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Genome Data Interpretation: How to Ease the Bottleneck

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Bloomberg BNA Business' “Diagnostic Testing & Emerging Technologies” highlights how NextCODE is providing a qualitatively different way to store and analyze genomic information to meet growing opportunities in personalized medicine.

Veröffentlicht in: Gesundheit & Medizin
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Genome Data Interpretation: How to Ease the Bottleneck

  1. 1. Genome Data Interpreta-on: How to Ease the Bo5leneck Hannes Smarason Genome Sequencing |Personalized Medicine | Transforming Health Care
  2. 2. Breaking the Data “Bo5leneck” While various systems have been established in recent years to store the large amounts of genomic data from pa>ents’ DNA, a remaining obstacle is to “break the boFleneck” so that researchers can process the vast data in mul>ple human genomes in order to iden>fy and isolate a small, useful piece of informa>on about disease.
  3. 3. Breaking the Data “Bo5leneck” • Conven>onal databases and algorithms have not been able to efficiently and reliably iden>fy subset informa>on among the millions of gene>c markers in order to inform clinical decisions. This has become a major data management roadblock. • The key is to find new approaches for databases and algorithms that accommodate the unique ways that genomic informa>on is analyzed and interpreted.
  4. 4. Improving the Efficiency of Storage and Analysis As discussed in Bloomberg BNA, Diagnos>c Tes>ng & Emerging Technologies, NextCODE is already easing this boFleneck by providing a qualita>vely different way to store and analyze genomic informa>on and apply it to meet the growing opportuni>es for personalized medicine.
  5. 5. Efficient Database Organiza-on • NextCODE’s Genomically Ordered Rela>onal (or GOR) database infrastructure is a truly different way of storing this huge amount of data. The principle is very simple: – Rather than store sequence and reference data in vast unwieldy files, it >es data directly to its specific genomic posi>on. – As a result, the algorithms are vastly more efficient compared to a tradi>onal rela>onal database because they can isolate by loca>on in the genome. • That makes analysis faster, more powerful and radically more efficient, both in terms of clinicians’ and researchers’ >me, as well as computer infrastructure, I/O and CPU usage.
  6. 6. Holis-c Approach, Broad Applicability This holis>c approach applies broadly to the priori>es of genome scien>sts around the world, helping them eliminate the data management boFleneck to iden>fy more culprits to many inherited diseases, more quickly and cost effec>vely. Read more about NextCODE’s work here.