Applications of single-cell RNA sequencing in drug discovery and development
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Countries where authors are citing Applications of single-cell RNA sequencing in drug discovery and development
This map shows the geographic impact of Applications of single-cell RNA sequencing in drug discovery and development. 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 Applications of single-cell RNA sequencing in drug discovery and development with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Applications of single-cell RNA sequencing in drug discovery and development more than expected).
Fields of papers citing Applications of single-cell RNA sequencing in drug discovery and development
This network shows the impact of Applications of single-cell RNA sequencing in drug discovery and development. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Applications of single-cell RNA sequencing in drug discovery and development.
About Applications of single-cell RNA sequencing in drug discovery and development
This paper, published in 2023, received 271 indexed citations . Written by Bram Van de Sande, Joon Sang Lee, Euphemia Mutasa-Gottgens, Bartholomew J. Naughton, Wendi Bacon, Jonathan R. Manning, Yong Wang, Jack Russella Pollard, Melissa G. Mendez and Jon Hill covering the research area of Biophysics, Molecular Biology and Cancer Research. It is primarily cited by scholars working on Molecular Biology (157 citations), Cancer Research (48 citations), Oncology (30 citations), Immunology (26 citations) and Biophysics (25 citations). Published in Nature Reviews Drug Discovery.
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/s41573-023-00688-4.