Simple analysis of deposited gene expression datasets for the non-bioinformatician: How to use GEO for fibrosis research

2Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In the past decade, high-throughput techniques have facilitated the “-omics” research. Transcriptomic study, for instance, has advanced our understanding on the expression landscape of different human diseases and cellular mechanisms. The National Center for Biotechnology Center (NCBI) initialized Genetic Expression Omnibus (GEO) to promote the sharing of transcriptomic data to facilitate biomedical research. In this chapter, we will illustrate how to use GEO to search and analyze the public available transcriptomic data, and we will provide easy to follow protocol for researchers to data mine the powerful resources in GEO to retrieve relevant information that can be valuable for fibrosis research.

Cite

CITATION STYLE

APA

Guo, Y., Townsend, R., & Tsoi, L. C. (2017). Simple analysis of deposited gene expression datasets for the non-bioinformatician: How to use GEO for fibrosis research. In Methods in Molecular Biology (Vol. 1627, pp. 511–525). Humana Press Inc. https://doi.org/10.1007/978-1-4939-7113-8_31

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free