Granger Sutton

16.3k citations
18 papers · 1.0k · h-index 11

Impact in

Papers in

    • Genomics and Phylogenetic Studies 17
    • RNA and protein synthesis mechanisms 4
    • Genetics, Bioinformatics, and Biomedical Research 2
    • Machine Learning in Bioinformatics 2
    • Biomedical Text Mining and Ontologies 2
    • Microbial Community Ecology and Physiology 5
    • Bacteriophages and microbial interactions 2

Granger Sutton

18 papers receiving 984 citations

Peers

Granger Sutton
Comparison fields: 5 of 102
  • Endocrinology 88
  • Molecular Medicine 77
  • Microbiology 9
  • Molecular Biology 722
  • Ecology 218
Replace M Lefèvre with:
M Lefèvre France
Yongbing Zhao China
Muriel Gaillard Switzerland
Weilong Hao United States
Günther Muth Germany
Rita Zilhão Portugal
Juraj Michálik Czechia
Astrid Lewin Germany
Gustavo Cerqueira United States
Avi Kimchi United States
Granger Sutton relative to M Lefèvre France M Lefèvre's profile →
Citations per field
00.5×4.5×
M Lefèvre · 1×
Citations per year

Countries citing papers authored by Granger Sutton

Since Specialization
Citations

This map shows the geographic impact of Granger Sutton's research. 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 Granger Sutton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Granger Sutton more than expected).

Fields of papers citing papers by Granger Sutton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Granger Sutton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Granger Sutton. The network helps show where Granger Sutton may publish in the future.

Co-authors

The 25 scholars most cited alongside Granger Sutton, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Granger Sutton Line = papers co-authored together Granger Sutton links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2009203
2 1995196
3 2004175
4 2012152
5 200879
6 201675
7 200831
8 199325
9 201118
10 200516
11 201511
12 201710
13
The comprehensive microbial resource
20009
14 20189
15 20094
16 19954
17 20043
18
The impact of rapid gene discovery technology on studies of evolution and biodiversity.
19973

About Granger Sutton

Granger Sutton is a scholar working on Molecular Biology, Ecology, Plant Science, Artificial Intelligence and Food Science, having authored 18 papers that have together received 1.0k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (17 papers), Microbial Community Ecology and Physiology (5 papers), RNA and protein synthesis mechanisms (4 papers), Chromosomal and Genetic Variations (4 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Machine Learning in Bioinformatics (2 papers), Bacteriophages and microbial interactions (2 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Endocrinology (88 citations), Molecular Medicine (77 citations), Microbiology (9 citations), Molecular Biology (722 citations) and Ecology (218 citations). Granger Sutton has collaborated with scholars based in United States, South Africa and Italy. Frequent co-authors include Erin Beck, Chris Fields, Carol J. Bult, Rebecca A. Clayton, Lauren Brinkac, Derrick E. Fouts, Jason Inman, Aaron L. Halpern, George M Garrity and Brian J. Tindall. Their work appears in journals such as Nucleic Acids Research, Bioinformatics, Journal of Computational Biology, BMC Bioinformatics and 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.

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