Investigating Intestinal Inflammation in DSS-induced Model of IBD

480 indexed citations
published 2012
Authors
Janice KimMd. Sharif ShajibWaliul I. Khan
Journal
Journal of Visualized Experiments

In The Last Decade

doi.org/10.3791/3678 →

Countries where authors are citing Investigating Intestinal Inflammation in DSS-induced Model of IBD

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Citations

This map shows the geographic impact of Investigating Intestinal Inflammation in DSS-induced Model of IBD. 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 Investigating Intestinal Inflammation in DSS-induced Model of IBD with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Investigating Intestinal Inflammation in DSS-induced Model of IBD more than expected).

Fields of papers citing Investigating Intestinal Inflammation in DSS-induced Model of IBD

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Investigating Intestinal Inflammation in DSS-induced Model of IBD. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Investigating Intestinal Inflammation in DSS-induced Model of IBD.

About Investigating Intestinal Inflammation in DSS-induced Model of IBD

This paper, published in 2012, received 480 indexed citations . Written by Janice Kim, Md. Sharif Shajib and Waliul I. Khan covering the research area of Genetics, Molecular Biology and Epidemiology. It is primarily cited by scholars working on Molecular Biology (210 citations), Genetics (138 citations) and Immunology (118 citations). Published in Journal of Visualized Experiments.

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/10.3791/3678.

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