Tianling Ding

409 citations
29 papers · 297 · h-index 9

Impact in

    • Mesenchymal stem cell research
    • Glioma Diagnosis and Treatment
    • Electrospun Nanofibers in Biomedical Applications

Papers in

    • CNS Lymphoma Diagnosis and Treatment 11
    • Glioma Diagnosis and Treatment 4
    • Chronic Lymphocytic Leukemia Research 2

Tianling Ding

28 papers receiving 295 citations

Peers

Tianling Ding
Comparison fields: 5 of 57
  • Genetics 49
  • Biomaterials 64
  • Neurology 60
  • Surgery 89
  • Pathology and Forensic Medicine 31
Replace Viktoryia Sidarovich with:
Viktoryia Sidarovich Italy
Daniele Boso Italy
Raphael Severino Bonadio Brazil
Maciej Kabat United States
Mònica Vilà-Ubach Spain
Robert Kuo United States
Daniel Levi Italy
Junsong Ye China
Lipi Shukla Australia
Joseph Neumeyer United States
Tianling Ding relative to Viktoryia Sidarovich Italy Viktoryia Sidarovich's profile →
Citations per field
00.5×3.8×
Viktoryia Sidarovich · 1×
Citations per year

Countries citing papers authored by Tianling Ding

Since Specialization
Citations

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

Fields of papers citing papers by Tianling Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016104
2 201225
3 202124
4 201819
5 201615
6 201112
7 202012
8 20229
9 20139
10 20228
11 20197
12 20207
13 20225
14
[Osteogenic and adipogenic differentiation of bone marrow-derived mesenchymal stem cells in patients with aplastic anemia].
20095
15 20235
16 20215
17 20214
18 20174
19 20203
20 20223

About Tianling Ding

Tianling Ding is a scholar working on Neurology, Genetics, Pathology and Forensic Medicine, Hematology and Immunology, having authored 29 papers that have together received 297 indexed citations. Recurring topics across this work include CNS Lymphoma Diagnosis and Treatment (11 papers), Lymphoma Diagnosis and Treatment (7 papers), Glioma Diagnosis and Treatment (4 papers), CAR-T cell therapy research (3 papers), Multiple Myeloma Research and Treatments (3 papers), Acute Myeloid Leukemia Research (2 papers), Chronic Lymphocytic Leukemia Research (2 papers) and MicroRNA in disease regulation (2 papers). The work is most often cited by research in Genetics (49 citations), Biomaterials (64 citations), Neurology (60 citations), Surgery (89 citations) and Pathology and Forensic Medicine (31 citations). Tianling Ding has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ning Sun, Feng Guo, Jianyi Zhang, Tong Chen, Chen Liu, Yishen Mao, Haiyan Chen, SF Chen, Chao Lü and Hui Yang. Their work appears in journals such as Journal of Clinical Oncology, Blood, Frontiers in Immunology, Tetrahedron and Biomarker 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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