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elucidata Scaling-up-Computationally-Intensive-Problems

Scaling-up Computationally Intensive Problems

Background and Challenges

Sequencing data are driving key decisions in labs and clinics. By 2025, between 100 million and 2 billion human genomes could be sequenced, generating 2–40 exabytes of data, which exceeds the projected storage needs of Youtube or Twitter. However, using omics data in research and clinical applications require storage, processing, analysis and sharing of large amounts of data. Performing computations on such large datasets can be a major bottleneck in the use of genomic information for making meaningful decisions.
Elucidata is committed to providing solutions that allow labs to easily and efficiently scale up their computational needs. We provide expertise and customized solutions according to specific requirements of our clients.

Example

Company A is interested in finding certain short sequences in a particular genome repetitively and on request by using a web application.
Company A previously performed all computations on a single server, which had limited processing and storage capability. These limitations led to slow processing, delayed results, and memory deadlocks during computations.
Elucidata addressed Company A’s need for computationally intensive analysis on large genomic datasets by creating a customized cloud computing solution. Our custom distributed cloud architecture is economical, faster, and can process a wide range of alignment requests on any genome. The deployment of our solution has led to faster analysis and reduced computational cost for Company A.

References

[1]Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, et al. (2015) Big Data: Astronomical or Genomical? PLoS Biol 13(7): e1002195.

Team

Data Engineer, Project Manager

Delivery

Installation, continuous maintenance, usage and billing reports, presentation

Time Taken

1 month


Inquiry?

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