Donghai Dai

1.5k citations
50 papers · 1.2k · h-index 21

Impact in

Papers in

Donghai Dai

50 papers receiving 1.2k citations

Peers

Donghai Dai
Comparison fields: 5 of 81
  • Obstetrics and Gynecology 269
  • Reproductive Medicine 229
  • Genetics 372
  • Cancer Research 155
  • Immunology 211
Replace Norio Takamoto with:
Norio Takamoto Japan
Tianjie Shen United States
Yu Zheng China
David S. Loose‐Mitchell United States
Jeannine Villella United States
Virginia Novaro Argentina
Armina A. Kazi United States
Masayuki Futagami Japan
Yoko Tateishi Japan
Aurelia Vattai Germany
Donghai Dai relative to Norio Takamoto Japan Norio Takamoto's profile →
Citations per field
00.5×2.6×
Norio Takamoto · 1×
Citations per year

Countries citing papers authored by Donghai Dai

Since Specialization
Citations

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

Fields of papers citing papers by Donghai Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013143
2
Progesterone inhibits human endometrial cancer cell growth and invasiveness: down-regulation of cellular adhesion molecules through progesterone B receptors.
2002135
3 200679
4 201460
5 200352
6 200451
7 200447
8 200841
9 200139
10 201436
11 200035
12 199733
13 200733
14 201631
15 201230
16 200527
17 201327
18 200426
19 199926
20 200525

About Donghai Dai

Donghai Dai is a scholar working on Genetics, Molecular Biology, Oncology, Cancer Research and Immunology, having authored 50 papers that have together received 1.2k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (16 papers), Reproductive System and Pregnancy (8 papers), Cancer Genomics and Diagnostics (7 papers), Endometrial and Cervical Cancer Treatments (6 papers), Endometriosis Research and Treatment (5 papers), Congenital heart defects research (5 papers), Ovarian cancer diagnosis and treatment (3 papers) and Cancer-related Molecular Pathways (3 papers). The work is most often cited by research in Obstetrics and Gynecology (269 citations), Reproductive Medicine (229 citations), Genetics (372 citations), Cancer Research (155 citations) and Immunology (211 citations). Donghai Dai has collaborated with scholars based in United States and China. Frequent co-authors include Kimberly K. Leslie, Thomas F. Ogle, Douglas M. Wolf, Elizabeth S. Litman, Michael J. White, Eric R. Prossnitz, Philip George, Jeffrey B. Arterburn, Harriet O. Smith and Helen J. Hathaway. Their work appears in journals such as Gynecologic Oncology, Biology of Reproduction, Journal of Clinical Oncology, International Journal of Gynecological Cancer and OncoTargets and Therapy.

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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