Pak Shing Kwan

1.2k citations
10 papers · 1.0k · h-index 8

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer, Hypoxia, and Metabolism
  • Oncology top 10%
    • Cancer Cells and Metastasis

Papers in

    • Cancer Cells and Metastasis 3
    • Peptidase Inhibition and Analysis 1
    • Chemokine receptors and signaling 1

Pak Shing Kwan

10 papers receiving 992 citations

Peers

Pak Shing Kwan
Comparison fields: 5 of 68
  • Cancer Research 443
  • Oncology 439
  • Hepatology 106
  • Molecular Biology 685
  • Cell Biology 91
Replace Yuen Piu Chan with:
Yuen Piu Chan Hong Kong
Emin Ibrahimov Canada
Teru Kawasoe Japan
Nadia Coltella Italy
Kandavel Shanmugam United States
Vikash Bhagwandin United States
Jurrit Zeilstra Netherlands
Paolo Luraghi Italy
Jacqueline E. Noll Australia
Francesca De Bacco Italy
Pak Shing Kwan relative to Yuen Piu Chan Hong Kong Yuen Piu Chan's profile →
Citations per field
00.5×1.5×
Yuen Piu Chan · 1×
Citations per year

Countries citing papers authored by Pak Shing Kwan

Since Specialization
Citations

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

Fields of papers citing papers by Pak Shing Kwan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pak Shing Kwan. 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 Pak Shing Kwan. The network helps show where Pak Shing Kwan may publish in the future.

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 2010328
2 2011206
3 2013128
4 201296
5 201070
6 201270
7 201462
8 201235
9 20115
10
Daxx regulates mitotic progression and prostate cancer predisposition
20131

About Pak Shing Kwan

Pak Shing Kwan is a scholar working on Molecular Biology, Oncology, Cancer Research, Cell Biology and Pathology and Forensic Medicine, having authored 10 papers that have together received 1.0k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (4 papers), Cancer Cells and Metastasis (3 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Cancer-related molecular mechanisms research (2 papers), Microtubule and mitosis dynamics (2 papers), Peptidase Inhibition and Analysis (1 paper), Prostate Cancer Treatment and Research (1 paper) and Chemokine receptors and signaling (1 paper). The work is most often cited by research in Cancer Research (443 citations), Oncology (439 citations), Hepatology (106 citations), Molecular Biology (685 citations) and Cell Biology (91 citations). Pak Shing Kwan has collaborated with scholars based in Hong Kong, China and Australia. Frequent co-authors include Stephanie Ma, Xin‐Yuan Guan, Kwok Wah Chan, Yuen Piu Chan, Kwan Ho Tang, Terence K. Lee, Man Tong, Chung Mau Lo, Irene Oi‐Lin Ng and Kwan Man. Their work appears in journals such as Cancer Research, Oncotarget, Cell stem cell, Carcinogenesis and Hepatology.

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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