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Computational Strategies for Scalable Genomics Analysis

Year: 2019

Type: article

Abstract: The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications.

Source: Genes

DOI: 10.3390/genes10121017

Authors: Lizhen Shi, Zhong Wang

Institutions: Florida State University, Lawrence Berkeley National Laboratory, University of California, Merced, Joint Genome Institute

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $1,824

OpenAlex ID: W2993246561

FWCI: 0.513

Cites: 54

Cited by: 20

Related to: 10