PROTEOMICS

7.2k papers and 286.6k indexed citations i.

About

The 7.2k papers published in PROTEOMICS in the last decades have received a total of 286.6k indexed citations. Papers published in PROTEOMICS usually cover Molecular Biology (5.0k papers), Spectroscopy (2.6k papers) and Cell Biology (575 papers) specifically the topics of Advanced Proteomics Techniques and Applications (2.4k papers), Mass Spectrometry Techniques and Applications (1.4k papers) and Metabolomics and Mass Spectrometry Studies (760 papers). The most active scholars publishing in PROTEOMICS are Thierry Rabilloud, Michael J. Dünn, Richard J. Simpson, Suresh Mathivanan, Angelika Görg, Setsuko Komatsu, Albert Sickmann, Jimmy K. Eng, Walter Weiss and Michael Hecker.

In The Last Decade

Fields of papers published in PROTEOMICS

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in PROTEOMICS. 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 PROTEOMICS.

Countries where authors publish in PROTEOMICS

Since Specialization
Citations

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