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Updated: Dec 5, 2025
05:34
Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
Published on: June 6, 2025
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Converging Interests: Chemoinformatics, History, and Bibliometrics
Wenxi Zhao1, Dmitriy Korobskiy1, Shreya Chandrasekharan1
1Netelabs, NET ESolutions Corporation, McLean, Virginia 22102, United States.
Journal of Chemical Information and Modeling
|October 15, 2020
Summary
Scientometric analysis of 181 million articles reveals trends in computational chemistry knowledge accumulation. This quantitative approach complements traditional research reviews.
Area of Science:
- Computational Chemistry
- Bibliometrics
- Scientometrics
Background:
- Qualitative methods are traditional for tracking scientific knowledge.
- Quantitative scientometric techniques offer scalable insights.
- Understanding knowledge accumulation is key in rapidly evolving fields.
Purpose of the Study:
- To demonstrate the utility of large-scale scientometric analysis.
- To identify key articles and trends in computational chemistry.
- To complement qualitative reviews with data-driven evidence.
Main Methods:
- Analysis of 181 million tri-cited articles.
- Application of modern scientometric techniques.
- Selection of a trio of articles from computational chemistry.
Main Results:
- Identified a set of highly influential articles in computational chemistry.
- Demonstrated the feasibility of large-scale scientometric analysis.
- Provided data to complement qualitative understanding of the field.
Conclusions:
- Scientometric techniques offer valuable, scalable insights into scientific fields.
- Quantitative analysis can effectively map knowledge accumulation.
- This approach enhances traditional methods for evaluating research impact.
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