Current Computer - Aided Drug Design

780 papers and 8.7k indexed citations i.

About

The 780 papers published in Current Computer - Aided Drug Design in the last decades have received a total of 8.7k indexed citations. Papers published in Current Computer - Aided Drug Design usually cover Computational Theory and Mathematics (404 papers), Molecular Biology (313 papers) and Organic Chemistry (239 papers) specifically the topics of Computational Drug Discovery Methods (404 papers), Synthesis and biological activity (158 papers) and Click Chemistry and Applications (49 papers). The most active scholars publishing in Current Computer - Aided Drug Design are Hong‐Xing Zhang, Xuan-Yu Meng, Mihaly Mezei, Meng Cui, Tingjun Hou, Xiaojie Xu, Junmei Wang, Hong‐Yu Zhang, Subhash C. Basak and Mark T.D. Cronin.

In The Last Decade

Fields of papers published in Current Computer - Aided Drug Design

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Current Computer - Aided Drug Design. 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 Current Computer - Aided Drug Design.

Countries where authors publish in Current Computer - Aided Drug Design

Since Specialization
Citations

This map shows the geographic impact of research published in Current Computer - Aided Drug Design. 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 Current Computer - Aided Drug Design with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Current Computer - Aided Drug Design more than expected).

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.

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