Daojun Mo

789 citations
19 papers · 642 · h-index 12

Impact in

Papers in

Daojun Mo

18 papers receiving 610 citations

Peers

Daojun Mo
Comparison fields: 5 of 71
  • Endocrinology, Diabetes and Metabolism 407
  • Rheumatology 73
  • Cardiology and Cardiovascular Medicine 60
  • Family Practice 4
  • Psychiatry and Mental health 28
Replace Jill H. Simmons with:
Jill H. Simmons United States
Alpesh Goyal India
Elaine Tham Australia
Joanne R. Julius United States
Wiam I. Hussein Saudi Arabia
Hamid Reza Nakhai-Pour Canada
Marilyn Tuttleman United States
Ahlia Sekkarie United States
Efstathios P. Papadakis Greece
Annette Settnes Denmark
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Citations per field
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Citations per year

Countries citing papers authored by Daojun Mo

Since Specialization
Citations

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

Fields of papers citing papers by Daojun Mo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2015108
2 200999
3 202065
4 201160
5 200954
6 200850
7 201548
8 201439
9 201336
10 201922
11 200520
12 200112
13 20068
14 20217
15 20246
16 20215
17 20252
18
Using Direct Standardization SAS® Macro for a Valid Comparison in Observational Studies
20081
19 20230

About Daojun Mo

Daojun Mo is a scholar working on Endocrinology, Diabetes and Metabolism, Rheumatology, Psychiatry and Mental health, Immunology and Statistics and Probability, having authored 19 papers that have together received 642 indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (7 papers), Rheumatoid Arthritis Research and Therapies (6 papers), Sexual function and dysfunction studies (2 papers), Biosimilars and Bioanalytical Methods (2 papers), Statistical Methods in Clinical Trials (1 paper), Fluoride Effects and Removal (1 paper), Adrenal Hormones and Disorders (1 paper) and Nutritional Studies and Diet (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (407 citations), Rheumatology (73 citations), Cardiology and Cardiovascular Medicine (60 citations), Family Practice (4 citations) and Psychiatry and Mental health (28 citations). Daojun Mo has collaborated with scholars based in United States, Germany and Spain. Frequent co-authors include Andrea F. Attanasio, Maureen J. Lage, Byron J. Hoogwerf, Jay Patrick Bae, David R. Nelson, Eva Marie Erfurth, Shlomo Melmed, Philippe Chanson, Alan G. Zimmermann and Christian Joseph Strasburger. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, The Journal of Rheumatology, ACR Open Rheumatology, Lara D. Veeken and International Journal of Impotence 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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