| Title |
Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing
|
|---|---|
| Published in |
Genome Biology, September 2003
|
| DOI | 10.1186/gb-2003-4-10-r66 |
| Pubmed ID | |
| Authors |
John Castle, Phil Garrett-Engele, Christopher D Armour, Sven J Duenwald, Patrick M Loerch, Michael R Meyer, Eric E Schadt, Roland Stoughton, Mark L Parrish, Daniel D Shoemaker, Jason M Johnson |
| Abstract |
Microarrays offer a high-resolution means for monitoring pre-mRNA splicing on a genomic scale. We have developed a novel, unbiased amplification protocol that permits labeling of entire transcripts. Also, hybridization conditions, probe characteristics, and analysis algorithms were optimized for detection of exons, exon-intron edges, and exon junctions. These optimized protocols can be used to detect small variations and isoform mixtures, map the tissue specificity of known human alternative isoforms, and provide a robust, scalable platform for high-throughput discovery of alternative splicing. |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 6% |
| United Kingdom | 2 | 4% |
| Portugal | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 43 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 36% |
| Student > Ph. D. Student | 7 | 14% |
| Professor > Associate Professor | 5 | 10% |
| Student > Doctoral Student | 3 | 6% |
| Student > Bachelor | 3 | 6% |
| Other | 11 | 22% |
| Unknown | 3 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 64% |
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Medicine and Dentistry | 3 | 6% |
| Computer Science | 2 | 4% |
| Mathematics | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2017.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Genome Biology
#3,489
of 4,467 outputs
Outputs of similar age
#19,613
of 55,966 outputs
Outputs of similar age from Genome Biology
#14
of 23 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.