The Perseus computational platform for comprehensive analysis of (prote)omics data
Impact in
- Molecular Biology 3.3k
- Spectroscopy 679
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.3901 →Countries where authors are citing The Perseus computational platform for comprehensive analysis of (prote)omics data
This map shows the geographic impact of The Perseus computational platform for comprehensive analysis of (prote)omics data. 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 The Perseus computational platform for comprehensive analysis of (prote)omics data with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The Perseus computational platform for comprehensive analysis of (prote)omics data more than expected).
Fields of papers citing The Perseus computational platform for comprehensive analysis of (prote)omics data
This network shows the impact of The Perseus computational platform for comprehensive analysis of (prote)omics data. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The Perseus computational platform for comprehensive analysis of (prote)omics data.
About The Perseus computational platform for comprehensive analysis of (prote)omics data
This paper, published in 2016, received 5.6k indexed citations . Written by Stefka Tyanova, Pavel Sinitcyn, Marco Y. Hein, Tamar Geiger, Matthias Mann and Jürgen Cox covering the research area of Molecular Biology and Spectroscopy. It is primarily cited by scholars working on Molecular Biology (3.3k citations), Spectroscopy (679 citations), Cell Biology (640 citations), Immunology (520 citations) and Oncology (440 citations). Published in Nature Methods.
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/10.1038/nmeth.3901.