David Chang
- Immunology top 5%
- Molecular Biology top 10%
- Oncology top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Pathology and Forensic Medicine top 5%
- Co-authors
- C.Y. LaiMichinaga MatsumotoMin YouDavid W. CrabbNoboru NakaiHsin‐Hsiung TaiGwyneth VanJohn Delaney
- Topics
- T-cell and B-cell Immunology (4 papers)Toxin Mechanisms and Immunotoxins (4 papers)Glycosylation and Glycoproteins Research (3 papers)
- Partner nations
- United StatesSwedenAustralia
In The Last Decade
David Chang
32 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 115
- Immunology 803
- Molecular Biology 729
- Oncology 315
- Radiology, Nuclear Medicine and Imaging 301
- Pathology and Forensic Medicine 251
Countries citing papers authored by David Chang
This map shows the geographic impact of David 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 David Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Chang more than expected).
Fields of papers citing papers by David Chang
This network shows the impact of papers produced by David 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 David Chang. The network helps show where David Chang may publish in the future.
Co-authorship network of co-authors of David Chang
This figure shows the co-authorship network connecting the top 25 collaborators of David Chang. A scholar is included among the top collaborators of David 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 David Chang. David Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 85 | |
| 2 | 9 | |
| 3 | 19 | |
| 4 | 27 | |
| 5 | 378 | |
| 6 | 50 | |
| 7 | 14 | |
| 8 | 35 | |
| 9 | 4 | |
| 10 | 10 | |
| 11 | 202 | |
| 12 | Factors affecting the generation of dendritic cells by culture of human monocytes in serum-free medium. | 1 |
| 13 | 20 | |
| 14 | 8 | |
| 15 | Mouse monoclonal antibody (WI-MN-1) against malignant melanoma. | 7 |
| 16 | Monoclonal antibody against myeloid leukemia cell line (KG-1). | 4 |
| 17 | 14 | |
| 18 | Monoclonal antibody against a unique antigen on human acute promyelocytic leukemia cell line (HL-60). | 2 |
| 19 | 7 | |
| 20 | 146 |
About David Chang
David Chang is a scholar working on Immunology, Endocrinology and Genetics, having authored 32 papers that have together received 2.2k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (4 papers), Toxin Mechanisms and Immunotoxins (4 papers) and Glycosylation and Glycoproteins Research (3 papers). The work is most often cited by research in Immunology (803 citations), Biochemistry (106 citations) and Pathology and Forensic Medicine (251 citations). David Chang has collaborated with scholars based in United States, Sweden and Australia. Frequent co-authors include C.Y. Lai, Michinaga Matsumoto, Min You, David W. Crabb, Noboru Nakai, Hsin‐Hsiung Tai, Gwyneth Van, John Delaney, Nessa Hawkins and Xing-Zhong Xia. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.