Masato Odawara

3.3k total citations
112 papers, 1.9k citations indexed

About

Masato Odawara is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Surgery. According to data from OpenAlex, Masato Odawara has authored 112 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Endocrinology, Diabetes and Metabolism, 38 papers in Molecular Biology and 17 papers in Surgery. Recurrent topics in Masato Odawara's work include Diabetes Treatment and Management (41 papers), Diabetes Management and Research (39 papers) and Metabolism, Diabetes, and Cancer (21 papers). Masato Odawara is often cited by papers focused on Diabetes Treatment and Management (41 papers), Diabetes Management and Research (39 papers) and Metabolism, Diabetes, and Cancer (21 papers). Masato Odawara collaborates with scholars based in Japan, United States and Switzerland. Masato Odawara's co-authors include Kamejiro Yamashita, Takashi Kadowaki, Yoichi Tachi, Takashi Miwa, Masato Kasuga, Hiroyuki Sakai, Takeshi Imaoka, Naoko Tajima, Jun‐ichiro Miyagawa and Noriyuki Iwamoto and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and The Lancet.

In The Last Decade

Masato Odawara

108 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Masato Odawara Japan 25 923 642 419 198 193 112 1.9k
Patrizia Guarini Italy 28 530 0.6× 853 1.3× 437 1.0× 173 0.9× 112 0.6× 79 2.4k
Silvia Pinach Italy 24 549 0.6× 620 1.0× 389 0.9× 214 1.1× 92 0.5× 44 1.9k
Gianluca Bardini Italy 20 1.1k 1.1× 491 0.8× 432 1.0× 123 0.6× 90 0.5× 40 1.6k
Marisa Passarelli Brazil 27 697 0.8× 469 0.7× 483 1.2× 97 0.5× 402 2.1× 105 1.8k
Anna Valerio Italy 25 687 0.7× 558 0.9× 455 1.1× 172 0.9× 121 0.6× 59 1.9k
Maria Lúcia Corrêa‐Giannella Brazil 27 580 0.6× 528 0.8× 405 1.0× 185 0.9× 214 1.1× 122 1.9k
Changyu Pan China 27 1.7k 1.8× 565 0.9× 334 0.8× 173 0.9× 57 0.3× 95 2.4k
Sylvie Picard France 20 368 0.4× 389 0.6× 241 0.6× 116 0.6× 159 0.8× 61 1.5k
Andrzej S. Januszewski Australia 25 580 0.6× 542 0.8× 192 0.5× 175 0.9× 451 2.3× 84 2.2k
Steven J. Hurel United Kingdom 26 619 0.7× 541 0.8× 309 0.7× 331 1.7× 66 0.3× 49 1.8k

Countries citing papers authored by Masato Odawara

Since Specialization
Citations

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

Fields of papers citing papers by Masato Odawara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masato Odawara

This figure shows the co-authorship network connecting the top 25 collaborators of Masato Odawara. A scholar is included among the top collaborators of Masato Odawara 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 Masato Odawara. Masato Odawara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Abe, Hironori, Junko Sasaki, Takashi Miwa, et al.. (2022). Machine learning approach to predict subtypes of primary aldosteronism is helpful to estimate indication of adrenal vein sampling. High Blood Pressure & Cardiovascular Prevention. 29(4). 375–383. 2 indexed citations
3.
Sasaki, Junko, et al.. (2021). A cross-sectional study of the correlation between diabetic therapy and serum zinc concentrations. Diabetology International. 13(1). 177–187. 3 indexed citations
4.
Kobayashi, Masakazu, Junji Akaki, Kiyofumi Ninomiya, et al.. (2020). Dose-Dependent Suppression of Postprandial Hyperglycemia and Improvement of Blood Glucose Parameters by Salacia chinensis Extract: Two Randomized, Double-Blind, Placebo-Controlled Studies. Journal of Medicinal Food. 24(1). 10–17. 8 indexed citations
5.
Ishikawa, Takuya, Takashi Miwa, Hiroyuki Sakai, et al.. (2020). A Novel Homozygous Mutation of Thyroid Peroxidase Gene Abolishes a Disulfide Bond Leading to Congenital Hypothyroidism. International Journal of Endocrinology. 2020. 1–8. 2 indexed citations
6.
Yamada, Hirotsugu, Atsushi Tanaka, Kenya Kusunose, et al.. (2017). Effect of sitagliptin on the echocardiographic parameters of left ventricular diastolic function in patients with type 2 diabetes: a subgroup analysis of the PROLOGUE study. Cardiovascular Diabetology. 16(1). 63–63. 49 indexed citations
7.
Komada, Yoko, et al.. (2017). Prevalence, symptomatic features, and factors associated with sleep disturbance/insomnia in Japanese patients with type-2 diabetes. Neuropsychiatric Disease and Treatment. Volume 13. 1873–1880. 44 indexed citations
8.
Kozlovski, Plamen, Viswanathan Mohan, Valentina Lukashevich, et al.. (2016). Effect of race and ethnicity on vildagliptin efficacy: A pooled analysis of phase II and III studies. Diabetes Obesity and Metabolism. 19(3). 429–435. 11 indexed citations
9.
Odawara, Masato, et al.. (2015). Effects of vildagliptin as add-on treatment in patients with type 2 diabetes mellitus: insights from long-term clinical studies in Japan. Journal of Diabetes & Metabolic Disorders. 15(1). 21–21. 3 indexed citations
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Odawara, Masato, Tetsuya Ohtani, & Takashi Kadowaki. (2012). Dosing of Insulin Glargine to Achieve the Treatment Target in Japanese Type 2 Diabetes on a Basal Supported Oral Therapy Regimen in Real Life: ALOHA Study Subanalysis. Diabetes Technology & Therapeutics. 14(7). 635–643. 24 indexed citations
14.
Kario, Kazuomi, Masato Odawara, Kenjiro Kimura, & Koichi Node. (2011). Nearly Half of Uncontrolled Hypertensive Patients could be Controlled by High-dose Titration of Amlodipine in the Clinical Setting: The ACHIEVE Study. Current Hypertension Reviews. 7(2). 102–110. 3 indexed citations
15.
Taniguchi, Jun, et al.. (2009). A Case of Insulin Autoimmune Syndrome Suspected of Showing False Positive Results for Insulin Receptor Antibody. 52(6). 449–455. 2 indexed citations
16.
Shima, Yukio, Kōji Nakanishi, Masato Odawara, Tetsuro Kobayashi, & Hidehiko Ohta. (2003). Association of the SNP-19 genotype 22 in the calpain-10 gene with elevated body mass index and hemoglobin A1c levels in Japanese. Clinica Chimica Acta. 336(1-2). 89–96. 54 indexed citations
17.
Odawara, Masato. (1996). Involvement of Mitochondrial Gene Abnormalities in the Pathogenesis of Diabetes Mellitus. Annals of the New York Academy of Sciences. 786(1). 72–81. 5 indexed citations
18.
Asano, Michiko, Yukichi Okuda, Takashi Yamaoka, et al.. (1995). Report of a Case of Pancreatic Diabetes with Severe Zinc Deficiency. 38(7). 517–522. 3 indexed citations
19.
Kim, Hyungjun, Hiroaki Kadowaki, H Sakura, et al.. (1992). Detection of mutations in the insulin receptor gene in patients with insulin resistance by analysis of single-stranded conformational polymorphisms. Diabetologia. 35(3). 261–266. 56 indexed citations
20.
Yamamoto, Ritsuko, Teruo Shiba, Kazuyuki Tobe, et al.. (1990). Defect in Tyrosine Kinase Activity of the Insulin Receptor from a Patient with Insulin Resistance and Acanthosis Nigricans*. The Journal of Clinical Endocrinology & Metabolism. 70(4). 869–878. 10 indexed citations

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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