Protein Expression and Purification

5.7k papers and 107.3k indexed citations i.

About

The 5.7k papers published in Protein Expression and Purification in the last decades have received a total of 107.3k indexed citations. Papers published in Protein Expression and Purification usually cover Molecular Biology (4.2k papers), Genetics (845 papers) and Biotechnology (804 papers) specifically the topics of Monoclonal and Polyclonal Antibodies Research (749 papers), Viral Infectious Diseases and Gene Expression in Insects (620 papers) and Protein purification and stability (543 papers). The most active scholars publishing in Protein Expression and Purification are F. William Studier, David S. Waugh, Yifeng Li, Song Tan, M. Castoldi, A. V. Popov, Brian G. Fox, Tsutomu Arakawa, Daisuke Ejima and Kouhei Tsumoto.

In The Last Decade

Fields of papers published in Protein Expression and Purification

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Protein Expression and Purification. 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 Protein Expression and Purification.

Countries where authors publish in Protein Expression and Purification

Since Specialization
Citations

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