An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy
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This map shows the geographic impact of An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy. 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 An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy more than expected).
Fields of papers citing An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy
This network shows the impact of An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy.
About An ancient retrotransposal insertion causes Fukuyama-type congenital muscular dystrophy
This paper, published in 1998, received 624 indexed citations . Written by Kazuhiro Kobayashi, Yutaka Nakahori, Masashi Miyake, Kiichiro Matsumura, Eri Kondo-Iida, Yoshiko Nomura, Masaya Segawa, Mieko Yoshioka, Kayoko Saito and Makiko Ōsawa covering the research area of Molecular Biology, Physiology and Cellular and Molecular Neuroscience. It is primarily cited by scholars working on Molecular Biology (559 citations), Cellular and Molecular Neuroscience (135 citations) and Cell Biology (86 citations). Published in Nature.
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/10.1038/28653.