Wen Y. Wu

1.5k total citations · 1 hit paper
9 papers, 971 citations indexed

About

Wen Y. Wu is a scholar working on Molecular Biology, Business and International Management and Genetics. According to data from OpenAlex, Wen Y. Wu has authored 9 papers receiving a total of 971 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Business and International Management and 2 papers in Genetics. Recurrent topics in Wen Y. Wu's work include CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Wen Y. Wu is often cited by papers focused on CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Wen Y. Wu collaborates with scholars based in Netherlands, United States and Germany. Wen Y. Wu's co-authors include John van der Oost, Prarthana Mohanraju, David Scott, Sourav Choudhury, Iana Fedorova, Nerges Winblad, Bernd Zetsche, Omar O. Abudayyeh, Matthias Heidenreich and Jonathan S. Gootenberg and has published in prestigious journals such as Nucleic Acids Research, Nature Biotechnology and Molecular Cell.

In The Last Decade

Wen Y. Wu

9 papers receiving 959 citations

Hit Papers

Multiplex gene editing by... 2016 2026 2019 2022 2016 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wen Y. Wu Netherlands 8 940 154 153 121 109 9 971
Jeroen Kneppers Netherlands 4 815 0.9× 132 0.9× 131 0.9× 86 0.7× 90 0.8× 6 869
Nerges Winblad Sweden 4 768 0.8× 118 0.8× 127 0.8× 84 0.7× 88 0.8× 4 795
Xiaoshu Xu United States 10 1.1k 1.2× 241 1.6× 200 1.3× 96 0.8× 72 0.7× 13 1.3k
Kathleen A. Christie United Kingdom 11 1.1k 1.1× 276 1.8× 142 0.9× 99 0.8× 99 0.9× 15 1.2k
Hisato Hirano Japan 9 1.2k 1.3× 179 1.2× 136 0.9× 183 1.5× 114 1.0× 14 1.3k
Maolu Yin China 6 720 0.8× 118 0.8× 80 0.5× 101 0.8× 119 1.1× 9 734
Iana Fedorova Russia 10 1.4k 1.4× 206 1.3× 194 1.3× 170 1.4× 150 1.4× 11 1.4k
Benjamin J. Rauch United States 9 912 1.0× 134 0.9× 58 0.4× 166 1.4× 138 1.3× 10 974
Satomi Banno Japan 7 1.1k 1.2× 331 2.1× 188 1.2× 92 0.8× 97 0.9× 8 1.2k
Soumya Kannan United States 12 814 0.9× 135 0.9× 80 0.5× 75 0.6× 43 0.4× 19 860

Countries citing papers authored by Wen Y. Wu

Since Specialization
Citations

This map shows the geographic impact of Wen Y. Wu's research. 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 Wen Y. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wen Y. Wu more than expected).

Fields of papers citing papers by Wen Y. Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wen Y. Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wen Y. Wu. The network helps show where Wen Y. Wu may publish in the future.

Co-authorship network of co-authors of Wen Y. Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Wen Y. Wu. A scholar is included among the top collaborators of Wen Y. Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wen Y. Wu. Wen Y. Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Wu, Wen Y., Belén Adiego-Pérez, & John van der Oost. (2024). Biology and applications of CRISPR–Cas12 and transposon-associated homologs. Nature Biotechnology. 42(12). 1807–1821. 14 indexed citations
2.
Mohanraju, Prarthana & Wen Y. Wu. (2024). TldR: TnpB’s evolutionary shift from transposon nucleases to RNA-guided transcriptional regulators. Trends in Microbiology. 32(11). 1039–1041. 1 indexed citations
3.
Wu, Wen Y., et al.. (2024). Live-cell imaging reveals the trade-off between target search flexibility and efficiency for Cas9 and Cas12a. Nucleic Acids Research. 52(9). 5241–5256. 8 indexed citations
4.
Nakagawa, Ryoya, Christian Südfeld, Wen Y. Wu, et al.. (2023). Mechanistic and evolutionary insights into a type V-M CRISPR–Cas effector enzyme. Nature Structural & Molecular Biology. 30(8). 1172–1182. 20 indexed citations
5.
Wu, Wen Y., Prarthana Mohanraju, Chunyu Liao, et al.. (2022). The miniature CRISPR-Cas12m effector binds DNA to block transcription. Molecular Cell. 82(23). 4487–4502.e7. 62 indexed citations
6.
Wu, Wen Y., Prarthana Mohanraju, Chunyu Liao, et al.. (2021). The Miniature CRISPR-Cas12m Effector Binds DNA To Block Transcription. SSRN Electronic Journal. 8 indexed citations
7.
Wu, Wen Y., Prarthana Mohanraju, Ferhat Alkan, et al.. (2020). Good guide, bad guide: spacer sequence-dependent cleavage efficiency of Cas12a. Nucleic Acids Research. 48(6). 3228–3243. 75 indexed citations
8.
Wu, Wen Y., Joyce H.G. Lebbink, Roland Kanaar, Niels Geijsen, & John van der Oost. (2018). Genome editing by natural and engineered CRISPR-associated nucleases. Nature Chemical Biology. 14(7). 642–651. 84 indexed citations
9.
Zetsche, Bernd, Matthias Heidenreich, Prarthana Mohanraju, et al.. (2016). Multiplex gene editing by CRISPR–Cpf1 using a single crRNA array. Nature Biotechnology. 35(1). 31–34. 699 indexed citations breakdown →

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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