Aya Kitamoto

1.6k citations
21 papers · 877 · h-index 14

Impact in

Papers in

Aya Kitamoto

21 papers receiving 868 citations

Peers

Aya Kitamoto
Comparison fields: 5 of 75
  • Cancer Research 180
  • Biological Psychiatry 25
  • Behavioral Neuroscience 32
  • Epidemiology 277
  • Endocrinology, Diabetes and Metabolism 124
Replace Kazumasa Isobe with:
Kazumasa Isobe Japan
Ning Bai China
Knut H. Lauritzen Norway
Soichi Takiguchi Japan
Kathrin Steib Germany
Saumyendra N. Sarkar United States
Nancy R. Stallings United States
Daniel Pisera Argentina
Yanyun Sun China
Junji Ichihara Japan
Aya Kitamoto relative to Kazumasa Isobe Japan Kazumasa Isobe's profile →
Citations per field
00.5×4.2×
Kazumasa Isobe · 1×
Citations per year

Countries citing papers authored by Aya Kitamoto

Since Specialization
Citations

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

Fields of papers citing papers by Aya Kitamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010160
2 2013154
3 2008112
4 201568
5 200961
6 201259
7 201454
8 201833
9 200531
10 201730
11 201724
12 200523
13 200722
14 201418
15 201312
16 20106
17 20105
18 20222
19
CDH13 Polymorphisms are associated with adiponectin levels and metabolic syndrome traits independently of visceral fat mass.
20191
20 20251

About Aya Kitamoto

Aya Kitamoto is a scholar working on Epidemiology, Molecular Biology, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Endocrinology, Diabetes and Metabolism, having authored 21 papers that have together received 877 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (6 papers), Neuroscience and Neuropharmacology Research (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Diet, Metabolism, and Disease (3 papers), Memory and Neural Mechanisms (3 papers), MicroRNA in disease regulation (3 papers), Adipose Tissue and Metabolism (3 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). The work is most often cited by research in Cancer Research (180 citations), Biological Psychiatry (25 citations), Behavioral Neuroscience (32 citations), Epidemiology (277 citations) and Endocrinology, Diabetes and Metabolism (124 citations). Aya Kitamoto has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Takuya Kitamoto, Atsushi Nakajima, Masato Yoneda, Kikuko Hotta, Toshio Kojima, Yasunori Fujita, Nanako Hamada, Yoshinori Nozawa, Masafumi Ito and Shoichi Masushige. Their work appears in journals such as Data in Brief, Hepatology Research, Neurochemical Research, Journal of Hepatology and Genes Brain & Behavior.

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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