Junlong Ma

44 papers receiving 354 citations

Peers

Junlong Ma
Comparison fields: 5 of 87
  • Nephrology 19
  • Toxicology 8
  • Complementary and alternative medicine 15
  • Physiology 35
  • Organic Chemistry 39
Replace Hina Khan with:
Hina Khan United States
Yuying Zhou China
Christian Orlowski Australia
Yi‐Hsuan Lin Taiwan
Hanming Wang China
Lu Xiao China
Junhao Jiang China
Dhvanit I. Shah India
Sadaf Nezamoleslami Iran
Jaehwa Choi United States
Junlong Ma relative to Hina Khan United States Hina Khan's profile →
Citations per field
00.5×3.3×
Hina Khan · 1×
Citations per year

Countries citing papers authored by Junlong Ma

Since Specialization
Citations

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

Fields of papers citing papers by Junlong Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201937
2 202032
3 202428
4 202025
5 202320
6 202119
7 201919
8 202015
9
Clinical application of neutrophil gelatinase-associated lipocalin in the revised chronic kidney disease classification.
201414
10 201911
11 202410
12 20139
13 20129
14 20258
15 20238
16 20247
17 20247
18 20256
19 20136
20 20256

About Junlong Ma

Junlong Ma is a scholar working on Organic Chemistry, Physiology, Electrical and Electronic Engineering, Molecular Biology and Oncology, having authored 52 papers that have together received 359 indexed citations. Recurring topics across this work include Synthesis and Properties of Aromatic Compounds (5 papers), Pain Mechanisms and Treatments (4 papers), Luminescence and Fluorescent Materials (3 papers), Organic Electronics and Photovoltaics (2 papers), Solar Thermal and Photovoltaic Systems (2 papers), Conducting polymers and applications (2 papers), Urinary Tract Infections Management (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Nephrology (19 citations), Toxicology (8 citations), Complementary and alternative medicine (15 citations), Physiology (35 citations) and Organic Chemistry (39 citations). Junlong Ma has collaborated with scholars based in China, Philippines and Singapore. Frequent co-authors include Heng Chen, Guoping Yang, Zhuo Chen, Gaoyun Hu, Qianbin Li, Chengbin Wang, Pan Huang, Guo-Ming Shen, Fei Huang and Jie Yang. Their work appears in journals such as Journal of Atherosclerosis and Thrombosis, Frontiers in Immunology, Angewandte Chemie International Edition, ChemCatChem and BMC Medical Research Methodology.

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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