Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
Impact in
- Molecular Biology 1.4k
- Ecology 950
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.2276 →Countries where authors are citing Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
This map shows the geographic impact of Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. 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 Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing more than expected).
Fields of papers citing Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
This network shows the impact of Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing.
About Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
This paper, published in 2012, received 3.4k indexed citations . Written by Nicholas A. Bokulich, Sathish Subramanian, Jeremiah J. Faith, Dirk Gevers, Jeffrey I. Gordon, Rob Knight, David A. Mills and J. Gregory Caporaso covering the research area of Molecular Biology and Ecology. It is primarily cited by scholars working on Molecular Biology (1.4k citations), Ecology (950 citations), Plant Science (562 citations), Food Science (308 citations) and Pollution (265 citations). Published in Nature 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.2276.