Computational Biology and Chemistry

2.3k papers and 29.2k indexed citations i.

About

The 2.3k papers published in Computational Biology and Chemistry in the last decades have received a total of 29.2k indexed citations. Papers published in Computational Biology and Chemistry usually cover Molecular Biology (1.7k papers), Computational Theory and Mathematics (444 papers) and Organic Chemistry (224 papers) specifically the topics of Computational Drug Discovery Methods (441 papers), Protein Structure and Dynamics (296 papers) and Machine Learning in Bioinformatics (293 papers). The most active scholars publishing in Computational Biology and Chemistry are Robert E. Ulanowicz, Jan Gorodkin, M. James C. Crabbe, William R. Taylor, Hervé Seligmann, Christian Michel, Zengyou He, Weichuan Yu, Cheng‐Hong Yang and Li‐Yeh Chuang.

In The Last Decade

Fields of papers published in Computational Biology and Chemistry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computational Biology and Chemistry. 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 Computational Biology and Chemistry.

Countries where authors publish in Computational Biology and Chemistry

Since Specialization
Citations

This map shows the geographic impact of research published in Computational Biology and Chemistry. 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 Computational Biology and Chemistry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational Biology and Chemistry 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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2025