S. Ellis

52 papers receiving 1.7k citations

Hit Papers

Radioimmunoassay for Rat Prolactin 1969 · 322 citations
3221969202619882007100200300

Peers

S. Ellis
Comparison fields: 5 of 109
  • Endocrinology, Diabetes and Metabolism 395
  • Behavioral Neuroscience 67
  • Cellular and Molecular Neuroscience 326
  • Reproductive Medicine 122
  • Cell Biology 223
Replace Bronwyn A. Evans with:
Bronwyn A. Evans Australia
Judit Horváth United States
K J Collier United States
J L Vannice United States
Tśuyoshi Soji Japan
Shunsuke Furuyama Japan
U. Krause Germany
Jean Y. Dubé Canada
C. A. Schneyer United States
David L. Berliner United States
S. Ellis relative to Bronwyn A. Evans Australia Bronwyn A. Evans's profile →
Citations per field
00.5×1.6×
Bronwyn A. Evans · 1×
Citations per year

Countries citing papers authored by S. Ellis

Since Specialization
Citations

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

Fields of papers citing papers by S. Ellis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Ellis. 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 S. Ellis. The network helps show where S. Ellis may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20153
2 200816
3 200623
4 199215
5 198832
6 19888
7 198812
8 19875
9
The use of suspension models and comparison with true weightlessness
19852
10 198461
11 198312
12 197412
13 197313
14 197210
15
Polypeptide degradation by dipeptidyl aminopeptidase I /cathepsin C/ and related peptidases
197161
16
Radioimmunoassay for Rat Prolactin
Hit paper breakdown →
1969322
17 1969190
18 196619
19 196617
20 196632

About S. Ellis

S. Ellis is a scholar working on Endocrinology, Diabetes and Metabolism, Aging, Physiology, Cellular and Molecular Neuroscience and Rehabilitation, having authored 52 papers that have together received 1.8k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (14 papers), Muscle Physiology and Disorders (7 papers), Peptidase Inhibition and Analysis (6 papers), Neuropeptides and Animal Physiology (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Spaceflight effects on biology (4 papers), Muscle metabolism and nutrition (4 papers) and Neuroendocrine Tumor Research Advances (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (395 citations), Behavioral Neuroscience (67 citations), Cellular and Molecular Neuroscience (326 citations), Reproductive Medicine (122 citations) and Cell Biology (223 citations). S. Ellis has collaborated with scholars based in United States, United Kingdom and Slovakia. Frequent co-authors include J. Ken McDonald, Danny A. Riley, James Bain, Thomas J. Reilly, R. E. Grindeland, Benjamin B. Zeitman, A. REES MIDGLEY, G. D. Niswender, J. Meites and Glenn R. Slocum. Their work appears in journals such as Endocrinology, Experimental Biology and Medicine, Journal of Biological Chemistry, Annals of the New York Academy of Sciences and Journal of Histochemistry & Cytochemistry.

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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