Phillip E. Williams

4.0k citations
110 papers · 3.3k indexed · h-index 36

Phillip E. Williams

108 papers receiving 3.1k citations

Peers

Phillip E. Williams
Comparison fields: 5 of 111
  • Endocrinology, Diabetes and Metabolism 1.1k
  • Endocrine and Autonomic Systems 417
  • Physiology 1.4k
  • Cell Biology 494
  • Clinical Biochemistry 200
Replace Doss W. Neal with:
Doss W. Neal United States
Carla Roberta de Oliveira Carvalho Brazil
N. Altszuler United States
R. A. Rizza United States
O. Schmitz Denmark
M. Vranić Canada
S. Efendić Sweden
Julio E. Ayala United States
J. P. Felber Switzerland
T. W. Balon United States
Phillip E. Williams relative to Doss W. Neal United States Doss W. Neal's profile →
Citations per field
00.5×1.5×1.8×
Doss W. Neal · 1×
Citations per year

Countries citing papers authored by Phillip E. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Phillip E. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201935
2 2015144
3 20151
4 20142
5 201147
6 20104
7 20094
8 20084
9 200613
10 200612
11 19981
12 199611
13 199455
14 199225
15 19914
16 199034
17 198953
18 198836
19 198821
20
The role of hyperglycemia in countering the action of glucagon on glucose production in conscious dogs
19811

About Phillip E. Williams

Phillip E. Williams is a scholar working on Endocrinology, Diabetes and Metabolism, Physiology, Cell Biology, Surgery and Behavioral Neuroscience, having authored 110 papers that have together received 3.3k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (44 papers), Diet and metabolism studies (38 papers), Metabolism, Diabetes, and Cancer (22 papers), Diabetes Management and Research (21 papers), Muscle metabolism and nutrition (19 papers), Diabetes Treatment and Management (18 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (13 papers) and Adipose Tissue and Metabolism (11 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.1k citations), Endocrine and Autonomic Systems (417 citations), Physiology (1.4k citations), Cell Biology (494 citations) and Clinical Biochemistry (200 citations). Phillip E. Williams has collaborated with scholars based in United States, Russia and Denmark. Frequent co-authors include Alan D. Cherrington, D. Borden Lacy, Naji N. Abumrad, W. W. Lacy, David H. Wasserman, Kareem Jabbour, Ralph W. Stevenson, Doss W. Neal, R. Tyler Frizzell and J E Liljenquist. Their work appears in journals such as American Journal of Physiology-Endocrinology and Metabolism, Diabetes, Metabolism, Journal of Clinical Investigation and Journal of Surgical Research.

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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