Sarah Will

1.2k citations
28 papers · 669 · h-index 15

Impact in

Papers in

Sarah Will

27 papers receiving 651 citations

Peers

Sarah Will
Comparison fields: 5 of 76
  • Endocrinology, Diabetes and Metabolism 181
  • Endocrine and Autonomic Systems 62
  • Physiology 141
  • Epidemiology 119
  • Cellular and Molecular Neuroscience 66
Replace Estela Wajcberg with:
Estela Wajcberg United States
Naoki Tamasawa Japan
Vishal Kothari United States
Hiroyasu Hirose Japan
Weina Zhu China
Emmanuelle Plée‐Gautier France
Alexander Obrosov United States
Fukashi Ishibashi Japan
Pimonrat Ketsawatsomkron United States
Tokuji Tanaka Japan
Sarah Will relative to Estela Wajcberg United States Estela Wajcberg's profile →
Citations per field
00.5×10×
Estela Wajcberg · 1×
Citations per year

Countries citing papers authored by Sarah Will

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Will

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006124
2 202161
3 200958
4 199155
5 201751
6 201847
7 198840
8 201833
9 201930
10 202423
11 201323
12 199017
13 200917
14 201216
15 202414
16 202012
17 201711
18 200910
19 20228
20 20237

About Sarah Will

Sarah Will is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Surgery, Physiology and Cellular and Molecular Neuroscience, having authored 28 papers that have together received 669 indexed citations. Recurring topics across this work include Diabetes Treatment and Management (8 papers), Metabolism, Diabetes, and Cancer (4 papers), Pancreatic function and diabetes (4 papers), Neuropeptides and Animal Physiology (4 papers), Pharmacology and Obesity Treatment (2 papers), Receptor Mechanisms and Signaling (2 papers), Bariatric Surgery and Outcomes (2 papers) and Adipose Tissue and Metabolism (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (181 citations), Endocrine and Autonomic Systems (62 citations), Physiology (141 citations), Epidemiology (119 citations) and Cellular and Molecular Neuroscience (66 citations). Sarah Will has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Mylène Perreault, James L. Trevaskis, Stephanie Oldham, James F. Tobin, Steven J. Kirincich, Christopher J. Rhodes, Vipin Suri, Suyue Wang, Yanling Zhang and David V. Erbe. Their work appears in journals such as Molecular Metabolism, Diabetes, Endocrinology, Diabetes Obesity and Metabolism and Pharmaceutics.

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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