Dian Yang

7.1k total citations
28 papers, 2.0k citations indexed

About

Dian Yang is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Dian Yang has authored 28 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 12 papers in Oncology and 6 papers in Epidemiology. Recurrent topics in Dian Yang's work include Lung Cancer Research Studies (7 papers), Neuroendocrine Tumor Research Advances (6 papers) and Cancer Genomics and Diagnostics (5 papers). Dian Yang is often cited by papers focused on Lung Cancer Research Studies (7 papers), Neuroendocrine Tumor Research Advances (6 papers) and Cancer Genomics and Diagnostics (5 papers). Dian Yang collaborates with scholars based in United States, Germany and China. Dian Yang's co-authors include Julien Sage, Monte M. Winslow, Barbara M. Grüner, Nadine S. Jahchan, Jonathan S. Weissman, Christina S. Kong, Britt Adamson, Jennifer J. Brady, Shin-Heng Chiou and Jing Shan Lim and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Dian Yang

27 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dian Yang United States 15 1.4k 716 353 300 212 28 2.0k
Nadine S. Jahchan United States 15 861 0.6× 656 0.9× 203 0.6× 276 0.9× 149 0.7× 29 1.5k
Bruno Alicke United States 21 1.8k 1.3× 566 0.8× 215 0.6× 149 0.5× 103 0.5× 32 2.3k
Theresa Zhang United States 17 1.3k 0.9× 507 0.7× 386 1.1× 143 0.5× 130 0.6× 28 2.0k
Ina Oehme Germany 29 3.1k 2.2× 1.1k 1.5× 268 0.8× 190 0.6× 93 0.4× 65 3.6k
Antonella Manca Italy 25 1.4k 1.0× 668 0.9× 466 1.3× 114 0.4× 156 0.7× 67 2.2k
Roberto Würth Italy 21 763 0.5× 527 0.7× 272 0.8× 189 0.6× 167 0.8× 37 1.4k
Anthony Possemato United States 8 1.9k 1.4× 651 0.9× 235 0.7× 257 0.9× 184 0.9× 14 2.4k
Emma Bolderson Australia 25 1.9k 1.4× 844 1.2× 383 1.1× 83 0.3× 173 0.8× 60 2.4k
Junfei Zhao United States 25 1.6k 1.2× 398 0.6× 587 1.7× 91 0.3× 200 0.9× 81 2.4k
David R. Croucher Australia 24 1.3k 0.9× 507 0.7× 486 1.4× 135 0.5× 145 0.7× 47 2.1k

Countries citing papers authored by Dian Yang

Since Specialization
Citations

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

Fields of papers citing papers by Dian Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dian Yang

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

All Works

20 of 20 papers shown
1.
Koblan, Luke W., Kathryn E. Yost, Pu Zheng, et al.. (2025). High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer. Science. 390(6770). eadx3800–eadx3800. 3 indexed citations
2.
Weng, Chen, Fulong Yu, Dian Yang, et al.. (2024). 2025 – DECIPHERING CELL STATES AND GENEALOGIES OF HUMAN HEMATOPOIESIS. Experimental Hematology. 137. 104582–104582. 2 indexed citations
3.
Shi, Peiguo, Wanwei Zhang, Sanny S.W. Chung, et al.. (2024). Sympathetic Neurons Promote Small Cell Lung Cancer through the β2-Adrenergic Receptor. Cancer Discovery. 15(3). 616–632. 9 indexed citations
4.
Whitfield, Troy W., Asaf Maoz, Dian Yang, et al.. (2024). Targeted therapies prime oncogene-driven lung cancers for macrophage-mediated destruction. Journal of Clinical Investigation. 134(9). 8 indexed citations
5.
Yang, Dian, et al.. (2024). Identifying influential nodes based on the disassortativity and community structure of complex network. Scientific Reports. 14(1). 8453–8453. 5 indexed citations
6.
Naranjo, Santiago, Lindsay M. LaFave, Rodrigo Romero, et al.. (2022). Modeling diverse genetic subtypes of lung adenocarcinoma with a next-generation alveolar type 2 organoid platform. Genes & Development. 36(15-16). 936–949. 23 indexed citations
7.
Koblan, Luke W., Mandana Arbab, Max W. Shen, et al.. (2021). Efficient C•G-to-G•C base editors developed using CRISPRi screens, target-library analysis, and machine learning. Nature Biotechnology. 39(11). 1414–1425. 155 indexed citations
8.
Hussmann, Jeffrey A., Ling Jia, Purnima Ravisankar, et al.. (2021). Mapping the genetic landscape of DNA double-strand break repair. Cell. 184(22). 5653–5669.e25. 109 indexed citations
9.
Chuang, Chen-Hua, et al.. (2020). Altered Mitochondria Functionality Defines a Metastatic Cell State in Lung Cancer and Creates an Exploitable Vulnerability. Cancer Research. 81(3). 567–579. 34 indexed citations
10.
Liu, Hong, Changhui Liu, Dian Yang, et al.. (2020). Application of Y-chromosomal microdeletions in a homicide case. Forensic Science International. 314. 110370–110370. 1 indexed citations
11.
Chan, Michelle M., Zachary D. Smith, Stefanie Grosswendt, et al.. (2019). Molecular recording of mammalian embryogenesis. Nature. 570(7759). 77–82. 225 indexed citations
12.
Yang, Dian, Sarah K. Denny, Peyton Greenside, et al.. (2018). Intertumoral Heterogeneity in SCLC Is Influenced by the Cell Type of Origin. Cancer Discovery. 8(10). 1316–1331. 104 indexed citations
13.
Chiou, Shin-Heng, Viviana I. Risca, Gordon Wang, et al.. (2017). BLIMP1 Induces Transient Metastatic Heterogeneity in Pancreatic Cancer. Cancer Discovery. 7(10). 1184–1199. 49 indexed citations
14.
Lim, Jing Shan, Alvaro Ibaseta, Marcus Fischer, et al.. (2017). Intratumoural heterogeneity generated by Notch signalling promotes small-cell lung cancer. Nature. 545(7654). 360–364. 311 indexed citations
15.
Greenside, Peyton, Zoe Rogers, Jennifer J. Brady, et al.. (2017). Molecular definition of a metastatic lung cancer state reveals a targetable CD109–Janus kinase–Stat axis. Nature Medicine. 23(3). 291–300. 111 indexed citations
16.
Denny, Sarah K., Dian Yang, Jennifer J. Brady, et al.. (2016). Nfib Promotes Metastasis through a Widespread Increase in Chromatin Accessibility. Cell. 166(2). 328–342. 244 indexed citations
17.
Grüner, Barbara M., Christopher J. Schulze, Dian Yang, et al.. (2016). An in vivo multiplexed small-molecule screening platform. Nature Methods. 13(10). 883–889. 48 indexed citations
18.
Chiou, Shin‐Heng, Ian P. Winters, Jing Wang, et al.. (2015). Pancreatic cancer modeling using retrograde viral vector delivery and in vivo CRISPR/Cas9-mediated somatic genome editing. Genes & Development. 29(14). 1576–1585. 165 indexed citations
19.
Caswell, Deborah R., Dian Yang, Shin-Heng Chiou, et al.. (2014). Obligate Progression Precedes Lung Adenocarcinoma Dissemination. Cancer Discovery. 4(7). 781–789. 40 indexed citations
20.
Jahchan, Nadine S., Joel T. Dudley, Paweł K. Mazur, et al.. (2013). A Drug Repositioning Approach Identifies Tricyclic Antidepressants as Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors. Cancer Discovery. 3(12). 1364–1377. 275 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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