CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets

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This paper, published in 1950, received 542 indexed citations. Written by Shengdar Q. Tsai, Nathalie T. Nguyen, Jose Malagon-Lopez, Ved V. Topkar, Martin J. Aryee and J. Keith Joung covering the research area of Molecular Biology. It is primarily cited by scholars working on Molecular Biology (511 citations), Genetics (142 citations) and Business and International Management (79 citations). Published in Nature Methods.

Countries where authors are citing CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets

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This map shows the geographic impact of CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets. 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 CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets more than expected).

Fields of papers citing CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets.

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.4278.

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2026