Ling Ma

3.9k citations
17 papers · 388 · h-index 11

Impact in

    • Cancer-related Molecular Pathways
    • PARP inhibition in cancer therapy
    • HER2/EGFR in Cancer Research
    • Ovarian cancer diagnosis and treatment

Papers in

Ling Ma

16 papers receiving 381 citations

Peers

Ling Ma
Comparison fields: 5 of 61
  • Oncology 176
  • Reproductive Medicine 48
  • Pulmonary and Respiratory Medicine 177
  • Cancer Research 52
  • Obstetrics and Gynecology 25
Replace Lauriane Eberst with:
Lauriane Eberst France
Paulina Antosik Poland
Kyriaki Pliarchopoulou Greece
John Floyd United States
Mancheng Gong China
Yi-Wen Chang Taiwan
D. Mirchandani United States
Sheeba Jacob India
C Villena-Heinsen Germany
C. P. Carden United Kingdom
Ling Ma relative to Lauriane Eberst France Lauriane Eberst's profile →
Citations per field
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Lauriane Eberst · 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

17 of 17 papers shown
#Work
1 201986
2 201664
3 199547
4 201933
5 202128
6 202125
7 201621
8 202217
9 202014
10 201613
11 201412
12 202210
13 20216
14 20215
15 20234
16 20213
17 20190

About Ling Ma

Ling Ma is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Molecular Biology, Reproductive Medicine and Cancer Research, having authored 17 papers that have together received 388 indexed citations. Recurring topics across this work include PARP inhibition in cancer therapy (4 papers), Advanced Breast Cancer Therapies (4 papers), Cancer Treatment and Pharmacology (3 papers), Ovarian cancer diagnosis and treatment (3 papers), Breast Cancer Treatment Studies (2 papers), Nanoplatforms for cancer theranostics (2 papers), Chronic Lymphocytic Leukemia Research (2 papers) and Endometrial and Cervical Cancer Treatments (2 papers). The work is most often cited by research in Oncology (176 citations), Reproductive Medicine (48 citations), Pulmonary and Respiratory Medicine (177 citations), Cancer Research (52 citations) and Obstetrics and Gynecology (25 citations). Ling Ma has collaborated with scholars based in United States, Croatia and Serbia. Frequent co-authors include Kristian Berg, Živilė Lukšiené, Johan Moan, Michael Danso, Sharon Wilks, Željko Vojnović, Antoinette R. Tan, Lazar Popović, Gail S. Wright and Donald Richards. Their work appears in journals such as Journal of Clinical Oncology, Cancer, Clinical Cancer Research, Journal of Materials Chemistry B and Medicine.

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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