Massively parallel single-nucleus RNA-seq with DroNc-seq

Abstract

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About

This paper, published in 1950, received 628 indexed citations. Written by Naomi Habib, Inbal Avraham‐Davidi, Anindita Basu, Tyler Burks, Karthik Shekhar, Matan Hofree, Sourav Choudhury, François Aguet, Ellen Gelfand and Kristin Ardlie covering the research area of Molecular Biology and Cancer Research. It is primarily cited by scholars working on Molecular Biology (475 citations), Cancer Research (130 citations) and Neurology (118 citations). Published in Nature Methods.

Countries where authors are citing Massively parallel single-nucleus RNA-seq with DroNc-seq

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Citations

This map shows the geographic impact of Massively parallel single-nucleus RNA-seq with DroNc-seq. 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 Massively parallel single-nucleus RNA-seq with DroNc-seq with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massively parallel single-nucleus RNA-seq with DroNc-seq more than expected).

Fields of papers citing Massively parallel single-nucleus RNA-seq with DroNc-seq

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Massively parallel single-nucleus RNA-seq with DroNc-seq. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Massively parallel single-nucleus RNA-seq with DroNc-seq.

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.4407.

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