Chang Shu

3.8k total citations · 1 hit paper
98 papers, 2.3k citations indexed

About

Chang Shu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Social Psychology. According to data from OpenAlex, Chang Shu has authored 98 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 13 papers in Cellular and Molecular Neuroscience and 10 papers in Social Psychology. Recurrent topics in Chang Shu's work include Bullying, Victimization, and Aggression (9 papers), Asymmetric Synthesis and Catalysis (8 papers) and Ubiquitin and proteasome pathways (7 papers). Chang Shu is often cited by papers focused on Bullying, Victimization, and Aggression (9 papers), Asymmetric Synthesis and Catalysis (8 papers) and Ubiquitin and proteasome pathways (7 papers). Chang Shu collaborates with scholars based in United States, China and Germany. Chang Shu's co-authors include Markus D. Siegelin, Benjamin Lê Cook, Georg Karpel‐Massler, E. Nilay Kafali, Michael Flores, Zimin Liu, Mike‐Andrew Westhoff, Peter Canoll, Jeffrey N. Bruce and Marc‐Eric Halatsch and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and JAMA.

In The Last Decade

Chang Shu

93 papers receiving 2.3k citations

Hit Papers

Trends in Smoking Among Adults With Mental Illness and As... 2014 2026 2018 2022 2014 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chang Shu United States 26 1.0k 381 259 214 176 98 2.3k
Xiaoyu Li China 26 1.3k 1.3× 316 0.8× 194 0.7× 264 1.2× 94 0.5× 91 2.7k
Nina F. Schor United States 29 1.4k 1.4× 341 0.9× 140 0.5× 185 0.9× 96 0.5× 135 2.7k
Santo Marsigliante Italy 30 1.2k 1.2× 222 0.6× 279 1.1× 387 1.8× 251 1.4× 167 3.1k
Hyun Joon Kim South Korea 31 1.4k 1.4× 611 1.6× 82 0.3× 232 1.1× 121 0.7× 129 3.4k
Yu Nakamura Japan 30 864 0.9× 406 1.1× 308 1.2× 201 0.9× 77 0.4× 152 2.6k
David Brown United Kingdom 24 1.3k 1.3× 535 1.4× 581 2.2× 170 0.8× 64 0.4× 71 3.5k
Mathias Rask‐Andersen Sweden 25 3.0k 3.0× 424 1.1× 113 0.4× 192 0.9× 76 0.4× 60 4.6k
Rana Dajani Jordan 22 1.9k 1.9× 172 0.5× 216 0.8× 93 0.4× 62 0.4× 115 3.2k
Nathalie Tremblay Canada 23 813 0.8× 336 0.9× 230 0.9× 120 0.6× 49 0.3× 37 2.4k
Tingting Yang China 28 796 0.8× 143 0.4× 85 0.3× 456 2.1× 133 0.8× 80 2.6k

Countries citing papers authored by Chang Shu

Since Specialization
Citations

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

Fields of papers citing papers by Chang Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chang Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Chang Shu. A scholar is included among the top collaborators of Chang Shu 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 Shu. Chang Shu 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.
Li, Boyang, Shaowei Wang, Bilal E. Kerman, et al.. (2025). Microglial States Are Susceptible to Senescence and Cholesterol Dysregulation in Alzheimer's Disease. Aging Cell. 24(10). e70189–e70189.
2.
Shu, Chang, et al.. (2024). Understanding the molecular pathway of triclosan-induced ADHD-like behaviour: Involvement of the hnRNPA1-PKM2-STAT3 feedback loop. Environment International. 191. 108966–108966. 2 indexed citations
4.
Wang, Haowen, et al.. (2024). Climate factors associated with cancer incidence: An ecological study covering 33 cancers from population-based registries in 37 countries. PLOS Climate. 3(3). e0000362–e0000362. 4 indexed citations
5.
6.
Sosnowski, David W., Andrew E. Jaffe, Ran Tao, et al.. (2022). Differential expression of NPAS4 in the dorsolateral prefrontal cortex following opioid overdose. SHILAP Revista de lepidopterología. 3. 100040–100040. 3 indexed citations
7.
Ji, John S., Linxin Liu, Chang Shu, Lijing L. Yan, & Yi Zeng. (2021). Sex Difference and Interaction of SIRT1 and FOXO3 Candidate Longevity Genes on Life Expectancy: A 10-Year Prospective Longitudinal Cohort Study. The Journals of Gerontology Series A. 77(8). 1557–1563. 9 indexed citations
8.
Liu, Linxin, Anna Zhu, Chang Shu, Yi Zeng, & John S. Ji. (2020). Gene–Environment Interaction of FOXO and Residential Greenness on Mortality Among Older Adults. Rejuvenation Research. 24(1). 49–61. 5 indexed citations
9.
Zhu, Anna, Lijing L. Yan, Chang Shu, Yi Zeng, & John S. Ji. (2020). APOE ε4 Modifies Effect of Residential Greenness on Cognitive Function among Older Adults: A Longitudinal Analysis in China. Scientific Reports. 10(1). 82–82. 24 indexed citations
10.
Shu, Chang, Amy C. Justice, Xinyu Zhang, et al.. (2020). DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population. Epigenetics. 16(7). 741–753. 12 indexed citations
12.
Cates, Hannah M., Chelsie E. Benca‐Bachman, Giordano de Guglielmo, et al.. (2019). National Institute on Drug Abuse genomics consortium white paper: Coordinating efforts between human and animal addiction studies. Genes Brain & Behavior. 18(6). e12577–e12577. 7 indexed citations
13.
Shu, Chang, Ge Feng, Qing Wang, et al.. (2019). Polysaccharides from Pyracantha fortuneana and its biological activity. International Journal of Biological Macromolecules. 150. 1162–1174. 34 indexed citations
14.
Zhang, Yiru, Chiaki Tsuge Ishida, Wataru Ishida, et al.. (2018). Combined HDAC and Bromodomain Protein Inhibition Reprograms Tumor Cell Metabolism and Elicits Synthetic Lethality in Glioblastoma. Clinical Cancer Research. 24(16). 3941–3954. 37 indexed citations
15.
Zhang, Yiru, Elena Bianchetti, Chang Shu, et al.. (2018). Metabolic Reprogramming by Dual AKT/ERK Inhibition through Imipridones Elicits Unique Vulnerabilities in Glioblastoma. Clinical Cancer Research. 24(21). 5392–5406. 63 indexed citations
16.
Karpel‐Massler, Georg, Chiaki Tsuge Ishida, Elena Bianchetti, et al.. (2017). Inhibition of Mitochondrial Matrix Chaperones and Antiapoptotic Bcl-2 Family Proteins Empower Antitumor Therapeutic Responses. Cancer Research. 77(13). 3513–3526. 62 indexed citations
17.
Ishida, Chiaki Tsuge, Elena Bianchetti, Chang Shu, et al.. (2017). BH3-mimetics and BET-inhibitors elicit enhanced lethality in malignant glioma. Oncotarget. 8(18). 29558–29573. 36 indexed citations
18.
Karpel‐Massler, Georg, Basil A. Horst, Chang Shu, et al.. (2016). A Synthetic Cell-Penetrating Dominant-Negative ATF5 Peptide Exerts Anticancer Activity against a Broad Spectrum of Treatment-Resistant Cancers. Clinical Cancer Research. 22(18). 4698–4711. 63 indexed citations
19.
Pareja, Fresia, David MacLeod, Chang Shu, et al.. (2014). PI3K and Bcl-2 Inhibition Primes Glioblastoma Cells to Apoptosis through Downregulation of Mcl-1 and Phospho-BAD. Molecular Cancer Research. 12(7). 987–1001. 72 indexed citations
20.
Gerlach, Stefan, Wensheng Peng, & Chang Shu. (2005). Macroeconomic conditions and banking performance in Hong Kong SAR: a panel data study. BIS Papers chapters. 22. 481–497. 41 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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