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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ChemDes: an integrated web-based platform for molecular descriptor and fingerprint computation
|
|---|---|
| Published in |
Journal of Cheminformatics, December 2015
|
| DOI | 10.1186/s13321-015-0109-z |
| Pubmed ID | |
| Authors |
Jie Dong, Dong-Sheng Cao, Hong-Yu Miao, Shao Liu, Bai-Chuan Deng, Yong-Huan Yun, Ning-Ning Wang, Ai-Ping Lu, Wen-Bin Zeng, Alex F. Chen |
| Abstract |
Molecular descriptors and fingerprints have been routinely used in QSAR/SAR analysis, virtual drug screening, compound search/ranking, drug ADME/T prediction and other drug discovery processes. Since the calculation of such quantitative representations of molecules may require substantial computational skills and efforts, several tools have been previously developed to make an attempt to ease the process. However, there are still several hurdles for users to overcome to fully harness the power of these tools. First, most of the tools are distributed as standalone software or packages that require necessary configuration or programming efforts of users. Second, many of the tools can only calculate a subset of molecular descriptors, and the results from multiple tools need to be manually merged to generate a comprehensive set of descriptors. Third, some packages only provide application programming interfaces and are implemented in different computer languages, which pose additional challenges to the integration of these tools. A freely available web-based platform, named ChemDes, is developed in this study. It integrates multiple state-of-the-art packages (i.e., Pybel, CDK, RDKit, BlueDesc, Chemopy, PaDEL and jCompoundMapper) for computing molecular descriptors and fingerprints. ChemDes not only provides friendly web interfaces to relieve users from burdensome programming work, but also offers three useful and convenient auxiliary tools for format converting, MOPAC optimization and fingerprint similarity calculation. Currently, ChemDes has the capability of computing 3679 molecular descriptors and 59 types of molecular fingerprints. ChemDes provides users an integrated and friendly tool to calculate various molecular descriptors and fingerprints. It is freely available at http://www.scbdd.com/chemdes. The source code of the project is also available as a supplementary file. Graphical abstract:An overview of ChemDes. A platform for computing various molecular descriptors and fingerprints. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 17% |
| Venezuela, Bolivarian Republic of | 1 | 17% |
| Japan | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 278 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | <1% |
| Spain | 1 | <1% |
| Germany | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 274 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 49 | 18% |
| Researcher | 39 | 14% |
| Student > Master | 38 | 14% |
| Student > Bachelor | 25 | 9% |
| Student > Doctoral Student | 15 | 5% |
| Other | 35 | 13% |
| Unknown | 77 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 46 | 17% |
| Biochemistry, Genetics and Molecular Biology | 30 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 26 | 9% |
| Agricultural and Biological Sciences | 15 | 5% |
| Computer Science | 15 | 5% |
| Other | 48 | 17% |
| Unknown | 98 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 11 January 2016.
All research outputs
#6,689,767
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#550
of 891 outputs
Outputs of similar age
#100,971
of 397,533 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 13 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 38th percentile – i.e., 38% 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 397,533 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.