Mamoru Urabe

35 papers receiving 882 citations

Peers

Mamoru Urabe
Comparison fields: 5 of 90
  • Reproductive Medicine 161
  • Endocrinology, Diabetes and Metabolism 305
  • Genetics 472
  • Obstetrics and Gynecology 113
  • Behavioral Neuroscience 44
Replace Antonella Caruso with:
Antonella Caruso Italy
Fernándo López-Barrera Mexico
Toru Momoi Japan
Harry J. Hirsch Israel
E. Bucht Sweden
J. Beacham United Kingdom
Renata I. Dmitrieva Russia
P. Knapstein Germany
Mélissa Pelletier Canada
Julia Bársony United States
Mamoru Urabe relative to Antonella Caruso Italy Antonella Caruso's profile →
Citations per field
00.5×1.5×2.3×
Antonella Caruso · 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 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1989183
2 1999148
3 199587
4 199374
5 198968
6 199644
7 198943
8 199630
9 200026
10
Immunohistochemical localisation of aromatase and its correlation with progesterone receptors in ovarian epithelial tumours.
199626
11 200021
12 198720
13 200119
14 198616
15
Menopause and hyperlipidemia: pravastatin lowers lipid levels without decreasing endogenous estrogens.
199314
16 199011
17 201411
18 198911
19 201710
20 19909

About Mamoru Urabe

Mamoru Urabe is a scholar working on Genetics, Molecular Biology, Endocrinology, Diabetes and Metabolism, Reproductive Medicine and Pathology and Forensic Medicine, having authored 35 papers that have together received 927 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (18 papers), Menopause: Health Impacts and Treatments (7 papers), Endometriosis Research and Treatment (4 papers), Effects and risks of endocrine disrupting chemicals (4 papers), Steroid Chemistry and Biochemistry (3 papers), Phytoestrogen effects and research (3 papers), Uterine Myomas and Treatments (3 papers) and Ovarian cancer diagnosis and treatment (2 papers). The work is most often cited by research in Reproductive Medicine (161 citations), Endocrinology, Diabetes and Metabolism (305 citations), Genetics (472 citations), Obstetrics and Gynecology (113 citations) and Behavioral Neuroscience (44 citations). Mamoru Urabe has collaborated with scholars based in Japan. Frequent co-authors include Hideo Honjo, Hiroji Okada, Takara Yamamoto, Jo Kitawaki, Takara Yamamoto, Yoshio Ogino, Jinsuke Yasuda, Toshio Nambara, Jun Hashi­moto and Makoto Yoshioka. Their work appears in journals such as The Journal of Steroid Biochemistry and Molecular Biology, European Journal of Endocrinology, Steroids, Gynecologic Oncology and Archives of Gynecology and Obstetrics.

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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