Melissa Sutton

18 papers receiving 205 citations

Peers

Melissa Sutton
Comparison fields: 5 of 77
  • Pharmacology 40
  • Biochemistry 16
  • Infectious Diseases 38
  • Applied Microbiology and Biotechnology 4
  • Modeling and Simulation 9
Replace Gabriel Pasquarelli-do-Nascimento with:
Gabriel Pasquarelli-do-Nascimento Brazil
Marco Fois Italy
Yu-Han Kao United States
Xiaohua Peng China
Naamah Bloch Israel
A.N. Galustyan Russia
Yoon-Seop Kim South Korea
Frank A. Orlando United States
Giovanni Noberasco Italy
Shujun Gu China
Melissa Sutton relative to Gabriel Pasquarelli-do-Nascimento Brazil Gabriel Pasquarelli-do-Nascimento's profile →
Citations per field
00.5×
Gabriel Pasquarelli-do-Nascimento · 1×
Citations per year

Countries citing papers authored by Melissa Sutton

Since Specialization
Citations

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

Fields of papers citing papers by Melissa Sutton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 200195
2
Effects of exercise training on common femoral artery blood flow in patients with intermittent claudication.
198927
3 202020
4 202316
5 202012
6 20256
7 20186
8 20246
9 20225
10
Noninvasive echo-Doppler duplex measurements of common femoral artery blood flow variables during supine exercise and post-occlusive reactive hyperemia.
19825
11 20225
12 20183
13 20242
14 20142
15 19652
16 20241
17 20221
18 20251
19 20250
20 20250

About Melissa Sutton

Melissa Sutton is a scholar working on Infectious Diseases, Epidemiology, Surgery, Clinical Psychology and Molecular Biology, having authored 20 papers that have together received 215 indexed citations. Recurring topics across this work include Respiratory viral infections research (6 papers), SARS-CoV-2 detection and testing (4 papers), Peripheral Artery Disease Management (3 papers), Family and Disability Support Research (2 papers), Child and Adolescent Psychosocial and Emotional Development (2 papers), COVID-19 Clinical Research Studies (2 papers), COVID-19 Impact on Reproduction (2 papers) and Advanced Chemical Sensor Technologies (1 paper). The work is most often cited by research in Pharmacology (40 citations), Biochemistry (16 citations), Infectious Diseases (38 citations), Applied Microbiology and Biotechnology (4 citations) and Modeling and Simulation (9 citations). Melissa Sutton has collaborated with scholars based in United States, Thailand and Canada. Frequent co-authors include Daniel J. Noonan, Shamina M. Rangwala, Karl Romstedt, Srichan Phornchirasilp, Dennis R. Feller, Gamal Shams, Paul R. Cieslak, Ernest R. Greene, Elaine C. Johnson and Wyatt F. Voyles. Their work appears in journals such as Early Childhood Education Journal, MMWR Morbidity and Mortality Weekly Report, Influenza and Other Respiratory Viruses, JAMA Network Open and Infant Mental Health Journal.

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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