Countries where authors publish in Interdisciplinary Sciences Computational Life Sciences
Since Specialization
Citations
This map shows the geographic impact of research published in Interdisciplinary Sciences Computational Life Sciences. 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 papers published in Interdisciplinary Sciences Computational Life Sciences with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Interdisciplinary Sciences Computational Life Sciences more than expected).
Fields of papers published in Interdisciplinary Sciences Computational Life Sciences
This network shows the impact of papers published in Interdisciplinary Sciences Computational Life Sciences. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Interdisciplinary Sciences Computational Life Sciences.
About Interdisciplinary Sciences Computational Life Sciences
The 886 papers published in Interdisciplinary Sciences Computational Life Sciences in the last decades have received a total of 9.4k indexed citations . Papers published in Interdisciplinary Sciences Computational Life Sciences usually cover Drug Discovery (2 papers), Computational Theory and Mathematics (144 papers) and Molecular Biology (580 papers) specifically the topics of Computational Drug Discovery Methods (139 papers), Machine Learning in Bioinformatics (110 papers) and Bioinformatics and Genomic Networks (92 papers). The most active scholars publishing in Interdisciplinary Sciences Computational Life Sciences are Le Zhang, Jin Li, Ailing Fu, Dong‐Qing Wei, Pritish Kumar Varadwaj, Shaoliang Peng, Jamal Aïssa, Mukesh C. Sharma, Luc Montagnier and Qi Zhao.
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.