Chang Gong

1.1k total citations
27 papers, 762 citations indexed

About

Chang Gong is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Chang Gong has authored 27 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 12 papers in Molecular Biology and 8 papers in Immunology. Recurrent topics in Chang Gong's work include Cancer Immunotherapy and Biomarkers (11 papers), Mathematical Biology Tumor Growth (6 papers) and Single-cell and spatial transcriptomics (5 papers). Chang Gong is often cited by papers focused on Cancer Immunotherapy and Biomarkers (11 papers), Mathematical Biology Tumor Growth (6 papers) and Single-cell and spatial transcriptomics (5 papers). Chang Gong collaborates with scholars based in United States, China and Netherlands. Chang Gong's co-authors include Aleksander S. Popel, Paolo Vicini, Jennifer J. Linderman, Denise E. Kirschner, Rajesh Narwal, Lorin Roskos, Samira Jamalian, Kerri‐Ann Norton, Oleg Milberg and Imke H. Bartelink and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and Cancer Research.

In The Last Decade

Chang Gong

25 papers receiving 757 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chang Gong United States 15 324 317 222 189 182 27 762
Morgan Craig Canada 16 142 0.4× 234 0.7× 184 0.8× 112 0.6× 72 0.4× 50 785
Irina Kareva United States 16 362 1.1× 307 1.0× 171 0.8× 178 0.9× 235 1.3× 44 836
Svetlana Bunimovich‐Mendrazitsky Israel 15 197 0.6× 157 0.5× 370 1.7× 150 0.8× 52 0.3× 49 712
Angela M. Jarrett United States 20 194 0.6× 183 0.6× 352 1.6× 71 0.4× 173 1.0× 41 829
Antje‐Christine Walz Switzerland 15 349 1.1× 402 1.3× 59 0.3× 153 0.8× 84 0.5× 34 892
Moran Elishmereni Israel 15 245 0.8× 154 0.5× 257 1.2× 301 1.6× 108 0.6× 20 753
Hanwen Wang United States 16 303 0.9× 210 0.7× 125 0.6× 146 0.8× 136 0.7× 37 684
Yuri Kogan Israel 14 317 1.0× 248 0.8× 362 1.6× 162 0.9× 97 0.5× 33 626
Arijit Chakravarty United States 17 458 1.4× 691 2.2× 53 0.2× 63 0.3× 80 0.4× 50 1.2k
Eliezer Shochat Switzerland 12 234 0.7× 302 1.0× 187 0.8× 73 0.4× 59 0.3× 17 588

Countries citing papers authored by Chang Gong

Since Specialization
Citations

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

Fields of papers citing papers by Chang Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chang Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Chang Gong. A scholar is included among the top collaborators of Chang Gong 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 Chang Gong. Chang Gong 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.
Zhang, Yueming, et al.. (2025). Involvement of SIRT1-mediated aging in liver diseases. Frontiers in Cell and Developmental Biology. 13. 1548015–1548015. 5 indexed citations
2.
Wang, Pingping, Ziyan Chen, Hongyan Zhang, et al.. (2025). Biological potential and mechanisms of Brain-Expressed X-linked family proteins in cancers: an updated review. Journal of Advanced Research. 82. 411–428.
3.
4.
Nikfar, Mehdi, Hao‐Yang Mi, Chang Gong, Holly Kimko, & Aleksander S. Popel. (2023). Quantifying Intratumoral Heterogeneity and Immunoarchitecture Generated In-Silico by a Spatial Quantitative Systems Pharmacology Model. Cancers. 15(10). 2750–2750. 11 indexed citations
5.
Gong, Chang, Hanwen Wang, Richard J. Sové, et al.. (2022). Simulations of tumor growth and response to immunotherapy by coupling a spatial agent-based model with a whole-patient quantitative systems pharmacology model. PLoS Computational Biology. 18(7). e1010254–e1010254. 36 indexed citations
6.
Gong, Chang, Hanwen Wang, Emily F. Davis-Marcisak, et al.. (2021). Integrating single cell sequencing with a spatial quantitative systems pharmacology model spQSP for personalized prediction of triple-negative breast cancer immunotherapy response. SHILAP Revista de lepidopterología. 1-2. 100002–100002. 22 indexed citations
7.
Yang, Yaping, et al.. (2020). Preliminary results of the SYSU strategy for screening breast cancerin southern Chinese women. Scientia Sinica Vitae. 50(10). 1114–1120. 1 indexed citations
8.
Mi, Haoyang, Chang Gong, Jeremias Sulam, et al.. (2020). Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in Triple-Negative Breast Cancer. Frontiers in Physiology. 11. 583333–583333. 50 indexed citations
9.
Gong, Chang, Jian Wu, Jing Gao, et al.. (2019). MicroRNA-181c suppresses growth and metastasis of hepatocellular carcinoma by modulating NCAPG. SHILAP Revista de lepidopterología. 1 indexed citations
10.
Milberg, Oleg, Chang Gong, Mohammad Jafarnejad, et al.. (2019). A QSP Model for Predicting Clinical Responses to Monotherapy, Combination and Sequential Therapy Following CTLA-4, PD-1, and PD-L1 Checkpoint Blockade. Scientific Reports. 9(1). 11286–11286. 71 indexed citations
11.
Jafarnejad, Mohammad, Chang Gong, Edward Gabrielson, et al.. (2019). A Computational Model of Neoadjuvant PD-1 Inhibition in Non-Small Cell Lung Cancer. The AAPS Journal. 21(5). 79–79. 53 indexed citations
12.
Gong, Chang, Robert A. Anders, Qingfeng Zhu, et al.. (2019). Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors. Frontiers in Oncology. 8. 649–649. 33 indexed citations
13.
Gong, Chang, Oleg Milberg, Bing Wang, et al.. (2017). Abstract 975: A multiscale computational model for spatio-temporal tumor immune response. Cancer Research. 77(13_Supplement). 975–975. 1 indexed citations
14.
Milberg, Oleg, Chang Gong, Bing Wang, et al.. (2017). Abstract 4531: Systems pharmacology to predict cellular biomarkers and optimize mono- and combination-therapy regimens: Focusing on immune checkpoint targets PD-1, PD-L1 and CTLA-4. Cancer Research. 77(13_Supplement). 4531–4531. 2 indexed citations
15.
Ziraldo, Cordelia, Chang Gong, Denise E. Kirschner, & Jennifer J. Linderman. (2016). Strategic Priming with Multiple Antigens can Yield Memory Cell Phenotypes Optimized for Infection with Mycobacterium tuberculosis: A Computational Study. Frontiers in Microbiology. 6. 1477–1477. 11 indexed citations
16.
Marino, Simeone, Hannah P. Gideon, Chang Gong, et al.. (2016). Computational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome. PLoS Computational Biology. 12(4). e1004804–e1004804. 31 indexed citations
17.
Gong, Chang, et al.. (2015). A population model capturing dynamics of tuberculosis granulomas predicts host infection outcomes. Mathematical Biosciences & Engineering. 12(3). 625–642. 15 indexed citations
18.
Gong, Chang, Jennifer J. Linderman, & Denise E. Kirschner. (2014). Harnessing the heterogeneity of T cell differentiation fate to fine-tune generation of effector and memory T cells (LYM4P.759). The Journal of Immunology. 192(Supplement_1). 65.16–65.16. 1 indexed citations
19.
Gong, Chang, Jennifer J. Linderman, & Denise E. Kirschner. (2014). Harnessing the Heterogeneity of T Cell Differentiation Fate to Fine-Tune Generation of Effector and Memory T Cells. Frontiers in Immunology. 5. 57–57. 31 indexed citations
20.
Gong, Chang, et al.. (2013). Predicting lymph node output efficiency using systems biology. Journal of Theoretical Biology. 335. 169–184. 39 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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