G C Ness

1.4k citations
29 papers · 1.3k · h-index 21

Impact in

  • Surgery top 5%
    • Cholesterol and Lipid Metabolism
    • Lipoproteins and Cardiovascular Health
    • Lipid metabolism and biosynthesis

Papers in

    • Plant biochemistry and biosynthesis 7
    • Peroxisome Proliferator-Activated Receptors 5
    • Cholesterol and Lipid Metabolism 13
    • Lipoproteins and Cardiovascular Health 3

G C Ness

29 papers receiving 1.2k citations

Peers

G C Ness
Comparison fields: 5 of 77
  • Surgery 725
  • Biochemistry 120
  • Endocrinology, Diabetes and Metabolism 212
  • Molecular Biology 724
  • Pharmacology 87
Replace George W. Melchior with:
George W. Melchior United States
J M Dietschy United States
J G Heider United States
Suzanna E. Dana United States
Harry W. Chen United States
D W Bilheimer United States
M J Bamberger United States
Bruce J. Auerbach United States
Mary C. Ritter United States
Clay T. Cramer United States
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Citations per field
00.5×2.8×
George W. Melchior · 1×
Citations per year

Countries citing papers authored by G C Ness

Since Specialization
Citations

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

Fields of papers citing papers by G C Ness

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G C Ness. 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 G C Ness. The network helps show where G C Ness may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199098
2 198494
3 199285
4 198869
5 199166
6 198966
7 199561
8 198661
9 198560
10 199559
11 199156
12 199454
13 197953
14 199452
15 199451
16 199448
17 199033
18 199029
19 199128
20 198522

About G C Ness

G C Ness is a scholar working on Molecular Biology, Surgery, Computational Theory and Mathematics, Endocrinology, Diabetes and Metabolism and Pharmacology, having authored 29 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (13 papers), Computational Drug Discovery Methods (7 papers), Plant biochemistry and biosynthesis (7 papers), Hormonal Regulation and Hypertension (5 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Metabolism and Genetic Disorders (3 papers), Pharmacogenetics and Drug Metabolism (3 papers) and Lipoproteins and Cardiovascular Health (3 papers). The work is most often cited by research in Surgery (725 citations), Biochemistry (120 citations), Endocrinology, Diabetes and Metabolism (212 citations), Molecular Biology (724 citations) and Pharmacology (87 citations). G C Ness has collaborated with scholars based in United States and India. Frequent co-authors include W. Scott Simonet, Sarah Shefer, G Salen, R. Kennedy Keller, G. Stephen Tint, Laura C. Pendleton, Zuohui Zhao, Clare E. Sample, Zhihong Zhao and A K Batta. Their work appears in journals such as Journal of Biological Chemistry, Archives of Biochemistry and Biophysics, Journal of Lipid Research, Journal of Clinical Investigation and Journal of Andrology.

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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