SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries
Impact in
- Genetics 316
Classified as
- Authors
- Curtis P. Van TassellTimothy P. L. SmithLakshmi K. MatukumalliJeremy F. TaylorRobert D. Schnabel
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.1185 →Countries where authors are citing SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries
This map shows the geographic impact of SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. 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 SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries more than expected).
Fields of papers citing SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries
This network shows the impact of SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries.
About SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries
This paper, published in 2008, received 486 indexed citations . Written by Curtis P. Van Tassell, Timothy P. L. Smith, Lakshmi K. Matukumalli, Jeremy F. Taylor, Robert D. Schnabel, Cindy Lawley, Christian Haudenschild, S. S. Moore, Wesley C. Warren and Tad S. Sonstegard covering the research area of Genetics. It is primarily cited by scholars working on Genetics (316 citations), Molecular Biology (182 citations), Plant Science (136 citations), Cancer Research (49 citations) and Ecology (37 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.1185.