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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Cheminformatics in the Service of GPCR Drug Discovery
|
|---|---|
| Chapter number | 20 |
| Book title |
Computational Methods for GPCR Drug Discovery
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7465-8_20 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7464-1, 978-1-4939-7465-8
|
| Authors |
Tim James |
| Abstract |
Cheminformatics is a broad discipline covering a wide range of computational approaches, including the characterization of molecular similarity, pattern recognition, and predictive modeling. The unifying theme that these apparently disparate methods have in common is the aim of extracting useable information from the increasing amounts of data that are associated with contemporary drug discovery projects. Both proprietary and publically available data can be exploited to help inform and improve the process of developing novel therapeutic molecules targeting the GPCR family of proteins. |
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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 26% |
| Student > Ph. D. Student | 3 | 16% |
| Student > Master | 2 | 11% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Other | 3 | 16% |
| Unknown | 4 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 16% |
| Chemistry | 3 | 16% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Computer Science | 2 | 11% |
| Agricultural and Biological Sciences | 2 | 11% |
| Other | 2 | 11% |
| Unknown | 5 | 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 02 December 2017.
All research outputs
#15,484,498
of 23,009,818 outputs
Outputs from Methods in molecular biology
#5,388
of 13,157 outputs
Outputs of similar age
#269,746
of 442,310 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,498 outputs
Altmetric has tracked 23,009,818 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 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% 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 442,310 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.