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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
TAG Sequence Identification of Genomic Regions Using TAGdb.
|
|---|---|
| Chapter number | 12 |
| Book title |
Plant Bioinformatics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3167-5_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3166-8, 978-1-4939-3167-5
|
| Authors |
Ruperao, Pradeep, Pradeep Ruperao |
| Editors |
David Edwards |
| Abstract |
Second-generation sequencing (SGS) technology has enabled the sequencing of genomes and identification of genes. However, large complex plant genomes remain particularly difficult for de novo assembly. Access to the vast quantity of raw sequence data may facilitate discoveries; however the volume of this data makes access difficult. This chapter discusses the Web-based tool TAGdb that enables researchers to identify paired read second-generation DNA sequence data that share identity with a submitted query sequence. The identified reads can be used for PCR amplification of genomic regions to identify genes and promoters without the need for genome assembly. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 67% |
| Student > Bachelor | 1 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 3 | 100% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 25 May 2016.
All research outputs
#14,240,471
of 22,831,537 outputs
Outputs from Methods in molecular biology
#4,191
of 13,126 outputs
Outputs of similar age
#205,980
of 393,555 outputs
Outputs of similar age from Methods in molecular biology
#417
of 1,470 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,126 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 64% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,555 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.