Mamoru Takeda

6.1k citations
179 papers · 4.7k indexed · h-index 35

Impact in

Papers in

Mamoru Takeda

175 papers receiving 4.6k citations

Peers

Mamoru Takeda
Comparison fields: 5 of 128
  • Cellular and Molecular Neuroscience 1.7k
  • Physiology 2.2k
  • Sensory Systems 356
  • Neurology 418
  • Endocrine and Autonomic Systems 312
Replace Alfredo Ribeiro‐da‐Silva with:
Alfredo Ribeiro‐da‐Silva Canada
Kyungsoon Chung United States
Megumu Yoshimura Japan
Hiroshi Baba Japan
Luc Jasmin United States
Linda S. Sorkin United States
Fernando Cerveró United Kingdom
Rohini Kuner Germany
Temugin Berta United States
Michael Costigan United States
Mamoru Takeda relative to Alfredo Ribeiro‐da‐Silva Canada Alfredo Ribeiro‐da‐Silva's profile →
Citations per field
00.5×10×
Alfredo Ribeiro‐da‐Silva · 1×
Citations per year

Countries citing papers authored by Mamoru Takeda

Since Specialization
Citations

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

Fields of papers citing papers by Mamoru Takeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20247
3 20243
4 20237
5 20231
6 20233
7 201767
8 201532
9 20108
10 20061
11
Preferred Retinal Locus and Visual Acuity in Eyes With Macular Disease
20061
12 200619
13 200421
14 200414
15 20031
16 20012
17 19998
18 1997117
19 199613
20
[Effect of anticancer agents on rat prostate. Evaluation of organ weight, histological finding and 5 alpha-reductase activities].
19851

About Mamoru Takeda

Mamoru Takeda is a scholar working on Cellular and Molecular Neuroscience, Physiology, Sensory Systems, Equine and Endocrine and Autonomic Systems, having authored 179 papers that have together received 4.7k indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (97 papers), Neuropeptides and Animal Physiology (41 papers), Ion channel regulation and function (41 papers), Neuroscience and Neuropharmacology Research (29 papers), Neuroscience of respiration and sleep (15 papers), Botulinum Toxin and Related Neurological Disorders (14 papers), Comparative Animal Anatomy Studies (12 papers) and Biochemical effects in animals (11 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.7k citations), Physiology (2.2k citations), Sensory Systems (356 citations), Neurology (418 citations) and Endocrine and Autonomic Systems (312 citations). Mamoru Takeda has collaborated with scholars based in Japan, New Zealand and United States. Frequent co-authors include Shigeji Matsumoto, Masayuki Takahashi, Masanori Nasu, Takeshi Tanimoto, S. Matsumoto, Jun Kadoi, Junichi Kitagawa, Mizuho Ikeda, Tsuyoshi Tanimoto and Koichi Iwata. Their work appears in journals such as Annals of Anatomy - Anatomischer Anzeiger, Neuroscience, Molecular Pain, Brain Research and Neuroscience 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.

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