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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles
|
|---|---|
| Published in |
Journal of Cheminformatics, November 2016
|
| DOI | 10.1186/s13321-016-0179-6 |
| Pubmed ID | |
| Authors |
Samuel Lampa, Jonathan Alvarsson, Ola Spjuth |
| Abstract |
Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. With large-scale data or when using computationally demanding modelling methods, e-infrastructures such as high-performance or cloud computing are required, adding to the existing challenges of fault-tolerant automation. Workflow management systems can aid in many of these challenges, but the currently available systems are lacking in the functionality needed to enable agile and flexible predictive modelling. We here present an approach inspired by elements of the flow-based programming paradigm, implemented as an extension of the Luigi system which we name SciLuigi. We also discuss the experiences from using the approach when modelling a large set of biochemical interactions using a shared computer cluster.Graphical abstract. |
X Demographics
The data shown below were collected from the profiles of 27 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 | 3 | 11% |
| South Africa | 2 | 7% |
| Canada | 2 | 7% |
| Sweden | 2 | 7% |
| Germany | 2 | 7% |
| United States | 2 | 7% |
| Thailand | 1 | 4% |
| India | 1 | 4% |
| Spain | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 10 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 56% |
| Scientists | 11 | 41% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 1% |
| Unknown | 81 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 22% |
| Student > Master | 16 | 20% |
| Student > Ph. D. Student | 15 | 18% |
| Student > Bachelor | 10 | 12% |
| Student > Doctoral Student | 2 | 2% |
| Other | 8 | 10% |
| Unknown | 13 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 21 | 26% |
| Agricultural and Biological Sciences | 10 | 12% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Chemistry | 6 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 6% |
| Other | 18 | 22% |
| Unknown | 15 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 08 July 2020.
All research outputs
#1,297,383
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#64
of 934 outputs
Outputs of similar age
#26,283
of 426,426 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 23 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done particularly well, scoring higher than 93% 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 426,426 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.