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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Serverless computing in omics data analysis and integration.

Piotr Grzesik1, Dariusz R Augustyn1, Łukasz Wyciślik1

  • 1Silesian University of Technology, Department of Applied Informatics, Gliwice 44-100, Poland.

Briefings in Bioinformatics
|September 10, 2021
PubMed
Summary
This summary is machine-generated.

Serverless computing offers scalable, parallel processing for complex omics data analysis, simplifying cloud infrastructure management. This approach accelerates multi-omics integration, as demonstrated in COVID-19 research.

Keywords:
bioinformaticscloud computingcontainer-as-a-servicefunction-as-a-serviceomics data integrationomics data processingserverless computing

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Multi-omics data analysis demands significant computational resources and complex pipelines.
  • Traditional cloud computing requires manual infrastructure management, posing challenges for researchers.
  • Existing cloud approaches for omics analysis have limitations in scalability and ease of use.

Purpose of the Study:

  • To review serverless computing solutions in bioinformatics.
  • To evaluate the application of serverless paradigms for omics data analysis and integration.
  • To demonstrate the utility of serverless computing for integrative multi-omics analysis, using COVID-19 as a case study.

Main Methods:

  • Review of existing cloud computing models in multi-omics analysis.
  • Introduction and explanation of the serverless computing paradigm.
  • Evaluation of serverless solutions for omics data integration.

Main Results:

  • Serverless computing simplifies cloud infrastructure management for omics analyses.
  • This paradigm offers high scalability and parallel execution without manual intervention.
  • Serverless approaches are applicable to integrative multi-omics data analysis.

Conclusions:

  • Serverless computing is a promising paradigm for efficient and scalable omics data analysis and integration.
  • It addresses limitations of traditional cloud computing by automating infrastructure management.
  • The approach facilitates complex multi-omics research, exemplified by its application in COVID-19 studies.