Peng Wang

9.7k citations
219 papers · 5.9k indexed · 2 hit papers · h-index 40

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Immunology top 2%
    • Immunotherapy and Immune Responses

Papers in

    • Cancer-related molecular mechanisms research 27
    • MicroRNA in disease regulation 15
    • Cancer Immunotherapy and Biomarkers 19

Peng Wang

197 papers receiving 5.8k citations

Hit Papers

Peptide binding predictions for HLA DR, DP and DQ molecules 2010 · 526 citations
5262008202620142020200400600

Peers

Peng Wang
Comparison fields: 5 of 154
  • Cancer Research 1.2k
  • Immunology 1.1k
  • Molecular Biology 3.5k
  • Oncology 1.0k
  • Epidemiology 1.1k
Replace Ping‐Kun Zhou with:
Ping‐Kun Zhou China
Yan Chen China
Bing Xia China
Jie Xu China
Marc Ferrer United States
Farzin Farzaneh United Kingdom
Qun Lin China
Andrew V. Kossenkov United States
Xia Zhao China
Santanu Dasgupta United States
Peng Wang relative to Ping‐Kun Zhou China Ping‐Kun Zhou's profile →
Citations per field
00.5×1.7×
Ping‐Kun Zhou · 1×
Citations per year

Countries citing papers authored by Peng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Peng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 20253
5 20250
6 20248
7 20249
8 20241
9 20240
10 20238
11 20223
12 20227
13 202216
14 2019265
15 201865
16 201734
17
MiR-191 inhibits TNF-α induced apoptosis of ovarian endometriosis and endometrioid carcinoma cells by targeting DAPK1.
201539
18 201417
19 2011129
20 200511

About Peng Wang

Peng Wang is a scholar working on Cancer Research, Oncology, Aging, Epidemiology and Molecular Biology, having authored 219 papers that have together received 5.9k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (27 papers), Autophagy in Disease and Therapy (25 papers), RNA Research and Splicing (20 papers), Cancer Immunotherapy and Biomarkers (19 papers), MicroRNA in disease regulation (15 papers), Circular RNAs in diseases (13 papers), RNA modifications and cancer (11 papers) and Liver Disease Diagnosis and Treatment (10 papers). The work is most often cited by research in Cancer Research (1.2k citations), Immunology (1.1k citations), Molecular Biology (3.5k citations), Oncology (1.0k citations) and Epidemiology (1.1k citations). Peng Wang has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Bjoern Peters, Alessandro Sette, John Sidney, Bianca R. Mothé, Courtney Dow, Lin Zhang, Jian Yu, Yo-Han Kim, Ole Lund and Morten Nielsen. Their work appears in journals such as Nature Communications, PLoS ONE, Oncotarget, Cell Death and Disease and Cancer 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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