Jun Long

20 papers receiving 324 citations

Peers

Jun Long
Comparison fields: 5 of 81
  • Infectious Diseases 89
  • Physiology 99
  • Pulmonary and Respiratory Medicine 88
  • Nutrition and Dietetics 32
  • Epidemiology 66
Replace Hai Lee Chung with:
Hai Lee Chung South Korea
Danny Laura Gomes Fagundes Brazil
David Alonso Spain
Chanchai Sittipunt Thailand
H. G. de Vries Netherlands
Marcelo Radisic Argentina
Jonathan Cohen United Kingdom
Man Tian China
Katie Dunne Ireland
Livingstone Chishimba United Kingdom
Jun Long relative to Hai Lee Chung South Korea Hai Lee Chung's profile →
Citations per field
00.5×1.5×2.1×
Hai Lee Chung · 1×
Citations per year

Countries citing papers authored by Jun Long

Since Specialization
Citations

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

Fields of papers citing papers by Jun Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201466
2 198465
3 201550
4 201147
5 201124
6 201315
7 202413
8 201511
9 201811
10 20187
11 20164
12 20254
13 20254
14 20243
15 20183
16 19853
17 20252
18 20241
19 19801
20 20241

About Jun Long

Jun Long is a scholar working on Complementary and Manual Therapy, Nephrology, Pulmonary and Respiratory Medicine, Internal Medicine and Hepatology, having authored 25 papers that have together received 335 indexed citations. Recurring topics across this work include Kidney Stones and Urolithiasis Treatments (5 papers), Therapeutic Uses of Natural Elements (4 papers), Liver Disease Diagnosis and Treatment (3 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers), Nutritional Studies and Diet (2 papers), Bacteriophages and microbial interactions (2 papers), Neonatal Health and Biochemistry (2 papers) and Chronic Obstructive Pulmonary Disease (COPD) Research (2 papers). The work is most often cited by research in Infectious Diseases (89 citations), Physiology (99 citations), Pulmonary and Respiratory Medicine (88 citations), Nutrition and Dietetics (32 citations) and Epidemiology (66 citations). Jun Long has collaborated with scholars based in China, South Korea and Australia. Frequent co-authors include M X Fitzgerald, Duan Wang, Fan Yang, Liang‐Yi Si, Gang Tang, Shaofang Zhang, Xiaoyan Fang, Dayong Gu, Jianan He and Hua‐Jian Xu. Their work appears in journals such as Frontiers in Nutrition, Bio-Medical Materials and Engineering, Journal of Agricultural and Food Chemistry, Journal of Clinical Laboratory Analysis and Frontiers in Forests and Global Change.

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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