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InChI in the wild: an assessment of InChIKey searching in Google

Overview of attention for article published in Journal of Cheminformatics, February 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#20 of 569)
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

blogs
4 blogs
twitter
20 tweeters
peer_reviews
1 peer review site
video
1 video uploader

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
4 CiteULike
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Title
InChI in the wild: an assessment of InChIKey searching in Google
Published in
Journal of Cheminformatics, February 2013
DOI 10.1186/1758-2946-5-10
Pubmed ID
Authors

Christopher Southan

Abstract

While chemical databases can be queried using the InChI string and InChIKey (IK) the latter was designed for open-web searching. It is becoming increasingly effective for this since more sources enhance crawling of their websites by the Googlebot and consequent IK indexing. Searchers who use Google as an adjunct to database access may be less familiar with the advantages of using the IK as explored in this review. As an example, the IK for atorvastatin retrieves ~200 low-redundancy links from a Google search in 0.3 of a second. These include most major databases and a very low false-positive rate. Results encompass less familiar but potentially useful sources and can be extended to isomer capture by using just the skeleton layer of the IK. Google Advanced Search can be used to filter large result sets. Image searching with the IK is also effective and complementary to open-web queries. Results can be particularly useful for less-common structures as exemplified by a major metabolite of atorvastatin giving only three hits. Testing also demonstrated document-to-document and document-to-database joins via structure matching. The necessary generation of an IK from chemical names can be accomplished using open tools and resources for patents, papers, abstracts or other text sources. Active global sharing of local IK-linked information can be accomplished via surfacing in open laboratory notebooks, blogs, Twitter, figshare and other routes. While information-rich chemistry (e.g. approved drugs) can exhibit swamping and redundancy effects, the much smaller IK result sets for link-poor structures become a transformative first-pass option. The IK indexing has therefore turned Google into a de-facto open global chemical information hub by merging links to most significant sources, including over 50 million PubChem and ChemSpider records. The simplicity, specificity and speed of matching make it a useful option for biologists or others less familiar with chemical searching. However, compared to rigorously maintained major databases, users need to be circumspect about the consistency of Google results and provenance of retrieved links. In addition, community engagement may be necessary to ameliorate possible future degradation of utility.

Twitter Demographics

The data shown below were collected from the profiles of 20 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 4%
Germany 2 4%
United States 1 2%
Canada 1 2%
Unknown 40 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 28%
Student > Ph. D. Student 8 17%
Student > Master 7 15%
Professor > Associate Professor 5 11%
Student > Bachelor 4 9%
Other 9 20%
Readers by discipline Count As %
Chemistry 13 28%
Computer Science 7 15%
Agricultural and Biological Sciences 6 13%
Pharmacology, Toxicology and Pharmaceutical Science 5 11%
Medicine and Dentistry 4 9%
Other 9 20%
Unknown 2 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 25 June 2019.
All research outputs
#504,801
of 14,050,946 outputs
Outputs from Journal of Cheminformatics
#20
of 569 outputs
Outputs of similar age
#7,738
of 244,776 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 3 outputs
Altmetric has tracked 14,050,946 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 569 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done particularly well, scoring higher than 96% 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 244,776 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 96% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them