Pui Yeng Lam

1.4k total citations · 1 hit paper
17 papers, 618 citations indexed

About

Pui Yeng Lam is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Pui Yeng Lam has authored 17 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 8 papers in Molecular Biology and 7 papers in Oncology. Recurrent topics in Pui Yeng Lam's work include Immune Cell Function and Interaction (10 papers), Single-cell and spatial transcriptomics (5 papers) and CAR-T cell therapy research (5 papers). Pui Yeng Lam is often cited by papers focused on Immune Cell Function and Interaction (10 papers), Single-cell and spatial transcriptomics (5 papers) and CAR-T cell therapy research (5 papers). Pui Yeng Lam collaborates with scholars based in Australia, Germany and United Kingdom. Pui Yeng Lam's co-authors include Stephen R. Mattarollo, John A. Hamilton, Sohye Yoon, Arti M. Raghubar, Quan Nguyen, Duy Pham, Xiao Tan, Laura F. Grice, Priyakshi Kalita‐de Croft and Emily F. Willis and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Pui Yeng Lam

17 papers receiving 614 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

2023 177 citations Duy Pham, Xiao Tan et al. Nature Communications profile →

Peers

Pui Yeng Lam

IMMUN

ONCOL

RHEUM

Daniel Dimitrov Germany

Sophia Müller‐Dott Germany

Mahmoud M. Ibrahim Germany

Esther Bandala‐Sanchez Australia

Marta Derecka United States

Rubén Barroso Spain

Cameron G. Williams Australia

Béla Kajtár Hungary

Amr Al‐Haidari Sweden

Souichi Tsutsumi Japan

Daniel Dimitrov Germany

Pui Yeng Lam

405 ×1.4

177 ×0.7

IMMUN

93 ×0.8

ONCOL

77 ×0.6

11 ×0.3

RHEUM

Citations per year, relative to Pui Yeng Lam Pui Yeng Lam (= 1×) peers Daniel Dimitrov

Countries citing papers authored by Pui Yeng Lam

Since Specialization

Citations

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

Fields of papers citing papers by Pui Yeng Lam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pui Yeng Lam. 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 Pui Yeng Lam. The network helps show where Pui Yeng Lam may publish in the future.

Co-authorship network of co-authors of Pui Yeng Lam

This figure shows the co-authorship network connecting the top 25 collaborators of Pui Yeng Lam. A scholar is included among the top collaborators of Pui Yeng Lam based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pui Yeng Lam. Pui Yeng Lam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Yoon, Sohye, Pui Yeng Lam, Chenhao Zhou, et al.. (2025). Assessing spatial sequencing and imaging approaches to capture the molecular and pathological heterogeneity of archived cancer tissues. The Journal of Pathology. 265(3). 274–288. 4 indexed citations

Rossi, Gustavo Rodrigues, Jane Sun, Cheng‐Yu Lin, et al.. (2024). A scalable, spin‐free approach to generate enhanced induced pluripotent stem cell–derived natural killer cells for cancer immunotherapy. Immunology and Cell Biology. 102(10). 924–934. 3 indexed citations

McCulloch, Timothy R., Gustavo Rodrigues Rossi, Pui Yeng Lam, et al.. (2024). Dichotomous outcomes of TNFR1 and TNFR2 signaling in NK cell-mediated immune responses during inflammation. Nature Communications. 15(1). 9871–9871. 10 indexed citations

Lam, Pui Yeng & Fernando Souza-Fonseca-Guimarães. (2024). Highlight of 2023: Unlocking the therapeutic potential of natural killer cells—advances in adaptive functions, cellular engineering and immunotherapy. Immunology and Cell Biology. 102(6). 444–447. 1 indexed citations

McCulloch, Timothy R., Gustavo Rodrigues Rossi, Socorro Miranda‐Hernandez, et al.. (2024). The immune checkpoint TIGIT is upregulated on T cells during bacterial infection and is a potential target for immunotherapy. Immunology and Cell Biology. 102(8). 721–733. 3 indexed citations

Pham, Duy, Xiao Tan, Brad Balderson, et al.. (2023). Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues. Nature Communications. 14(1). 7739–7739. 177 indexed citations breakdown →

Raghubar, Arti M., Joanna Crawford, Pui Yeng Lam, et al.. (2023). Spatial Transcriptomics in Kidney Tissue. Methods in molecular biology. 2664. 233–282. 3 indexed citations

Raghubar, Arti M., Duy Pham, Xiao Tan, et al.. (2022). Spatially Resolved Transcriptomes of Mammalian Kidneys Illustrate the Molecular Complexity and Interactions of Functional Nephron Segments. Frontiers in Medicine. 9. 873923–873923. 18 indexed citations

Tran, Minh, Sohye Yoon, Stacey B. Andersen, et al.. (2022). A robust experimental and computational analysis framework at multiple resolutions, modalities and coverages. Frontiers in Immunology. 13. 911873–911873. 9 indexed citations

10.

Kobayashi, T, Pui Yeng Lam, Hui Jiang, et al.. (2020). Increased lipid metabolism impairs NK cell function and mediates adaptation to the lymphoma environment. Blood. 136(26). 3004–3017. 113 indexed citations

11.

Lam, Pui Yeng, T Kobayashi, Megan S. F. Soon, et al.. (2019). NKT Cell–Driven Enhancement of Antitumor Immunity Induced by Clec9a-Targeted Tailorable Nanoemulsion. Cancer Immunology Research. 7(6). 952–962. 11 indexed citations

12.

Soon, Megan S. F., T Kobayashi, Michael Nissen, et al.. (2018). Therapeutic vaccination with 4–1BB co-stimulation eradicates mouse acute myeloid leukemia. OncoImmunology. 7(10). e1486952–e1486952. 16 indexed citations

13.

Achuthan, Adrian, Quyen Le Hoang Thuy To Nguyen, Pui Yeng Lam, et al.. (2018). Glucocorticoids promote apoptosis of proinflammatory monocytes by inhibiting ERK activity. Cell Death and Disease. 9(3). 53 indexed citations

14.

Tuong, Zewen Kelvin, T Kobayashi, Megan S. F. Soon, et al.. (2017). B cell lymphoma progression promotes the accumulation of circulating Ly6Clo monocytes with immunosuppressive activity. OncoImmunology. 7(2). e1393599–e1393599. 15 indexed citations

15.

Lam, Pui Yeng, Michael Nissen, & Stephen R. Mattarollo. (2017). Invariant Natural Killer T Cells in Immune Regulation of Blood Cancers: Harnessing Their Potential in Immunotherapies. Frontiers in Immunology. 8. 1355–1355. 23 indexed citations

16.

Achuthan, Adrian, Andrew D. Cook, Ming-Chin Lee, et al.. (2016). Granulocyte macrophage colony-stimulating factor induces CCL17 production via IRF4 to mediate inflammation. Journal of Clinical Investigation. 126(9). 3453–3466. 126 indexed citations

17.

Kwa, Mei Qi, Thao Nguyen, Jennifer Huynh, et al.. (2014). Interferon Regulatory Factor 6 Differentially Regulates Toll-like Receptor 2-dependent Chemokine Gene Expression in Epithelial Cells. Journal of Biological Chemistry. 289(28). 19758–19768. 33 indexed citations

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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