BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine
- Journal
- Scientific Reports
In The Last Decade
doi.org/10.1038/srep21146 →Countries where authors are citing BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine
This map shows the geographic impact of BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine. 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 BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine more than expected).
Fields of papers citing BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine
This network shows the impact of BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine.
About BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine
This paper, published in 2016, received 639 indexed citations . Written by Zhongyang Liu, Feifei Guo, Yong Wang, Chun Li, Xinlei Zhang, Honglei Li, Lihong Diao, Jiangyong Gu, Wei Wang and Dong Li covering the research area of Molecular Biology and Computational Theory and Mathematics. It is primarily cited by scholars working on Molecular Biology (360 citations), Pharmacology (222 citations) and Complementary and alternative medicine (157 citations). Published in Scientific Reports.
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/10.1038/srep21146.