Baojun Chang

1.9k citations
25 papers · 1.3k · h-index 17

Impact in

Papers in

Baojun Chang

25 papers receiving 1.3k citations

Peers

Baojun Chang
Comparison fields: 5 of 93
  • Sensory Systems 144
  • Cardiology and Cardiovascular Medicine 370
  • Pathology and Forensic Medicine 163
  • Biophysics 53
  • Cell Biology 137
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Shi Pan United States
Rebecca S. Keller United States
Boris Manoury France
Virginia S. Hahn United States
Junlian Gu China
Pu Duann United States
Voahanginirina Randriamboavonjy Germany
Yu‐Pei Yuan China
Toshihide Shima Japan
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Citations per field
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Citations per year

Countries citing papers authored by Baojun Chang

Since Specialization
Citations

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

Fields of papers citing papers by Baojun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Baojun Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Baojun Chang Line = papers co-authored together Baojun Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988302
2 2010215
3 2002146
4 2016105
5 200474
6 200966
7 201451
8 200142
9 201736
10 201635
11 201335
12 200134
13 201529
14 200426
15 202119
16 201317
17 202216
18 201315
19 200314
20 202211

About Baojun Chang

Baojun Chang is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Oncology, Pathology and Forensic Medicine and Cell Biology, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Chemotherapy-induced organ toxicity mitigation (4 papers), Ubiquitin and proteasome pathways (3 papers), Pulmonary Hypertension Research and Treatments (3 papers), Hippo pathway signaling and YAP/TAZ (3 papers), Glycosylation and Glycoproteins Research (2 papers), Metabolism and Genetic Disorders (2 papers), Chemotherapy-induced cardiotoxicity and mitigation (2 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Sensory Systems (144 citations), Cardiology and Cardiovascular Medicine (370 citations), Pathology and Forensic Medicine (163 citations), Biophysics (53 citations) and Cell Biology (137 citations). Baojun Chang has collaborated with scholars based in United States, Japan and Norway. Frequent co-authors include Masayasu Inoue, Manabu Nishikawa, Xu Wu, Jeffery D. Molkentin, Petra Eder, Eisuke F. Sato, Robert J. Boucek, Dean E. Brenner, Phillip S. Mushlin and Sidney Fleischer. Their work appears in journals such as Archives of Biochemistry and Biophysics, Proceedings of the National Academy of Sciences, Science Signaling, Cancer Letters and Nature Communications.

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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