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RESEARCH PRODUCT
Next-generation sequencing: big data meets high performance computing
Andreas HildebrandtBertil Schmidtsubject
0301 basic medicineComputer scienceDistributed computingGenomic researchBig dataTerabyteComputing MethodologiesDNA sequencing03 medical and health sciences0302 clinical medicineDatabases GeneticDrug DiscoveryHumansThroughput (business)PharmacologyGenomebusiness.industryHigh-Throughput Nucleotide SequencingGenomicsSequence Analysis DNAPrecision medicineSupercomputerData scienceCancer treatment030104 developmental biology030220 oncology & carcinogenesisbusinessAlgorithmsdescription
The progress of next-generation sequencing has a major impact on medical and genomic research. This high-throughput technology can now produce billions of short DNA or RNA fragments in excess of a few terabytes of data in a single run. This leads to massive datasets used by a wide range of applications including personalized cancer treatment and precision medicine. In addition to the hugely increased throughput, the cost of using high-throughput technologies has been dramatically decreasing. A low sequencing cost of around US$1000 per genome has now rendered large population-scale projects feasible. However, to make effective use of the produced data, the design of big data algorithms and their efficient implementation on modern high performance computing systems is required.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-04-01 | Drug Discovery Today |