Max Diehn

1.1k total citations · 1 hit paper
8 papers, 597 citations indexed

About

Max Diehn is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Max Diehn has authored 8 papers receiving a total of 597 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Pulmonary and Respiratory Medicine and 4 papers in Oncology. Recurrent topics in Max Diehn's work include Cancer Genomics and Diagnostics (3 papers), Lung Cancer Treatments and Mutations (3 papers) and Lung Cancer Diagnosis and Treatment (2 papers). Max Diehn is often cited by papers focused on Cancer Genomics and Diagnostics (3 papers), Lung Cancer Treatments and Mutations (3 papers) and Lung Cancer Diagnosis and Treatment (2 papers). Max Diehn collaborates with scholars based in United States and China. Max Diehn's co-authors include Linda D. Shortliffe, Irving L. Weissman, Matt van de Rijn, Íñigo Espinosa, Harcharan Gill, Keith Syson Chan, Joseph C. Presti, David J. Wong, Laurie Ailles and Howard Y. Chang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Genetics and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Max Diehn

8 papers receiving 584 citations

Hit Papers

Identification, molecular characterization, clinical prog... 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Max Diehn United States 5 314 247 195 162 94 8 597
Jinjoo Kang United States 11 230 0.7× 280 1.1× 73 0.4× 42 0.3× 78 0.8× 13 490
Irene Raitman United States 6 291 0.9× 158 0.6× 60 0.3× 101 0.6× 154 1.6× 10 554
Rose-Anne Romano United States 9 272 0.9× 189 0.8× 39 0.2× 60 0.4× 114 1.2× 9 501
Esther van de Kamp Netherlands 5 379 1.2× 283 1.1× 45 0.2× 39 0.2× 67 0.7× 6 533
Scott Jepson United States 8 384 1.2× 289 1.2× 75 0.4× 106 0.7× 37 0.4× 8 652
Kanako Yuki Japan 9 248 0.8× 309 1.3× 30 0.2× 113 0.7× 124 1.3× 15 629
Naoko Negishi Japan 11 411 1.3× 118 0.5× 45 0.2× 371 2.3× 58 0.6× 16 789
Henia Darr United States 10 1.1k 3.4× 281 1.1× 80 0.4× 77 0.5× 135 1.4× 10 1.3k
Tetsuji Tokunaga Japan 15 461 1.5× 250 1.0× 39 0.2× 70 0.4× 154 1.6× 31 641
Hisanori Takenobu Japan 13 340 1.1× 266 1.1× 35 0.2× 103 0.6× 147 1.6× 25 616

Countries citing papers authored by Max Diehn

Since Specialization
Citations

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

Fields of papers citing papers by Max Diehn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Diehn

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

All Works

8 of 8 papers shown
1.
Hamilton, Mark P., Takeshi Sugio, Troy Noordenbos, et al.. (2024). Absence of Evidence for Pervasive CAR19 Driven T-Cell Lymphomagenesis Revealed By Comprehensive Genomic Profiling of an Index Tumor.. Transplantation and Cellular Therapy. 30(2). S487–S488. 3 indexed citations
3.
Chaudhuri, Aadel A., Alex Lovejoy, Jacob J. Chabon, et al.. (2017). Circulating Tumor DNA Analysis during Radiation Therapy for Localized Lung Cancer Predicts Treatment Outcome. International Journal of Radiation Oncology*Biology*Physics. 99(2). S1–S2. 11 indexed citations
4.
Merriott, David J., Aadel A. Chaudhuri, Jacob J. Chabon, et al.. (2017). Circulating Tumor DNA Quantitation for Early Response Assessment of Immune Checkpoint Inhibitors for Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 99(2). S20–S21. 1 indexed citations
5.
Sun, Jianguo, et al.. (2015). Yap1 promotes the survival and self-renewal of breast tumor initiating cells via inhibiting Smad3 signaling. Oncotarget. 7(9). 9692–9706. 14 indexed citations
6.
Chan, Keith Syson, Íñigo Espinosa, Mark P. Chao, et al.. (2009). Identification, molecular characterization, clinical prognosis, and therapeutic targeting of human bladder tumor-initiating cells. Proceedings of the National Academy of Sciences. 106(33). 14016–14021. 513 indexed citations breakdown →
7.
Piedras-Renterı́a, Erika S., Jason L. Pyle, Max Diehn, et al.. (2004). Presynaptic homeostasis at CNS nerve terminals compensates for lack of a key Ca 2+ entry pathway. Proceedings of the National Academy of Sciences. 101(10). 3609–3614. 45 indexed citations
8.
Diehn, Max. (1999). Large-scale identification of secreted and membrane-associated gene products using DNA microarrays. Nature Genetics. 23(S3). 41–41. 7 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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