Intel, Lenovo and BGI Genomics from Shenzhen, China are working together to accelerate the analysis of the genomic characteristics of coronavirus (COOVID-19).
Intel and Lenovo’s life sciences and technology experts will work together to support BGI researchers with big data analysis technologies and IT resources, to advance on the sequencing and analysis of the genomic characteristics of coronavirus.
Intel and Lenovo provide BGI with a large high performance computing cluster to process high-speed readings from the BGI DNBSEQ-T7 sequencer.
BGI Genomics researchers will have access to high-performance computing (HPC) and genomics analysis technologies, resources and skills of Intel and Lenovo, to accelerate their research into the genomic characteristics of the coronavirus.
Technology will help scientists study virulence, transmission patterns and host-pathogenic interactions, which will inform epidemiological and vaccine design studies.
This requires ample basics to create better diagnostic methods and design an effective vaccine or other protective measures, such as immunotherapy.
As a result of this work, BGI will continue to optimize its COVID-19 diagnostic kits. Developed knowledge could be useful in identifying potential goals for developing a vaccine or effective treatment in the future.
The solution is optimized jointly by Intel and Lenovo to accelerate the call workflows of variants of the entire genome and the entire exoma up to 40X1 using the Lenovo (GOAST) genomic optimization and scalability tool, the first solution
This will allow BGI to optimize its IT processes and efficient data processing to generate reliable genomic analysis results faster, reducing scientific and clinical observation times.
For genomic sequencing, 1 ml of body fluid usually contains a swarm of millions of different virions; each virion, in turn, has a genome of about 30,000 bases or ‘letters’ of DNA.
Since BGI is sequencing microbes swarms from many patients with suspected infection, their work will generate petabytes of data. To efficiently process this amount of important data, advanced HPC infrastructure, optimized genomics processing and analysis technologies are needed.