Ling Ma

50 papers receiving 935 citations

Peers

Ling Ma
Comparison fields: 5 of 120
  • Organic Chemistry 265
  • Aging 14
  • Developmental Neuroscience 25
  • Drug Discovery 1
  • Complementary and alternative medicine 41
Replace Josephine S. Modica-Napolitano with:
Josephine S. Modica-Napolitano United States
Lijuan Liu China
Scott E. Snyder United States
Mauro Cunha Xavier Pinto Brazil
Zhiyong He China
David Hevia Spain
Teresa Noel United States
Soosung Kang South Korea
Rongfeng Lan China
Shi‐Xian Deng United States
Ling Ma relative to Josephine S. Modica-Napolitano United States Josephine S. Modica-Napolitano's profile →
Citations per field
00.5×3.4×
Josephine S. Modica-Napolitano · 1×
Citations per year

Countries citing papers authored by Ling Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ling Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201262
2 200259
3 201156
4 200255
5 200849
6 201448
7 200541
8 200637
9 201437
10 201632
11 201830
12 202427
13 201324
14 201124
15 201422
16 200021
17 200720
18 201820
19 200519
20 201519

About Ling Ma

Ling Ma is a scholar working on Molecular Biology, Materials Chemistry, Organic Chemistry, Cellular and Molecular Neuroscience and Pharmacology, having authored 53 papers that have together received 952 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (5 papers), Nerve injury and regeneration (3 papers), Catalytic C–H Functionalization Methods (3 papers), Boron Compounds in Chemistry (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Neurogenesis and neuroplasticity mechanisms (2 papers) and Molecular Sensors and Ion Detection (2 papers). The work is most often cited by research in Organic Chemistry (265 citations), Aging (14 citations), Developmental Neuroscience (25 citations), Drug Discovery (1 citation) and Complementary and alternative medicine (41 citations). Ling Ma has collaborated with scholars based in China, United States and Saint Kitts and Nevis. Frequent co-authors include Wenbin Lin, M. Frederick Hawthorne, Peter S. White, George Sines, Qiao Cheng, Jinyi Xu, Jinhui Wu, Ziyuan Li, Hequan Yao and Zhe-Yu Chen. Their work appears in journals such as Journal of Neuroscience, Inorganic Chemistry, Bioorganic & Medicinal Chemistry Letters, Tetrahedron Letters and Organic & Biomolecular Chemistry.

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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