Title |
A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease
|
---|---|
Published in |
BMC Medical Genomics, June 2012
|
DOI | 10.1186/1755-8794-5-28 |
Pubmed ID | |
Authors |
Nalini Raghavachari, Jennifer Barb, Yanqin Yang, Poching Liu, Kimberly Woodhouse, Daniel Levy, Christopher J O‘Donnell, Peter J Munson, Gregory J Kato |
Abstract |
Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 20% |
France | 2 | 20% |
Montenegro | 1 | 10% |
Unknown | 5 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 50% |
Scientists | 5 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 3% |
United States | 3 | 2% |
Denmark | 2 | 1% |
Spain | 2 | 1% |
Austria | 1 | <1% |
Brazil | 1 | <1% |
Czechia | 1 | <1% |
Ukraine | 1 | <1% |
Australia | 1 | <1% |
Other | 4 | 3% |
Unknown | 138 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 49 | 31% |
Student > Ph. D. Student | 39 | 25% |
Student > Master | 14 | 9% |
Other | 10 | 6% |
Student > Bachelor | 9 | 6% |
Other | 21 | 13% |
Unknown | 16 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 73 | 46% |
Biochemistry, Genetics and Molecular Biology | 39 | 25% |
Medicine and Dentistry | 17 | 11% |
Computer Science | 3 | 2% |
Mathematics | 2 | 1% |
Other | 9 | 6% |
Unknown | 15 | 9% |