Megan Wu

879 citations
12 papers · 615 · h-index 10

Impact in

  • Nephrology top 10%
    • Renal Diseases and Glomerulopathies
    • Renal and related cancers
    • DNA Repair Mechanisms
    • Developmental Biology and Gene Regulation

Papers in

    • Renal and related cancers 3
    • DNA Repair Mechanisms 2
    • Epigenetics and DNA Methylation 1
    • Cancer Cells and Metastasis 3
    • PARP inhibition in cancer therapy 2

Megan Wu

12 papers receiving 613 citations

Peers

Megan Wu
Comparison fields: 5 of 73
  • Nephrology 61
  • Molecular Biology 407
  • Genetics 52
  • Cancer Research 70
  • Oncology 106
Replace Yue Shen with:
Yue Shen China
Elena E. Tchekneva United States
Dana Duan United States
Ganeshkumar Rajendran United States
Philip G. Woost United States
Ralph Patrick Australia
Noga Gadir United States
Sophie Valleix France
Liisa Laitinen Finland
Yen‐Rei Yu United States
Megan Wu relative to Yue Shen China Yue Shen's profile →
Citations per field
00.5×2.9×
Yue Shen · 1×
Citations per year

Countries citing papers authored by Megan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Megan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 200897
2 201281
3 200470
4 200968
5 201064
6 201964
7 201952
8 201441
9 201739
10 201627
11 20229
12 20243

About Megan Wu

Megan Wu is a scholar working on Molecular Biology, Oncology, Genetics, Surgery and Nephrology, having authored 12 papers that have together received 615 indexed citations. Recurring topics across this work include Renal and related cancers (3 papers), Cancer Cells and Metastasis (3 papers), Glioma Diagnosis and Treatment (3 papers), DNA Repair Mechanisms (2 papers), PARP inhibition in cancer therapy (2 papers), Cancer Mechanisms and Therapy (1 paper), Cardiac electrophysiology and arrhythmias (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Nephrology (61 citations), Molecular Biology (407 citations), Genetics (52 citations), Cancer Research (70 citations) and Oncology (106 citations). Megan Wu has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Tino D. Piscione, Susan E. Quaggin, Alan P. Kozikowski, Michał Pawłowski, Brian Budke, Philip P. Connell, Sunit Das, Corrinne G. Lobe, Tuncer Onay and Jay H. Kalin. Their work appears in journals such as Cancer Research, Journal of Medicinal Chemistry, Journal of the American Society of Nephrology, Oncotarget and Circulation 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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