KEGG Mapper for inferring cellular functions from protein sequences

Abstract

About

This paper, published in 1950, received 791 indexed citations. Written by Minoru Kanehisa and Yoko Sato covering the research area of Molecular Biology. It is primarily cited by scholars working on Molecular Biology (438 citations), Ecology (164 citations) and Plant Science (138 citations). Published in Protein Science.

In The Last Decade

doi.org/10.1002/pro.3711 →

Countries where authors are citing KEGG Mapper for inferring cellular functions from protein sequences

Since Specialization

Citations

This map shows the geographic impact of KEGG Mapper for inferring cellular functions from protein sequences. 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 KEGG Mapper for inferring cellular functions from protein sequences with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites KEGG Mapper for inferring cellular functions from protein sequences more than expected).

Fields of papers citing KEGG Mapper for inferring cellular functions from protein sequences

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of KEGG Mapper for inferring cellular functions from protein sequences. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the KEGG Mapper for inferring cellular functions from protein sequences.

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/10.1002/pro.3711.

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