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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Analysis of next-generation sequencing data using galaxy.
|
|---|---|
| Chapter number | 2 |
| Book title |
Stem Cell Transcriptional Networks
|
| Published in |
Methods in molecular biology, January 2014
|
| DOI | 10.1007/978-1-4939-0512-6_2 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-0511-9, 978-1-4939-0512-6
|
| Authors |
Daniel Blankenberg, Jennifer Hillman-Jackson, Blankenberg, Daniel, Hillman-Jackson, Jennifer |
| Abstract |
The extraordinary throughput of next-generation sequencing (NGS) technology is outpacing our ability to analyze and interpret the data. This chapter will focus on practical informatics methods, strategies, and software tools for transforming NGS data into usable information through the use of a web-based platform, Galaxy. The Galaxy interface is explored through several different types of example analyses. Instructions for running one's own Galaxy server on local hardware or on cloud computing resources are provided. Installing new tools into a personal Galaxy instance is also demonstrated. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 33% |
| France | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 77 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 31% |
| Student > Ph. D. Student | 12 | 15% |
| Student > Master | 11 | 14% |
| Student > Bachelor | 8 | 10% |
| Professor > Associate Professor | 4 | 5% |
| Other | 7 | 9% |
| Unknown | 13 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 28% |
| Biochemistry, Genetics and Molecular Biology | 17 | 21% |
| Computer Science | 7 | 9% |
| Medicine and Dentistry | 5 | 6% |
| Immunology and Microbiology | 4 | 5% |
| Other | 9 | 11% |
| Unknown | 16 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 October 2020.
All research outputs
#15,299,919
of 22,754,104 outputs
Outputs from Methods in molecular biology
#5,313
of 13,089 outputs
Outputs of similar age
#190,001
of 305,238 outputs
Outputs of similar age from Methods in molecular biology
#200
of 597 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,089 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 305,238 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 597 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 56% of its contemporaries.