Eric E. Snyder

4.2k citations
19 papers · 2.2k · h-index 16

Impact in

Papers in

    • Genomics and Phylogenetic Studies 6
    • RNA and protein synthesis mechanisms 3
    • Machine Learning in Bioinformatics 2
    • Genetic Mapping and Diversity in Plants and Animals 4
    • Genetic Associations and Epidemiology 4

Eric E. Snyder

19 papers receiving 2.1k citations

Peers

Eric E. Snyder
Comparison fields: 5 of 138
  • Endocrine and Autonomic Systems 467
  • Physiology 545
  • Parasitology 134
  • Nutrition and Dietetics 314
  • Genetics 557
Replace Mitsuharu Matsumoto with:
Mitsuharu Matsumoto Japan
J F Brown United Kingdom
Kathleen A. Smith United States
Takashi Kaneko Japan
Kimitoshi Kato Japan
Mrinalini C. Rao United States
Gabriela E. Bergonzelli Switzerland
Joseph Chou United States
John C. Carlson United States
Shoulong Deng China
Eric E. Snyder relative to Mitsuharu Matsumoto Japan Mitsuharu Matsumoto's profile →
Citations per field
00.5×5.7×
Mitsuharu Matsumoto · 1×
Citations per year

Countries citing papers authored by Eric E. Snyder

Since Specialization
Citations

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

Fields of papers citing papers by Eric E. Snyder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric E. Snyder. 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 Eric E. Snyder. The network helps show where Eric E. Snyder may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric E. Snyder, 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 Eric E. Snyder Line = papers co-authored together Eric E. Snyder links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2010274
2 2004240
3 2005234
4 2003177
5 2001174
6 2008155
7 1995145
8 1993134
9 2002130
10 1997106
11 1990102
12 199598
13 200294
14 200182
15 199148
16 200331
17 200713
18 20051
19 19901

About Eric E. Snyder

Eric E. Snyder is a scholar working on Molecular Biology, Genetics, Physiology, Surgery and Endocrine and Autonomic Systems, having authored 19 papers that have together received 2.2k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), Adipose Tissue and Metabolism (6 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers), Genetic Associations and Epidemiology (4 papers), RNA and protein synthesis mechanisms (3 papers), Pancreatic function and diabetes (2 papers), Machine Learning in Bioinformatics (2 papers) and Insect symbiosis and bacterial influences (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (467 citations), Physiology (545 citations), Parasitology (134 citations), Nutrition and Dietetics (314 citations) and Genetics (557 citations). Eric E. Snyder has collaborated with scholars based in United States, Canada and Sweden. Frequent co-authors include Claude Bouchard, Marie‐Christine Chagnon, Louis Përusse, Tuomo Rankinen, S. John Weisnagel, Gary D. Stormo, Gary D. Stormo, Brandon Walts, Bruno Sobral and Joshua M. Shallom. Their work appears in journals such as Biochemistry, Nucleic Acids Research, The Journal of Clinical Endocrinology & Metabolism, Journal of Bacteriology and Journal of Molecular Biology.

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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