Pamela V. Chang

6.5k total citations · 4 hit papers
28 papers, 5.3k citations indexed

About

Pamela V. Chang is a scholar working on Molecular Biology, Oncology and Organic Chemistry. According to data from OpenAlex, Pamela V. Chang has authored 28 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 9 papers in Oncology and 8 papers in Organic Chemistry. Recurrent topics in Pamela V. Chang's work include Gut microbiota and health (11 papers), Glycosylation and Glycoproteins Research (9 papers) and Click Chemistry and Applications (7 papers). Pamela V. Chang is often cited by papers focused on Gut microbiota and health (11 papers), Glycosylation and Glycoproteins Research (9 papers) and Click Chemistry and Applications (7 papers). Pamela V. Chang collaborates with scholars based in United States, Germany and Russia. Pamela V. Chang's co-authors include Ruslan Medzhitov, Stefan Offermanns, Liming Hao, Carolyn R. Bertozzi, Jennifer A. Prescher, Nicholas J. Agard, Jeremy M. Baskin, Scott T. Laughlin, Julian A. Codelli and Samantha A. Scott and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Pamela V. Chang

28 papers receiving 5.2k citations

Hit Papers

The microbial metabolite butyrate regulates intestinal... 2007 2026 2013 2019 2014 2007 2010 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pamela V. Chang United States 18 3.8k 2.0k 817 571 463 28 5.3k
Hidetoshi Arima Japan 44 3.2k 0.8× 1.0k 0.5× 170 0.2× 367 0.6× 369 0.8× 264 7.2k
Young S. Kim United States 47 3.6k 0.9× 852 0.4× 735 0.9× 371 0.6× 1.0k 2.2× 146 6.2k
Matthew Lee United States 19 3.3k 0.9× 535 0.3× 349 0.4× 262 0.5× 225 0.5× 73 5.4k
Sven Frøkjær Denmark 41 4.2k 1.1× 560 0.3× 442 0.5× 1.3k 2.3× 648 1.4× 116 7.4k
Tom C. Karagiannis Australia 38 3.6k 0.9× 339 0.2× 233 0.3× 421 0.7× 427 0.9× 141 5.8k
Edward W. Tate United Kingdom 44 4.2k 1.1× 1.3k 0.6× 346 0.4× 139 0.2× 537 1.2× 207 6.7k
Ambikanandan Misra India 44 2.7k 0.7× 765 0.4× 266 0.3× 210 0.4× 293 0.6× 166 7.6k
Gary M. Gray United States 53 2.4k 0.6× 1.7k 0.8× 238 0.3× 613 1.1× 512 1.1× 266 9.5k
Franck Fieschi France 37 2.7k 0.7× 857 0.4× 460 0.6× 496 0.9× 1.7k 3.7× 119 5.2k
Serge Van Calenbergh Belgium 44 3.4k 0.9× 1.4k 0.7× 130 0.2× 134 0.2× 875 1.9× 227 6.3k

Countries citing papers authored by Pamela V. Chang

Since Specialization
Citations

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

Fields of papers citing papers by Pamela V. Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pamela V. Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Pamela V. Chang. A scholar is included among the top collaborators of Pamela V. 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 Pamela V. Chang. Pamela V. 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.
Han, Lin, et al.. (2024). Chemoproteomic profiling of substrate specificity in gut microbiota-associated bile salt hydrolases. Cell chemical biology. 32(1). 145–156.e9. 9 indexed citations
2.
Scott, Samantha A., Jingjing Fu, & Pamela V. Chang. (2024). Dopamine receptor D2 confers colonization resistance via microbial metabolites. Nature. 628(8006). 180–185. 34 indexed citations
3.
Chang, Pamela V.. (2024). Microbial metabolite-receptor interactions in the gut microbiome. Current Opinion in Chemical Biology. 83. 102539–102539. 6 indexed citations
4.
Parasar, Bibudha, et al.. (2024). Bile Salt Hydrolase Activity‐Based Probes for Monitoring Gut Microbial Bile Acid Metabolism. ChemBioChem. 25(10). e202300821–e202300821. 2 indexed citations
5.
Han, Lin & Pamela V. Chang. (2023). Activity-based protein profiling in microbes and the gut microbiome. Current Opinion in Chemical Biology. 76. 102351–102351. 6 indexed citations
6.
Chang, Pamela V., et al.. (2023). Electrostatic Interactions Dictate Bile Salt Hydrolase Substrate Preference. Biochemistry. 62(21). 3076–3084. 4 indexed citations
7.
Chang, Pamela V., et al.. (2022). Shedding Light on Bacterial Physiology with Click Chemistry. Israel Journal of Chemistry. 63(1-2). 1 indexed citations
8.
Parasar, Bibudha & Pamela V. Chang. (2022). BSH-TRAP: Bile salt hydrolase tagging and retrieval with activity-based probes. Methods in enzymology on CD-ROM/Methods in enzymology. 664. 85–102. 5 indexed citations
9.
Scott, Samantha A., Jingjing Fu, & Pamela V. Chang. (2020). Microbial tryptophan metabolites regulate gut barrier function via the aryl hydrocarbon receptor. Proceedings of the National Academy of Sciences. 117(32). 19376–19387. 448 indexed citations breakdown →
10.
Parasar, Bibudha & Pamela V. Chang. (2020). Engineered Th17 Cell Differentiation Using a Photoactivatable Immune Modulator. Journal of the American Chemical Society. 142(42). 18103–18108. 7 indexed citations
11.
Parasar, Bibudha & Pamela V. Chang. (2020). Finding the Sweet Spot for Breast Cancer Detection. ACS Central Science. 6(12). 2123–2125. 1 indexed citations
12.
Chang, Pamela V.. (2020). Chemical Mechanisms of Colonization Resistance by the Gut Microbial Metabolome. ACS Chemical Biology. 15(5). 1119–1126. 20 indexed citations
13.
Parasar, Bibudha, et al.. (2019). Chemoproteomic Profiling of Gut Microbiota-Associated Bile Salt Hydrolase Activity. ACS Central Science. 5(5). 867–873. 70 indexed citations
14.
Nicolas, Gaël & Pamela V. Chang. (2019). Deciphering the Chemical Lexicon of Host–Gut Microbiota Interactions. Trends in Pharmacological Sciences. 40(6). 430–445. 141 indexed citations
15.
Parasar, Bibudha & Pamela V. Chang. (2016). Chemical optogenetic modulation of inflammation and immunity. Chemical Science. 8(2). 1450–1453. 19 indexed citations
16.
Chang, Pamela V. & Carolyn R. Bertozzi. (2012). Imaging beyond the proteome. Chemical Communications. 48(71). 8864–8864. 69 indexed citations
17.
Chang, Pamela V., Jennifer A. Prescher, Ellen M. Sletten, et al.. (2010). Copper-free click chemistry in living animals. Proceedings of the National Academy of Sciences. 107(5). 1821–1826. 537 indexed citations breakdown →
18.
Chang, Pamela V., Danielle H. Dube, Ellen M. Sletten, & Carolyn R. Bertozzi. (2010). A Strategy for the Selective Imaging of Glycans Using Caged Metabolic Precursors. Journal of the American Chemical Society. 132(28). 9516–9518. 83 indexed citations
19.
Dong, Xu, et al.. (2008). Photoaffinity Isolation and Identification of Proteins in Cancer Cell Extracts that Bind to Platinum‐Modified DNA. ChemBioChem. 10(1). 141–157. 56 indexed citations
20.
Laughlin, Scott T., Nicholas J. Agard, Jeremy M. Baskin, et al.. (2006). Metabolic Labeling of Glycans with Azido Sugars for Visualization and Glycoproteomics. Methods in enzymology on CD-ROM/Methods in enzymology. 415. 230–250. 121 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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