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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
UniProt Protein Knowledgebase
|
|---|---|
| Chapter number | 2 |
| Book title |
Protein Bioinformatics
|
| Published in |
Methods in molecular biology, February 2017
|
| DOI | 10.1007/978-1-4939-6783-4_2 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6781-0, 978-1-4939-6783-4
|
| Authors |
Sangya Pundir, Maria J. Martin, Claire O’Donovan |
| Editors |
Cathy H. Wu, Cecilia N. Arighi, Karen E. Ross |
| Abstract |
The Universal Protein Resource (UniProt) is a freely available comprehensive resource for protein sequence and annotation data. UniProt is a collaboration between the European Bioinformatics Institute (EMBL-EBI), the Swiss Institute of Bioinformatics (SIB), and the Protein Information Resource (PIR). Across the three institutes more than 100 people are involved through different tasks such as expert curation, software development, and support.This chapter introduces the functionality and data provided by UniProt. It describes example use cases for which you might come to UniProt and the methods to help you achieve your goals. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 155 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 26 | 17% |
| Student > Ph. D. Student | 25 | 16% |
| Student > Master | 19 | 12% |
| Researcher | 16 | 10% |
| Professor | 6 | 4% |
| Other | 28 | 18% |
| Unknown | 35 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 44 | 28% |
| Agricultural and Biological Sciences | 18 | 12% |
| Computer Science | 14 | 9% |
| Chemistry | 8 | 5% |
| Engineering | 6 | 4% |
| Other | 24 | 15% |
| Unknown | 41 | 26% |
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 27 February 2018.
All research outputs
#20,402,251
of 22,952,268 outputs
Outputs from Methods in molecular biology
#9,921
of 13,137 outputs
Outputs of similar age
#356,014
of 420,286 outputs
Outputs of similar age from Methods in molecular biology
#919
of 1,176 outputs
Altmetric has tracked 22,952,268 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,137 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 420,286 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,176 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.