Winnie Tan

672 citations
18 papers · 489 · h-index 12

Impact in

    • Carcinogens and Genotoxicity Assessment
    • DNA Repair Mechanisms
    • Ubiquitin and proteasome pathways
    • CRISPR and Genetic Engineering
    • Genomics and Chromatin Dynamics
    • Epigenetics and DNA Methylation

Papers in

    • DNA Repair Mechanisms 11
    • CRISPR and Genetic Engineering 3
    • Genomics and Chromatin Dynamics 3
    • DNA and Nucleic Acid Chemistry 2
    • Ubiquitin and proteasome pathways 2
    • 14-3-3 protein interactions 1
    • Microtubule and mitosis dynamics 4

Winnie Tan

18 papers receiving 486 citations

Peers

Winnie Tan
Comparison fields: 5 of 59
  • Cancer Research 76
  • Molecular Biology 363
  • Cell Biology 55
  • Oncology 69
  • Genetics 58
Replace Fengming Gong with:
Fengming Gong China
Sreeja C. Sekhar United States
Jiantao Xiao China
Ingrid Lilienthal Sweden
Lan Chen China
Brian I. Hang United States
Xinyuan Dong United States
Xiangpeng Dai China
Haifeng Shen China
Yuki Yoshino Japan
Winnie Tan relative to Fengming Gong China Fengming Gong's profile →
Citations per field
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Citations per year

Countries citing papers authored by Winnie Tan

Since Specialization
Citations

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

Fields of papers citing papers by Winnie Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2016108
2 201471
3 202062
4 201446
5 202030
6 202028
7 200227
8 202220
9 201518
10 201718
11 202014
12 202013
13 20209
14 20209
15 20206
16 20215
17 20253
18 20252

About Winnie Tan

Winnie Tan is a scholar working on Molecular Biology, Cell Biology, Cancer Research, Oncology and Hepatology, having authored 18 papers that have together received 489 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (11 papers), Microtubule and mitosis dynamics (4 papers), CRISPR and Genetic Engineering (3 papers), Genomics and Chromatin Dynamics (3 papers), DNA and Nucleic Acid Chemistry (2 papers), Ubiquitin and proteasome pathways (2 papers), 14-3-3 protein interactions (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Cancer Research (76 citations), Molecular Biology (363 citations), Cell Biology (55 citations), Oncology (69 citations) and Genetics (58 citations). Winnie Tan has collaborated with scholars based in Australia, Hong Kong and China. Frequent co-authors include Andrew J. Deans, Vincent J. Murphy, Sylvie van Twest, Wayne Crismani, Julienne J. O’Rourke, Kin Chan, Nikki P. Lee, Charlotte Hodson, Jörg Heierhorst and Paolo Swuec. Their work appears in journals such as Molecular Cell, eLife, Oncology Reports, Cell Reports and Frontiers in Cell and Developmental Biology.

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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