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MONA – Interactive manipulation of molecule collections

Overview of attention for article published in Journal of Cheminformatics, August 2013
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2 X users
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1 Google+ user

Citations

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55 Mendeley
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Title
MONA – Interactive manipulation of molecule collections
Published in
Journal of Cheminformatics, August 2013
DOI 10.1186/1758-2946-5-38
Pubmed ID
Authors

Matthias Hilbig, Sascha Urbaczek, Inken Groth, Stefan Heuser, Matthias Rarey

Abstract

: Working with small-molecule datasets is a routine task for cheminformaticians and chemists. The analysis and comparison of vendor catalogues and the compilation of promising candidates as starting points for screening campaigns are but a few very common applications. The workflows applied for this purpose usually consist of multiple basic cheminformatics tasks such as checking for duplicates or filtering by physico-chemical properties. Pipelining tools allow to create and change such workflows without much effort, but usually do not support interventions once the pipeline has been started. In many contexts, however, the best suited workflow is not known in advance, thus making it necessary to take the results of the previous steps into consideration before proceeding.To support intuition-driven processing of compound collections, we developed MONA, an interactive tool that has been designed to prepare and visualize large small-molecule datasets. Using an SQL database common cheminformatics tasks such as analysis and filtering can be performed interactively with various methods for visual support. Great care was taken in creating a simple, intuitive user interface which can be instantly used without any setup steps. MONA combines the interactivity of molecule database systems with the simplicity of pipelining tools, thus enabling the case-to-case application of chemistry expert knowledge. The current version is available free of charge for academic use and can be downloaded at http://www.zbh.uni-hamburg.de/mona.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 25%
Researcher 11 20%
Student > Bachelor 6 11%
Student > Master 4 7%
Student > Doctoral Student 3 5%
Other 7 13%
Unknown 10 18%
Readers by discipline Count As %
Chemistry 15 27%
Computer Science 10 18%
Pharmacology, Toxicology and Pharmaceutical Science 5 9%
Biochemistry, Genetics and Molecular Biology 4 7%
Agricultural and Biological Sciences 3 5%
Other 7 13%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 October 2013.
All research outputs
#12,688,753
of 22,719,618 outputs
Outputs from Journal of Cheminformatics
#605
of 828 outputs
Outputs of similar age
#99,621
of 200,084 outputs
Outputs of similar age from Journal of Cheminformatics
#7
of 8 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 828 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 25th percentile – i.e., 25% 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 200,084 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.