De Chang

5.0k citations
62 papers · 1.5k · 1 hit paper · h-index 16

Impact in

Papers in

De Chang

59 papers receiving 1.5k citations

De Chang's Hit Papers

Epidemiologic and Clinical Characteristics of Novel Coronavirus Infections Involving 13 Patients Outside Wuhan, China 2020 · 479 citations
4790+2+4Years since publication100200300400

Peers

De Chang
Comparison fields: 5 of 124
  • Molecular Medicine 124
  • Infectious Diseases 432
  • Applied Microbiology and Biotechnology 30
  • Modeling and Simulation 59
  • Neurology 149
Replace Tieshan Teng with:
Tieshan Teng China
Longxiang Xie China
Abualgasim Elgaili Abdalla Saudi Arabia
Francesca Benedetti United States
Tongyu Zhu China
Ni Tien Taiwan
Sajad Yaghoubi Iran
Seyed Mohammad Reza Hashemian Iran
De Chang relative to Tieshan Teng China Tieshan Teng's profile →
Citations per field
00.5×9.6×
Tieshan Teng · 1×
Citations per year

Countries citing papers authored by De Chang

Since Specialization
Citations

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

Fields of papers citing papers by De Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside De 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 De Chang Line = papers co-authored together De Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Epidemiologic and Clinical Characteristics of Novel Coronavirus Infections Involving 13 Patients Outside Wuhan, China
Hit paper breakdown →
2020479
2 2021178
3 2011108
4 201396
5 202060
6 202043
7 201743
8 201339
9 202034
10 201331
11 201430
12 202023
13 201321
14 202319
15 201417
16 201317
17 201414
18 201213
19 201213
20 202013

About De Chang

De Chang is a scholar working on Molecular Biology, Infectious Diseases, Physiology, Pulmonary and Respiratory Medicine and Ecology, having authored 62 papers that have together received 1.5k indexed citations. Recurring topics across this work include Spaceflight effects on biology (14 papers), COVID-19 Clinical Research Studies (11 papers), SARS-CoV-2 and COVID-19 Research (9 papers), Genomics and Phylogenetic Studies (8 papers), Space Exploration and Technology (5 papers), Long-Term Effects of COVID-19 (5 papers), Space Science and Extraterrestrial Life (4 papers) and Pediatric health and respiratory diseases (4 papers). The work is most often cited by research in Molecular Medicine (124 citations), Infectious Diseases (432 citations), Applied Microbiology and Biotechnology (30 citations), Modeling and Simulation (59 citations) and Neurology (149 citations). De Chang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Lokesh Sharma, Charles S. Dela Cruz, Lixin Xie, Minggui Lin, Guangfa Zhu, Lai Wei, Hong‐Zhen Du, Lei You, Yinghua Guo and Longxiang Su. Their work appears in journals such as Journal of Bacteriology, Frontiers in Immunology, ERJ Open Research, International Journal of COPD and Advances in Space Research.

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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