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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
High Throughput Screening
|
|---|---|
| Chapter number | 12 |
| Book title |
High Throughput Screening
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3673-1_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3671-7, 978-1-4939-3673-1
|
| Authors |
White, E Lucile, Tower, Nichole A, Rasmussen, Lynn, E. Lucile White, Nichole A. Tower, Lynn Rasmussen, White, E. Lucile, Tower, Nichole A. |
| Abstract |
High-throughput screening is a valuable way to identify hit compounds that combined with a robust medicinal chemistry program could lead to the identification of new antibiotics. Here, we discuss our method for screening large compound libraries with virulent Mycobacterium tuberculosis, possibly one of the more difficult bacteria to use because of its slow growth and assignment to Biosafety Level-3 by the CDC and NIH. The principles illuminated here, however, are relevant to the execution of most bacteria high-throughput screens. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 22% |
| Student > Bachelor | 1 | 11% |
| Student > Master | 1 | 11% |
| Researcher | 1 | 11% |
| Student > Postgraduate | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 3 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 2 | 22% |
| Biochemistry, Genetics and Molecular Biology | 2 | 22% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 11% |
| Unknown | 4 | 44% |
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 20 June 2016.
All research outputs
#13,983,915
of 22,877,793 outputs
Outputs from Methods in molecular biology
#3,939
of 13,132 outputs
Outputs of similar age
#199,677
of 393,703 outputs
Outputs of similar age from Methods in molecular biology
#386
of 1,471 outputs
Altmetric has tracked 22,877,793 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,132 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 68% 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 393,703 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,471 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 71% of its contemporaries.