Efficient derivation of microglia-like cells from human pluripotent stem cells
Impact in
- Neurology 289
Classified as
- Journal
- Nature Medicine
In The Last Decade
doi.org/10.1038/nm.4189 →Countries where authors are citing Efficient derivation of microglia-like cells from human pluripotent stem cells
This map shows the geographic impact of Efficient derivation of microglia-like cells from human pluripotent stem cells. 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 Efficient derivation of microglia-like cells from human pluripotent stem cells with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Efficient derivation of microglia-like cells from human pluripotent stem cells more than expected).
Fields of papers citing Efficient derivation of microglia-like cells from human pluripotent stem cells
This network shows the impact of Efficient derivation of microglia-like cells from human pluripotent stem cells. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Efficient derivation of microglia-like cells from human pluripotent stem cells.
About Efficient derivation of microglia-like cells from human pluripotent stem cells
This paper, published in 2016, received 500 indexed citations . Written by Julien Muffat, Yun Li, Bingbing Yuan, Maisam Mitalipova, Attya Omer, Sean Corcoran, Grisilda Bakiasi, Li-Huei Tsai, Patrick Aubourg and Richard M. Ransohoff covering the research area of Neurology, Cellular and Molecular Neuroscience and Immunology. It is primarily cited by scholars working on Neurology (289 citations), Molecular Biology (192 citations), Immunology (151 citations), Developmental Neuroscience (141 citations) and Cellular and Molecular Neuroscience (83 citations). Published in Nature Medicine.
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/nm.4189.