errors in the information.
    Erlich installed the operating system he stored in his DNA with a virtual machine and played mine clearance games.
    believe this is the densest data storage device ever available," Erlich said.
    Erlich didn't stop there.
    and colleagues showed that the encoded data could be copied as many times as anywhere.
    if you want to copy data, you only need to copy DNA through polymerase chain reaction (PCR).
    found that data that has been copied multiple times can also be restored without error.
    but there are some things to note.
    $7,000 to synthesize DNA, and another $2,000 to read the data.
    but thankfully sequencing DNA is getting cheaper and cheaper.
    $2.7 billion to sequence human DNA 15 years ago, but fell to $10 million in 2008.
    in the near future, it will become cheaper and cheaper.
    important thing to mention is that DNA storage is not suitable for normal use.
    you can't replace your hard drive with DNA at home because it takes a few days to read and write.
    but DNA is a good choice for storing the huge amounts of data produced every day.
    that someone might one day invent a very fast coding decoding technique in a molecule, but it still seems very difficult at the moment.
    source: China Biotechnology Network.
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