The current status and challenges in computational analysis of genomic big data

Yiming Qin, Hari Krishna Yalamanchili, Jing Qin, Bin Yan, Junwen Wang

Research output: Contribution to journalReview articlepeer-review

24 Scopus citations

Abstract

DNA, RNA and protein are three major kinds of biological macromolecules with up to billions of basic elements in such biological organisms as human or mouse. They function at molecular, cellular and organismal levels individually and interactively. Traditional assays on such macromolecules are largely experimentally based, which are usually time consuming and laborious. In the past few years, high-throughput technologies, such as microarray and next-generation sequencing (NGS), were developed. Consequently, large genomic datasets are being generated and computational tools to analyzing these data are in urgent demand. This paper reviews several state-of-the-art high-throughput methodologies, representative projects, available databases and bioinformatics tools at different molecular levels. Finally, challenges and perspectives in processing genomic big data are discussed.

Original languageEnglish (US)
Pages (from-to)12-18
Number of pages7
JournalBig Data Research
Volume2
Issue number1
DOIs
StatePublished - Mar 1 2015

Keywords

  • Gene regulatory networks
  • Genomic big data
  • Integrative data analysis
  • Next generation sequencing
  • OMICS

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Science Applications
  • Information Systems and Management

Fingerprint Dive into the research topics of 'The current status and challenges in computational analysis of genomic big data'. Together they form a unique fingerprint.

Cite this