Similarity network fusion for aggregating data types on a genomic scale

1.3k indexed citations

Abstract

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This paper, published in 2014, received 1.3k indexed citations. Written by Bo Wang, Aziz M. Mezlini, Marc Fiume, Zhuowen Tu, Michael Brudno, Benjamin Haibe‐Kains and Anna Goldenberg covering the research area of Molecular Biology. It is primarily cited by scholars working on Molecular Biology (881 citations), Cancer Research (222 citations) and Artificial Intelligence (185 citations). Published in Nature Methods.

Countries where authors are citing Similarity network fusion for aggregating data types on a genomic scale

Specialization
Citations

This map shows the geographic impact of Similarity network fusion for aggregating data types on a genomic scale. 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 Similarity network fusion for aggregating data types on a genomic scale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Similarity network fusion for aggregating data types on a genomic scale more than expected).

Fields of papers citing Similarity network fusion for aggregating data types on a genomic scale

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Similarity network fusion for aggregating data types on a genomic scale. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Similarity network fusion for aggregating data types on a genomic scale.

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.2810.

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