Journal of Computational Biology

2.3k papers and 78.0k indexed citations i.

About

The 2.3k papers published in Journal of Computational Biology in the last decades have received a total of 78.0k indexed citations. Papers published in Journal of Computational Biology usually cover Molecular Biology (2.0k papers), Genetics (484 papers) and Artificial Intelligence (429 papers) specifically the topics of Genomics and Phylogenetic Studies (701 papers), RNA and protein synthesis mechanisms (429 papers) and Gene expression and cancer classification (398 papers). The most active scholars publishing in Journal of Computational Biology are Hidde de Jong, Pavel A. Pevzner, Max A. Alekseyev, Anton Bankevich, Glenn Tesler, Alexander Sirotkin, Dmitry Antipov, Sergey Nurk, Andrey D. Prjibelski and Alexey Gurevich.

In The Last Decade

Fields of papers published in Journal of Computational Biology

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries where authors publish in Journal of Computational Biology

Since Specialization
Citations

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