Tomoko Asakawa

1.1k citations
17 papers · 885 indexed · h-index 14
Topics
Neuropeptides and Animal Physiology (11 papers)Peptidase Inhibition and Analysis (9 papers)Diabetes Treatment and Management (9 papers)
Partner nations
JapanUnited States

In The Last Decade

Tomoko Asakawa

17 papers receiving 862 citations

Peers

Tomoko Asakawa
Comparison fields: 5 of 74
  • Endocrinology, Diabetes and Metabolism 450
  • Molecular Biology 385
  • Oncology 303
  • Cellular and Molecular Neuroscience 243
  • Surgery 171
Replace Jing-Ya Li with:
Jing-Ya Li China
Robert W. Wiethe United States
Maria E. Due‐Hansen Denmark
Erik T. Bodor United States
Yoshiharu Hayashi Japan
Seiji Okazaki Japan
Elwood Largis United States
Amal M. Boctor United States
André Crastes de Paulet France
Tomoko Asakawa relative to Jing-Ya Li China Jing-Ya Li's profile →
Citations per field
00.5×4.2×
Jing-Ya Li · 1×
Citations per year

Countries citing papers authored by Tomoko Asakawa

Since Specialization
Citations

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

Fields of papers citing papers by Tomoko Asakawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoko Asakawa

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoko Asakawa. A scholar is included among the top collaborators of Tomoko Asakawa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tomoko Asakawa. Tomoko Asakawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 8
2 10
3 18
4 11
5 17
6 14
7 28
8 40
9 23
10 14
11 34
12 81
13 63
14 18
15 326
16 103
17 77

About Tomoko Asakawa

Tomoko Asakawa is a scholar working on Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism and Endocrine and Autonomic Systems, having authored 17 papers that have together received 885 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (11 papers), Peptidase Inhibition and Analysis (9 papers) and Diabetes Treatment and Management (9 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (450 citations), Cellular and Molecular Neuroscience (243 citations) and Oncology (303 citations). Tomoko Asakawa has collaborated with scholars based in Japan and United States. Frequent co-authors include Koji Takeuchi, Daniel B. Kassel, Lihong Shi, Hideyuki Tomitori, Anthony J. Michael, Keiko Kashiwagi, Kazuei Igarashi, Osamu Kataoka, Zhiyuan Zhang and Marc Navre. Their work appears in journals such as Biochemical Journal, Journal of Medicinal Chemistry and British Journal of Pharmacology.

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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