Jun Mori

68 papers receiving 2.2k citations

Peers

Jun Mori
Comparison fields: 5 of 105
  • Cardiology and Cardiovascular Medicine 805
  • Endocrinology, Diabetes and Metabolism 404
  • Physiology 421
  • Geriatrics and Gerontology 49
  • Molecular Biology 765
Replace Nirmal Parajuli with:
Nirmal Parajuli Canada
Anton J.M. Roks Netherlands
Fernando P. Dominici Argentina
Cinzia Perrino Italy
Subhash K. Das Canada
Ivan Luptak United States
John Fassett United States
Yi Pan Canada
Xiaoxiang Yan China
Christian Riehle United States
Jun Mori relative to Nirmal Parajuli Canada Nirmal Parajuli's profile →
Citations per field
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Nirmal Parajuli · 1×
Citations per year

Countries citing papers authored by Jun Mori

Since Specialization
Citations

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

Fields of papers citing papers by Jun Mori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013365
2 2015206
3 2014163
4 2012145
5 2013138
6 2012119
7 2006113
8 2014112
9 201561
10 201957
11 201354
12 200650
13 201747
14 202239
15 201737
16 200536
17 201235
18 200834
19 200530
20 202028

About Jun Mori

Jun Mori is a scholar working on Molecular Biology, Physiology, Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Surgery, having authored 71 papers that have together received 2.2k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (11 papers), Growth Hormone and Insulin-like Growth Factors (8 papers), Renin-Angiotensin System Studies (4 papers), Pancreatic function and diabetes (4 papers), Cardiovascular Disease and Adiposity (4 papers), Cardiovascular Function and Risk Factors (4 papers), Microtubule and mitosis dynamics (3 papers) and Neonatal Health and Biochemistry (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (805 citations), Endocrinology, Diabetes and Metabolism (404 citations), Physiology (421 citations), Geriatrics and Gerontology (49 citations) and Molecular Biology (765 citations). Jun Mori has collaborated with scholars based in Japan, Canada and United States. Frequent co-authors include Gary D. Lopaschuk, Gavin Y. Oudit, Natasha Fillmore, Vaibhav B. Patel, Ratnadeep Basu, Cory S. Wagg, Osama Abo Alrob, Tharmarajan Ramprasath, Brent A. McLean and Subhash K. Das. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, PLoS ONE, American Journal of Physiology-Endocrinology and Metabolism, Nutrition & Metabolism and Diabetes.

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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