Chase L. Beisel

7.3k total citations · 2 hit papers
99 papers, 5.2k citations indexed

About

Chase L. Beisel is a scholar working on Molecular Biology, Genetics and Insect Science. According to data from OpenAlex, Chase L. Beisel has authored 99 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Molecular Biology, 29 papers in Genetics and 16 papers in Insect Science. Recurrent topics in Chase L. Beisel's work include CRISPR and Genetic Engineering (77 papers), RNA and protein synthesis mechanisms (41 papers) and Bacterial Genetics and Biotechnology (22 papers). Chase L. Beisel is often cited by papers focused on CRISPR and Genetic Engineering (77 papers), RNA and protein synthesis mechanisms (41 papers) and Bacterial Genetics and Biotechnology (22 papers). Chase L. Beisel collaborates with scholars based in United States, Germany and France. Chase L. Beisel's co-authors include Gisela Storz, Ryan T. Leenay, Michelle L. Luo, Daphne Collias, Christina D. Smolke, Rodolphe Barrangou, Zhen Gu, Wujin Sun, Wenyan Ji and Quanyin Hu and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Chase L. Beisel

94 papers receiving 5.1k citations

Hit Papers

Self‐Assembled DNA Nanoclews for the Efficient Delivery o... 2015 2026 2018 2022 2015 2021 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chase L. Beisel United States 40 4.6k 1.2k 607 472 379 99 5.2k
Melissa Richards United States 5 4.6k 1.0× 1.0k 0.9× 1.2k 1.9× 555 1.2× 180 0.5× 7 5.1k
Ekaterina Semenova United States 34 5.8k 1.3× 1.4k 1.2× 904 1.5× 839 1.8× 274 0.7× 68 6.4k
Francisco J. M. Mojica Spain 22 5.7k 1.3× 1.4k 1.2× 1.3k 2.1× 769 1.6× 170 0.4× 35 6.4k
Magnus Lundgren Sweden 19 4.1k 0.9× 1.3k 1.1× 950 1.6× 490 1.0× 101 0.3× 30 4.5k
David Bikard France 35 6.2k 1.4× 2.0k 1.7× 1.9k 3.1× 670 1.4× 240 0.6× 63 7.6k
Hélène Deveau Canada 12 6.1k 1.3× 1.3k 1.1× 2.1k 3.4× 737 1.6× 210 0.6× 15 6.9k
Karen L. Maxwell Canada 39 4.1k 0.9× 879 0.8× 2.6k 4.3× 533 1.1× 449 1.2× 94 5.7k
Leonid Minakhin United States 28 4.6k 1.0× 1.5k 1.3× 1.4k 2.3× 332 0.7× 263 0.7× 57 5.2k
Daan C. Swarts Netherlands 22 3.3k 0.7× 642 0.5× 748 1.2× 279 0.6× 321 0.8× 34 3.7k
Lucas B. Harrington United States 16 6.1k 1.3× 776 0.7× 340 0.6× 555 1.2× 1.1k 3.0× 21 6.6k

Countries citing papers authored by Chase L. Beisel

Since Specialization
Citations

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

Fields of papers citing papers by Chase L. Beisel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chase L. Beisel. 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 Chase L. Beisel. The network helps show where Chase L. Beisel may publish in the future.

Co-authorship network of co-authors of Chase L. Beisel

This figure shows the co-authorship network connecting the top 25 collaborators of Chase L. Beisel. A scholar is included among the top collaborators of Chase L. Beisel 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 Chase L. Beisel. Chase L. Beisel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Smyth, Redmond P., et al.. (2026). RNA-triggered Cas12a3 cleaves tRNA tails to execute bacterial immunity. Nature. 649(8099). 1312–1321.
2.
Schmelz, Stefan, et al.. (2025). AcrVIB1 inhibits CRISPR-Cas13b immunity by promoting unproductive crRNA binding accessible to RNase attack. Molecular Cell. 85(6). 1162–1175.e7. 1 indexed citations
3.
Liao, Chunyu, et al.. (2024). CRISPR-based screening of small RNA modulators of bile susceptibility in Bacteroides thetaiotaomicron. Proceedings of the National Academy of Sciences. 121(6). e2311323121–e2311323121. 7 indexed citations
4.
Vento, Justin M., Tianyu Li, Constantinos Patinios, et al.. (2024). A cell-free transcription-translation pipeline for recreating methylation patterns boosts DNA transformation in bacteria. Molecular Cell. 84(14). 2785–2796.e4. 10 indexed citations
6.
Jabalera, Ylenia, Igor Tascón, Jorge P. López‐Alonso, et al.. (2024). A resurrected ancestor of Cas12a expands target access and substrate recognition for nucleic acid editing and detection. Nature Biotechnology. 43(10). 1663–1672. 1 indexed citations
7.
Arifah, Adini Qisthi, Georgia Angelidou, Volker Brinkmann, et al.. (2024). MprF-mediated immune evasion is necessary for Lactiplantibacillus plantarum resilience in the Drosophila gut during inflammation. PLoS Pathogens. 20(8). e1012462–e1012462. 5 indexed citations
8.
Liao, Chunyu, et al.. (2023). Shortened CRISPR-Cas9 arrays enable multiplexed gene targeting in bacteria from a smaller DNA footprint. RNA Biology. 20(1). 666–680. 1 indexed citations
9.
Jiao, Chunlei, Christina Homberger, Jörg Vogel, et al.. (2023). RNA recording in single bacterial cells using reprogrammed tracrRNAs. Nature Biotechnology. 41(8). 1107–1116. 17 indexed citations
11.
Liao, Chunyu, Sarah L. Svensson, Zasha Weinberg, et al.. (2022). Spacer prioritization in CRISPR–Cas9 immunity is enabled by the leader RNA. Nature Microbiology. 7(4). 530–541. 9 indexed citations
12.
Yu, Tao, et al.. (2021). Coupling smartphone and CRISPR–Cas12a for digital and multiplexed nucleic acid detection. AIChE Journal. 67(12). 43 indexed citations
13.
Annas, George J., Chase L. Beisel, Kendell Clement, et al.. (2021). A Code of Ethics for Gene Drive Research. The CRISPR Journal. 4(1). 19–24. 29 indexed citations
14.
Collias, Daphne, Ryan T. Leenay, Rebecca Slotkowski, et al.. (2020). A positive, growth-based PAM screen identifies noncanonical motifs recognized by the S. pyogenes Cas9. Science Advances. 6(29). eabb4054–eabb4054. 22 indexed citations
15.
Garenne, David, Chase L. Beisel, & Vincent Noireaux. (2019). Characterization of the all‐ E. coli transcription‐translation system myTXTL by mass spectrometry. Rapid Communications in Mass Spectrometry. 33(11). 1036–1048. 42 indexed citations
16.
Westbrook, Alexandra, Xun Tang, Ryan Marshall, et al.. (2019). Distinct timescales of RNA regulators enable the construction of a genetic pulse generator. Biotechnology and Bioengineering. 116(5). 1139–1151. 40 indexed citations
17.
Black, Joshua B., Tyler S. Klann, Christopher E. Nelson, et al.. (2019). Targeted transcriptional modulation with type I CRISPR–Cas systems in human cells. Nature Biotechnology. 37(12). 1493–1501. 65 indexed citations
18.
Agrawal, Deepak K., Xun Tang, Alexandra Westbrook, et al.. (2018). Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression. ACS Synthetic Biology. 7(5). 1219–1228. 30 indexed citations
19.
Marshall, Ryan, Colin S. Maxwell, Scott P. Collins, Chase L. Beisel, & Vincent Noireaux. (2017). Short DNA containing χ sites enhances DNA stability and gene expression in E. coli cell‐free transcription–translation systems. Biotechnology and Bioengineering. 114(9). 2137–2141. 65 indexed citations
20.
Klumpe, Heidi E., et al.. (2014). Programmable Removal of Bacterial Strains by Use of Genome-Targeting CRISPR-Cas Systems. mBio. 5(1). e00928–13. 307 indexed citations

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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