Quantitative single-cell RNA-seq with unique molecular identifiers

812 indexed citations

Abstract

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About

This paper, published in 2013, received 812 indexed citations. Written by Saiful Islam, Amit Zeisel, Simon Joost, Gioele La Manno, Paweł Zając, Maria Kasper, Peter Lönnerberg and Sten Linnarsson covering the research area of Molecular Biology and Cancer Research. It is primarily cited by scholars working on Molecular Biology (721 citations), Cancer Research (239 citations) and Immunology (121 citations). Published in Nature Methods.

Countries where authors are citing Quantitative single-cell RNA-seq with unique molecular identifiers

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This map shows the geographic impact of Quantitative single-cell RNA-seq with unique molecular identifiers. 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 Quantitative single-cell RNA-seq with unique molecular identifiers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quantitative single-cell RNA-seq with unique molecular identifiers more than expected).

Fields of papers citing Quantitative single-cell RNA-seq with unique molecular identifiers

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Quantitative single-cell RNA-seq with unique molecular identifiers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Quantitative single-cell RNA-seq with unique molecular identifiers.

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.2772.

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