Alan L. Chang

3.7k total citations
45 papers, 2.1k citations indexed

About

Alan L. Chang is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Alan L. Chang has authored 45 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Immunology and 9 papers in Oncology. Recurrent topics in Alan L. Chang's work include Immune cells in cancer (8 papers), Virus-based gene therapy research (5 papers) and Single-cell and spatial transcriptomics (4 papers). Alan L. Chang is often cited by papers focused on Immune cells in cancer (8 papers), Virus-based gene therapy research (5 papers) and Single-cell and spatial transcriptomics (4 papers). Alan L. Chang collaborates with scholars based in United States, Canada and China. Alan L. Chang's co-authors include Maciej S. Lesniak, Derek A. Wainwright, Alex L. Tobias, Atique U. Ahmed, Yu Han, Mahua Dey, Hsiu‐Hua Chang, Long‐Chuan Lu, Yu Han and Jian Qiao and has published in prestigious journals such as Nature Communications, The Journal of Immunology and Brain.

In The Last Decade

Alan L. Chang

36 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alan L. Chang United States 19 765 611 584 445 211 45 2.1k
Feifei Zhao China 23 1.6k 2.1× 762 1.2× 1.0k 1.8× 253 0.6× 76 0.4× 58 3.4k
Kun Yao China 22 284 0.4× 492 0.8× 693 1.2× 664 1.5× 262 1.2× 108 1.9k
Oxana Bereshchenko Italy 23 465 0.6× 325 0.5× 1.1k 1.8× 137 0.3× 66 0.3× 43 2.0k
Biplab Dasgupta United States 31 229 0.3× 479 0.8× 1.9k 3.2× 372 0.8× 202 1.0× 72 4.4k
Nikola A. Bowden Australia 23 358 0.5× 456 0.7× 1.4k 2.3× 54 0.1× 158 0.7× 67 2.3k
Ou Bai China 18 343 0.4× 228 0.4× 905 1.5× 66 0.1× 63 0.3× 88 1.7k
Xiaoping Li China 29 265 0.3× 758 1.2× 1.2k 2.1× 72 0.2× 199 0.9× 155 2.8k
Miyuki Uno Brazil 20 180 0.2× 162 0.3× 659 1.1× 243 0.5× 121 0.6× 66 1.2k

Countries citing papers authored by Alan L. Chang

Since Specialization
Citations

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

Fields of papers citing papers by Alan L. Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alan L. Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Alan L. Chang. A scholar is included among the top collaborators of Alan L. Chang 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 Alan L. Chang. Alan L. Chang 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.
Bukhari, Syed, Lei Xue, David Seong, et al.. (2025). Deep learning-based cell type profiles reveal signatures of Alzheimer’s disease resilience and resistance. Brain. 148(10). 3665–3678.
2.
Chang, Alan L., et al.. (2024). Nikodym sets and maximal functions associated with spheres. Revista Matemática Iberoamericana. 41(3). 1009–1056.
3.
Stevenson, David K., Alan L. Chang, Ronald J. Wong, et al.. (2024). Towards a new taxonomy of preterm birth. Journal of Perinatology. 45(8). 1158–1162. 1 indexed citations
4.
Chang, Alan L., et al.. (2024). Reassessing acquired neonatal intestinal diseases using unsupervised machine learning. Pediatric Research. 96(1). 165–171. 9 indexed citations
5.
Phongpreecha, Thanaphong, Fiorella C. Grandi, Lei Xue, et al.. (2023). Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature. Nature Communications. 14(1). 4947–4947. 13 indexed citations
6.
Mathews, Juanita, et al.. (2023). Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine. Patterns. 4(5). 100737–100737. 26 indexed citations
7.
Phongpreecha, Thanaphong, Camilo Espinosa, Brenna Cholerton, et al.. (2023). Quantitative estimate of cognitive resilience and its medical and genetic associations. Alzheimer s Research & Therapy. 15(1). 192–192. 4 indexed citations
8.
Reiss, Jonathan D., Laura S. Peterson, Alan L. Chang, et al.. (2022). Perinatal infection, inflammation, preterm birth, and brain injury: A review with proposals for future investigations. Experimental Neurology. 351. 113988–113988. 22 indexed citations
9.
Reiss, Jonathan D., Alan L. Chang, Jonathan A. Mayo, et al.. (2021). Newborn screen metabolic panels reflect the impact of common disorders of pregnancy. Pediatric Research. 92(2). 490–497. 6 indexed citations
10.
Espinosa, Camilo, Martin Becker, Ivana Marić, et al.. (2021). Data-Driven Modeling of Pregnancy-Related Complications. Trends in Molecular Medicine. 27(8). 762–776. 32 indexed citations
11.
Renauer, Paul, Guangchuan Wang, Ryan D. Chow, et al.. (2019). Convergent Identification and Interrogation of Tumor-Intrinsic Factors that Modulate Cancer Immunity In Vivo. Cell Systems. 8(2). 136–151.e7. 12 indexed citations
12.
Miska, Jason, Catalina Lee-Chang, Aida Rashidi, et al.. (2019). HIF-1α Is a Metabolic Switch between Glycolytic-Driven Migration and Oxidative Phosphorylation-Driven Immunosuppression of Tregs in Glioblastoma. Cell Reports. 27(1). 226–237.e4. 230 indexed citations
13.
Muroski, Megan E., Jason Miska, Alan L. Chang, et al.. (2017). Fatty Acid Uptake in T Cell Subsets Using a Quantum Dot Fatty Acid Conjugate. Scientific Reports. 7(1). 5790–5790. 26 indexed citations
14.
Qiao, Jian, Mahua Dey, Alan L. Chang, et al.. (2015). Intratumoral oncolytic adenoviral treatment modulates the glioma microenvironment and facilitates systemic tumor-antigen-specific T cell therapy. OncoImmunology. 4(8). e1022302–e1022302. 27 indexed citations
15.
Wainwright, Derek A., Alan L. Chang, Mahua Dey, et al.. (2014). Durable Therapeutic Efficacy Utilizing Combinatorial Blockade against IDO, CTLA-4, and PD-L1 in Mice with Brain Tumors. Clinical Cancer Research. 20(20). 5290–5301. 448 indexed citations
16.
Kraft, Bryan, Claude A. Piantadosi, Joseph E. Lucas, et al.. (2014). Development of a Novel Preclinical Model of Pneumococcal Pneumonia in Nonhuman Primates. American Journal of Respiratory Cell and Molecular Biology. 50(5). 995–1004. 18 indexed citations
17.
Dey, Mahua, Alan L. Chang, Derek A. Wainwright, et al.. (2013). Heme oxygenase-1 protects regulatory T cells from hypoxia-induced cellular stress in an experimental mouse brain tumor model. Journal of Neuroimmunology. 266(1-2). 33–42. 14 indexed citations
18.
Wainwright, Derek A., Irina V. Balyasnikova, Alan L. Chang, et al.. (2012). IDO Expression in Brain Tumors Increases the Recruitment of Regulatory T Cells and Negatively Impacts Survival. Clinical Cancer Research. 18(22). 6110–6121. 378 indexed citations
19.
Carmody, Kristin, et al.. (2010). Extrauterine Migration of a Mirena® Intrauterine Device: A Case Report. Journal of Emergency Medicine. 41(2). 161–165. 6 indexed citations
20.
Butler, Stephen F., Kathrine C. Fernandez, Alan L. Chang, et al.. (2009). Measuring Attractiveness for Abuse of Prescription Opioids. Pain Medicine. 11(1). 67–80. 43 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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