Serena Tan

743 citations
6 papers · 443 · h-index 5

Impact in

  • Cell Biology top 10%
    • Microtubule and mitosis dynamics
    • Cellular transport and secretion
    • Cellular Mechanics and Interactions
    • Neurogenesis and neuroplasticity mechanisms

Papers in

    • Microtubule and mitosis dynamics 2
    • Cellular transport and secretion 1
    • Biomedical Text Mining and Ontologies 1
    • Ion channel regulation and function 1

Serena Tan

6 papers receiving 437 citations

Peers

Serena Tan
Comparison fields: 5 of 68
  • Cell Biology 193
  • Developmental Neuroscience 38
  • Cellular and Molecular Neuroscience 136
  • Molecular Biology 275
  • Aging 4
Replace Chun-Fang Huang with:
Chun-Fang Huang Taiwan
Atsuko Honda Japan
Takako Kaneko‐Kawano Japan
Vincent Th. G. Schoonderwoert Netherlands
Lukas Schwintzer Germany
Chiyuki Matsui Japan
Clare E. Buckley United Kingdom
Gary M. Riefler United States
Dong‐Won Lee South Korea
N. T. Hang Pham Canada
Serena Tan relative to Chun-Fang Huang Taiwan Chun-Fang Huang's profile →
Citations per field
00.5×1.5×
Chun-Fang Huang · 1×
Citations per year

Countries citing papers authored by Serena Tan

Since Specialization
Citations

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

Fields of papers citing papers by Serena Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1 2003167
2 2009152
3 201069
4 201531
5 201523
6 20121

About Serena Tan

Serena Tan is a scholar working on Cell Biology, Molecular Biology, Immunology and Allergy, Cellular and Molecular Neuroscience and Oncology, having authored 6 papers that have together received 443 indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (2 papers), Microtubule and mitosis dynamics (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Cellular transport and secretion (1 paper), Biomedical Text Mining and Ontologies (1 paper), Cancer Cells and Metastasis (1 paper), Ion channel regulation and function (1 paper) and Nerve injury and regeneration (1 paper). The work is most often cited by research in Cell Biology (193 citations), Developmental Neuroscience (38 citations), Cellular and Molecular Neuroscience (136 citations), Molecular Biology (275 citations) and Aging (4 citations). Serena Tan has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Richard B. Vallee, Julian Scherer, Tony Pawson, J. Paul Fawcett, Gregg G. Gundersen, Jan Schmoranzer, Kseniya Petrova, Natalie Landman, Simon S. Murray and Sung Ho Ryu. Their work appears in journals such as Current Biology, The Journal of Comparative Neurology, Brain and Behavior, Nature reviews. Cancer and Journal of Biological Chemistry.

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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