Chapter title |
Simple Analysis of Deposited Gene Expression Datasets for the Non-Bioinformatician: How to Use GEO for Fibrosis Research
|
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Chapter number | 31 |
Book title |
Fibrosis
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Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-7113-8_31 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7112-1, 978-1-4939-7113-8
|
Authors |
Yang Guo, Richard Townsend, Lam C. Tsoi |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 7 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 2 | 29% |
Researcher | 1 | 14% |
Student > Doctoral Student | 1 | 14% |
Unknown | 3 | 43% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 1 | 14% |
Medicine and Dentistry | 1 | 14% |
Unknown | 5 | 71% |