G. Schmitz

426 citations
18 papers · 298 · h-index 10

Impact in

Papers in

    • Lipoproteins and Cardiovascular Health 7
    • Cholesterol and Lipid Metabolism 2
    • Cancer, Lipids, and Metabolism 6

G. Schmitz

17 papers receiving 292 citations

Peers

G. Schmitz
Comparison fields: 5 of 65
  • Endocrinology, Diabetes and Metabolism 104
  • Cancer Research 48
  • Surgery 110
  • Pharmacology 16
  • Biochemistry 13
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Praveen V. Manthena United States
Eva Xepapadaki Greece
Bożena Sosnowska Poland
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Citations per field
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Citations per year

Countries citing papers authored by G. Schmitz

Since Specialization
Citations

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

Fields of papers citing papers by G. Schmitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 1984120
2 200738
3 199324
4
Variable expression of hypercholesterolemia in Apolipoprotein E2* (Arg136 --> Cys) heterozygotes.
200019
5
Cell surface distribution and intracellular fate of human beta-very low density lipoprotein in cultured peritoneal mouse macrophages: a cytochemical and immunocytochemical study.
198715
6 202113
7 201612
8 201611
9 198111
10 20009
11
Role of the high density lipoprotein-receptor cycle in macrophage-cholesterol metabolism.
19869
12 20216
13 19954
14
Receptor domains in the plasma membrane of cultured mouse peritoneal macrophages.
19853
15 20102
16 20251
17 20051
18 20220

About G. Schmitz

G. Schmitz is a scholar working on Surgery, Cancer Research, Plant Science, Endocrinology, Diabetes and Metabolism and Immunology, having authored 18 papers that have together received 298 indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (7 papers), Cancer, Lipids, and Metabolism (6 papers), Cassava research and cyanide (3 papers), Banana Cultivation and Research (3 papers), Pharmacogenetics and Drug Metabolism (2 papers), Inflammatory mediators and NSAID effects (2 papers), Cholesterol and Lipid Metabolism (2 papers) and Atherosclerosis and Cardiovascular Diseases (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (104 citations), Cancer Research (48 citations), Surgery (110 citations), Pharmacology (16 citations) and Biochemistry (13 citations). G. Schmitz has collaborated with scholars based in Brazil, Germany and United States. Frequent co-authors include H J Menzel, G. Aßmann, H. Schulte, Horst Robenek, C.‐J. Estler, R. Poledne, Juliana Heidler, SR Bornstein, Gerd A. Müller and Henning Morawietz. Their work appears in journals such as Scientia Horticulturae, Physiological Research, Life, Clinical Chemistry and Starch - Stärke.

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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