Scientific Computing is the heartbeat of genomics. In order to integrate and analyse large and complex data sets to achieve a more complete systems-level understanding of biological processes and diseases, a robust scientific computing platform is necessary.
The Scientific Computing Platform started as independent teams with distinct functions. As GIS’ demand for storage and compute grew, the platform evolved into an integrated entity covering the above-mentioned three areas of operations to meet GIS’ scientific computing needs. We are constantly developing way to provide more integrated approaches to meet these needs.
In order to deal with large-scale data generated by research programmes and collaborations at GIS, we utilise our local infrastructure at GIS as well as the National Supercomputing Center and cloud computing. Through the infrastructure built by the Scientific Computing Platform, groups at GIS have contributed to numerous national and international consortia, generating new insights into the role of the genome in human diseases.
Scientific Computing is an essential pillar for nearly all research programmes at GIS. These programmes rely on services provided by the Scientific Computing Collective, ranging from petabytes of long-term data archive to enabling population scale joint variant calling. Reliable and robust scientific computing is critical for GIS to lead and participate in large research programmes and collaborations.
GIS' vision is to be the custodian for Singapore’s Genomic data. This demand requires GIS to acquire new capabilities (e.g. secure, standard compliant data sharing at scale) to drive GIS scientific computing towards a best-in-class platform in Singapore and beyond.
Additionally, the GIS Scientific Computing Platform has acquired many experiences and skills that are unique in Singapore. The platform is arguably the only local entity capable of supporting genomics research and analysis on a petabyte scale.
The GIS Scientific Platform has the potential to partner with industry - specifically hyper-scalers and solution providers. We foresee synergistic outcomes for both GIS and potential industry partners through joint-development initiatives.
Our near-term goal is for a scalable and secure data management system, which manages all of GIS’ scientific data, starting with genotype data. This feeds into our long-term goal for a scalable and secure data vault for all genomic data in Singapore, in order to fulfil GIS’ vision as custodian of Singapore’s Genomic data.
Artificial Intelligence (AI) at GIS
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Computational Tools & Resources