Mamoru Urabe

37 papers receiving 902 citations

Peers

Mamoru Urabe
Comparison fields: 5 of 91
  • Endocrinology, Diabetes and Metabolism 312
  • Reproductive Medicine 143
  • Genetics 422
  • Behavioral Neuroscience 47
  • Obstetrics and Gynecology 91
Replace Lihong Peng with:
Lihong Peng China
J Spranger Germany
J. Beacham United Kingdom
Julia Bársony United States
Atul R. Chopra United States
Fernándo López-Barrera Mexico
Toru Momoi Japan
Christine F. Conover United States
H. T. Keutmann United States
David Greenwald United States
Mamoru Urabe relative to Lihong Peng China Lihong Peng's profile →
Citations per field
00.5×5.2×
Lihong Peng · 1×
Citations per year

Countries citing papers authored by Mamoru Urabe

Since Specialization
Citations

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

Fields of papers citing papers by Mamoru Urabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1989201
2 1999154
3 199596
4 199376
5 198969
6 198945
7 199644
8 199633
9 200027
10
Immunohistochemical localisation of aromatase and its correlation with progesterone receptors in ovarian epithelial tumours.
199626
11 200021
12 200119
13 198617
14
Menopause and hyperlipidemia: pravastatin lowers lipid levels without decreasing endogenous estrogens.
199315
15 201412
16 199011
17 198911
18 201710
19 19909
20 20029

About Mamoru Urabe

Mamoru Urabe is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism, Molecular Biology, Reproductive Medicine and Pathology and Forensic Medicine, having authored 37 papers that have together received 965 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (19 papers), Menopause: Health Impacts and Treatments (8 papers), Endometriosis Research and Treatment (4 papers), Effects and risks of endocrine disrupting chemicals (4 papers), Phytoestrogen effects and research (4 papers), Uterine Myomas and Treatments (3 papers), Steroid Chemistry and Biochemistry (3 papers) and Cancer-related cognitive impairment studies (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (312 citations), Reproductive Medicine (143 citations), Genetics (422 citations), Behavioral Neuroscience (47 citations) and Obstetrics and Gynecology (91 citations). Mamoru Urabe has collaborated with scholars based in Japan. Frequent co-authors include Hideo Honjo, Hiroji Okada, Takara Yamamoto, Takara Yamamoto, Jo Kitawaki, Yoshio Ogino, Jinsuke Yasuda, Toshikazu Kubo, Jun Hashi­moto and Takeshi Yonezawa. Their work appears in journals such as The Journal of Steroid Biochemistry and Molecular Biology, European Journal of Endocrinology, Steroids, Gynecologic Oncology and Hormone and Metabolic 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.

Explore authors with similar magnitude of impact