Quantitative assessment of single-cell RNA-sequencing methods

535 indexed citations

Abstract

loading...

About

This paper, published in 2013, received 535 indexed citations. Written by Angela Ruohao Wu, Norma Neff, Tomer Kalisky, Piero Dalerba, Barbara Treutlein, Michael E. Rothenberg, Gary L. Mantalas, Sopheak Sim, Michael F. Clarke and Stephen R. Quake covering the research area of Molecular Biology. It is primarily cited by scholars working on Molecular Biology (437 citations), Cancer Research (128 citations) and Biomedical Engineering (74 citations). Published in Nature Methods.

Countries where authors are citing Quantitative assessment of single-cell RNA-sequencing methods

Specialization
Citations

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

Fields of papers citing Quantitative assessment of single-cell RNA-sequencing methods

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Quantitative assessment of single-cell RNA-sequencing methods. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Quantitative assessment of single-cell RNA-sequencing methods.

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.2694.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026