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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Database Search Engines: Paradigms, Challenges and Solutions
|
|---|---|
| Chapter number | 6 |
| Book title |
Modern Proteomics – Sample Preparation, Analysis and Practical Applications
|
| Published in |
Advances in experimental medicine and biology, December 2016
|
| DOI | 10.1007/978-3-319-41448-5_6 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-941446-1, 978-3-31-941448-5
|
| Authors |
Kenneth Verheggen, Lennart Martens, Frode S. Berven, Harald Barsnes, Marc Vaudel |
| Editors |
Hamid Mirzaei, Martin Carrasco |
| Abstract |
The first step in identifying proteins from mass spectrometry based shotgun proteomics data is to infer peptides from tandem mass spectra, a task generally achieved using database search engines. In this chapter, the basic principles of database search engines are introduced with a focus on open source software, and the use of database search engines is demonstrated using the freely available SearchGUI interface. This chapter also discusses how to tackle general issues related to sequence database searching and shows how to minimize their impact. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 22% |
| Student > Master | 8 | 16% |
| Researcher | 6 | 12% |
| Other | 3 | 6% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 15 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 27% |
| Agricultural and Biological Sciences | 4 | 8% |
| Engineering | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Computer Science | 2 | 4% |
| Other | 7 | 14% |
| Unknown | 20 | 39% |
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 02 October 2017.
All research outputs
#18,493,111
of 22,914,829 outputs
Outputs from Advances in experimental medicine and biology
#3,316
of 4,953 outputs
Outputs of similar age
#309,685
of 420,880 outputs
Outputs of similar age from Advances in experimental medicine and biology
#338
of 500 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 19th percentile – i.e., 19% 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 420,880 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 500 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.