This map shows the geographic impact of research published in STAR Protocols. 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 STAR Protocols with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites STAR Protocols more than expected).
This network shows the impact of papers published in STAR Protocols. 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 STAR Protocols.
About STAR Protocols
The 3.5k papers published in STAR Protocols in the last decades have received a total of 18.0k indexed citations . Papers published in STAR Protocols usually cover Molecular Biology (1.1k papers), Biophysics (101 papers), Developmental Neuroscience (36 papers), Cell Biology (118 papers) and Immunology (145 papers) specifically the topics of Single-cell and spatial transcriptomics (158 papers), Pluripotent Stem Cells Research (142 papers), CRISPR and Genetic Engineering (125 papers), Genomics and Chromatin Dynamics (80 papers), Advanced Fluorescence Microscopy Techniques (59 papers), Advanced Proteomics Techniques and Applications (51 papers), SARS-CoV-2 and COVID-19 Research (51 papers) and T-cell and B-cell Immunology (46 papers). The most active scholars publishing in STAR Protocols are Ido Goldstein, Meital Charni‐Natan, Toshimasa Yamauchi, Takashi Kadowaki, Gotaro Toda, Kohjiro Ueki, Qiang Wan, Yi Liu, Yuan Ma and Xia Gu.
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.