Hanlin Mok

706 total citations · 1 hit paper
7 papers, 462 citations indexed

About

Hanlin Mok is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Immunology. According to data from OpenAlex, Hanlin Mok has authored 7 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Pulmonary and Respiratory Medicine, 3 papers in Oncology and 3 papers in Immunology. Recurrent topics in Hanlin Mok's work include Immunotherapy and Immune Responses (3 papers), Prostate Cancer Treatment and Research (3 papers) and Cancer Research and Treatments (2 papers). Hanlin Mok is often cited by papers focused on Immunotherapy and Immune Responses (3 papers), Prostate Cancer Treatment and Research (3 papers) and Cancer Research and Treatments (2 papers). Hanlin Mok collaborates with scholars based in United States and China. Hanlin Mok's co-authors include Sarki A. Abdulkadir, Jonathan F. Anker, Barbara Lysy, Young A. Yoo, Rajita Vatapalli, Vinay Sagar, Huiying Han, Yara Rodríguez, Zachary R. Chalmers and Kenji Unno and has published in prestigious journals such as Nature Communications, JNCI Journal of the National Cancer Institute and Cancer Cell.

In The Last Decade

Hanlin Mok

6 papers receiving 460 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.

Small-Molecule MYC Inhibitors Suppress Tumor Growth and Enhance Immunotherapy

2019 302 citations Huiying Han, Atul D. Jain et al. Cancer Cell profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Hanlin Mok United States	5	292	187	103	90	70	7	462
Ashu Shah United States	10	225 0.8×	164 0.9×	54 0.5×	92 1.0×	78 1.1×	19	401
Annabelle Chow Canada	12	185 0.6×	168 0.9×	72 0.7×	88 1.0×	101 1.4×	17	398
Eric H.‐B. Huang United States	12	341 1.2×	192 1.0×	96 0.9×	124 1.4×	67 1.0×	15	528
Scott F. Winter United States	9	239 0.8×	121 0.6×	84 0.8×	107 1.2×	85 1.2×	10	413
Tatiana S. Gerashchenko Russia	12	188 0.6×	226 1.2×	92 0.9×	125 1.4×	160 2.3×	37	502
Kazuyo Yasuda Japan	15	351 1.2×	279 1.5×	49 0.5×	124 1.4×	128 1.8×	24	585
C. Guha United States	4	231 0.8×	299 1.6×	58 0.6×	135 1.5×	65 0.9×	13	515
Ines De Pauw Belgium	14	201 0.7×	204 1.1×	79 0.8×	74 0.8×	57 0.8×	18	413
Junya Yan China	11	241 0.8×	234 1.3×	48 0.5×	94 1.0×	97 1.4×	29	428

Countries citing papers authored by Hanlin Mok

Since Specialization

Citations

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

Fields of papers citing papers by Hanlin Mok

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanlin Mok

This figure shows the co-authorship network connecting the top 25 collaborators of Hanlin Mok. A scholar is included among the top collaborators of Hanlin Mok 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 Hanlin Mok. Hanlin Mok is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Tamilselvam, Batcha, Yingxing Li, Henry Chen, et al.. (2025). A bacterial genotoxin reveals a p53-proteasome-LC3 regulatory axis that drives the suppression of autophagy in cells experiencing sublethal DNA damage. iScience. 28(4). 112118–112118.

2.

Unno, Kenji, Zachary R. Chalmers, Sahithi Pamarthy, et al.. (2021). Activated ALK Cooperates with N-Myc via Wnt/β-Catenin Signaling to Induce Neuroendocrine Prostate Cancer. Cancer Research. 81(8). 2157–2170. 41 indexed citations

3.

Han, Huiying, Atul D. Jain, Mihai I. Truica, et al.. (2019). Small-Molecule MYC Inhibitors Suppress Tumor Growth and Enhance Immunotherapy. Cancer Cell. 36(5). 483–497.e15. 302 indexed citations breakdown →

4.

Anker, Jonathan F., et al.. (2018). A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer. Journal of Visualized Experiments. 7 indexed citations

5.

Anker, Jonathan F., et al.. (2018). Multi-faceted immunomodulatory and tissue-tropic clinical bacterial isolate potentiates prostate cancer immunotherapy. Nature Communications. 9(1). 1591–1591. 80 indexed citations

6.

Anker, Jonathan F., et al.. (2018). A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer. Journal of Visualized Experiments. 1 indexed citations

7.

Yoo, Young A., Rajita Vatapalli, Barbara Lysy, et al.. (2018). The Role of Castration-Resistant Bmi1+Sox2+ Cells in Driving Recurrence in Prostate Cancer. JNCI Journal of the National Cancer Institute. 111(3). 311–321. 31 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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