Big data challenges in genomics

Hongyan Xu

doi:10.1016/bs.host.2019.08.002

Big data challenges in genomics

Hongyan Xu

Research output: Chapter in Book/Report/Conference proceeding › Chapter

4 Scopus citations

Abstract

With the recent development in biotechnology, especially next-generation sequencing in genomics, there is an explosion of genomic data generated. The data are big in terms of both volume and diversity. The big data contain much more information and also pose unprecedented challenges in data analysis. In this article, we discuss the big data challenges and opportunities in genomics research. We also discuss possible solutions for these challenges, which can serve as the basis for future research.

Original language	English (US)
Title of host publication	Handbook of Statistics
Publisher	Elsevier B.V.
DOIs	https://doi.org/10.1016/bs.host.2019.08.002
State	Accepted/In press - Jan 1 2019

Publication series

Name	Handbook of Statistics
ISSN (Print)	0169-7161

Keywords

Bioinformatics
Computational biology
Data volume
Disease genomics
Human genomics
Machine learning
Next-generation sequencing
RNA-Seq

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
Applied Mathematics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/bs.host.2019.08.002

Cite this

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title = "Big data challenges in genomics",

abstract = "With the recent development in biotechnology, especially next-generation sequencing in genomics, there is an explosion of genomic data generated. The data are big in terms of both volume and diversity. The big data contain much more information and also pose unprecedented challenges in data analysis. In this article, we discuss the big data challenges and opportunities in genomics research. We also discuss possible solutions for these challenges, which can serve as the basis for future research.",

keywords = "Bioinformatics, Computational biology, Data volume, Disease genomics, Human genomics, Machine learning, Next-generation sequencing, RNA-Seq",

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AB - With the recent development in biotechnology, especially next-generation sequencing in genomics, there is an explosion of genomic data generated. The data are big in terms of both volume and diversity. The big data contain much more information and also pose unprecedented challenges in data analysis. In this article, we discuss the big data challenges and opportunities in genomics research. We also discuss possible solutions for these challenges, which can serve as the basis for future research.

KW - Bioinformatics

KW - Computational biology

KW - Data volume

KW - Disease genomics

KW - Human genomics

KW - Machine learning

KW - Next-generation sequencing

KW - RNA-Seq

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DO - 10.1016/bs.host.2019.08.002

M3 - Chapter

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T3 - Handbook of Statistics

BT - Handbook of Statistics

PB - Elsevier B.V.

ER -

Big data challenges in genomics

Abstract

Publication series

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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