Substituent constants for correlation analysis in chemistry and biology
Impact in
- Spectroscopy 693
Classified as
- Authors
- Corwin HanschAlbert J. Leo
- Journal
- Medical Entomology and Zoology
In The Last Decade
doi.org/w15335986 →Countries where authors are citing Substituent constants for correlation analysis in chemistry and biology
This map shows the geographic impact of Substituent constants for correlation analysis in chemistry and biology. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Substituent constants for correlation analysis in chemistry and biology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Substituent constants for correlation analysis in chemistry and biology more than expected).
Fields of papers citing Substituent constants for correlation analysis in chemistry and biology
This network shows the impact of Substituent constants for correlation analysis in chemistry and biology. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Substituent constants for correlation analysis in chemistry and biology.
About Substituent constants for correlation analysis in chemistry and biology
This paper, published in 1979, received 2.6k indexed citations . Written by Corwin Hansch and Albert J. Leo covering the research area of Computational Theory and Mathematics. It is primarily cited by scholars working on Organic Chemistry (870 citations), Spectroscopy (693 citations), Molecular Biology (618 citations), Computational Theory and Mathematics (475 citations) and Health, Toxicology and Mutagenesis (264 citations). Published in Medical Entomology and Zoology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w15335986.