HU Ren-ming

1.4k citations
31 papers · 897 indexed · h-index 13

Impact in

Papers in

HU Ren-ming

31 papers receiving 875 citations

Peers

HU Ren-ming
Comparison fields: 5 of 94
  • Cell Biology 162
  • Endocrinology, Diabetes and Metabolism 123
  • Genetics 202
  • Molecular Biology 476
  • Endocrine and Autonomic Systems 42
Replace Kenta Magoori with:
Kenta Magoori Japan
Leah M. Helvering United States
Tomoki Okazaki Japan
Dennis Sohn Germany
Raymonde Bredoux France
Lynn Cheatham United States
Nathalie Danièle France
Andrea N. Moor United States
Hisashi Oishi Japan
Mildred Acevedo‐Duncan United States
HU Ren-ming relative to Kenta Magoori Japan Kenta Magoori's profile →
Citations per field
00.5×1.5×1.9×
Kenta Magoori · 1×
Citations per year

Countries citing papers authored by HU Ren-ming

Since Specialization
Citations

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

Fields of papers citing papers by HU Ren-ming

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by HU Ren-ming. 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 HU Ren-ming. The network helps show where HU Ren-ming may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20245
3 202318
4 20236
5 202011
6 201416
7 20121
8 2010102
9 201011
10 201028
11 200948
12 20098
13 200865
14
Evaluation of insulin secretion and insulin sensitivity in the selection of hypoglycemic drugs——a multicentre clinical study
20071
15 200775
16 200733
17
Correlation between polymorphism of sulfonylurea receptor 1 gene and type 2 diabetes
20032
18 20029
19
Molecular genetic study on a pedigree with three sisters suffering from P450c 17alpha deficiency
20001
20 199842

About HU Ren-ming

HU Ren-ming is a scholar working on Cancer Research, Endocrinology, Diabetes and Metabolism, Molecular Biology, Cell Biology and Pharmacology, having authored 31 papers that have together received 897 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (5 papers), Microtubule and mitosis dynamics (4 papers), Ubiquitin and proteasome pathways (4 papers), Angiogenesis and VEGF in Cancer (3 papers), Cancer-related Molecular Pathways (3 papers), Genomics and Chromatin Dynamics (3 papers), Mitochondrial Function and Pathology (2 papers) and Nitric Oxide and Endothelin Effects (2 papers). The work is most often cited by research in Cell Biology (162 citations), Endocrinology, Diabetes and Metabolism (123 citations), Genetics (202 citations), Molecular Biology (476 citations) and Endocrine and Autonomic Systems (42 citations). HU Ren-ming has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Ellis R. Levin, Ali Pedram, Mahnaz Razandi, Bruce A. Prins, Elżbieta Biesiada, Xuebiao Yao, Bin Lü, Wenbai Zhou, Andrew Shaw and Tina Rönn. Their work appears in journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications, Cell Metabolism, Journal of Endocrinology and Endocrinology.

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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