Jeffrey T. Chang
- Molecular Biology top 0.5%
- Cancer Research top 1%
- Oncology top 2%
- Genetics top 2%
- Pulmonary and Respiratory Medicine top 5%
- Co-authors
- Brad ChapmanJoseph R. NevinsPeter CockFrank KauffBartek WilczyńskiIddo FriedbergCymon J. CoxTiago Antão
- Topics
- Cancer Cells and Metastasis (20 papers)Bioinformatics and Genomic Networks (15 papers)Cancer Genomics and Diagnostics (11 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Jeffrey T. Chang
102 papers receiving 9.3k citations
Hit Papers
Peers
Comparison fields: 5 of 201
- Molecular Biology 6.6k
- Cancer Research 1.6k
- Oncology 1.5k
- Genetics 888
- Pulmonary and Respiratory Medicine 657
Countries citing papers authored by Jeffrey T. Chang
This map shows the geographic impact of Jeffrey T. 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 Jeffrey T. Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey T. Chang more than expected).
Fields of papers citing papers by Jeffrey T. Chang
This network shows the impact of papers produced by Jeffrey T. 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 Jeffrey T. Chang. The network helps show where Jeffrey T. Chang may publish in the future.
Co-authorship network of co-authors of Jeffrey T. Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey T. Chang. A scholar is included among the top collaborators of Jeffrey T. 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 Jeffrey T. Chang. Jeffrey T. 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 | 0 | |
| 2 | 4 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 59 | |
| 6 | 8 | |
| 7 | 5 | |
| 8 | 11 | |
| 9 | 20 | |
| 10 | 41 | |
| 11 | 67 | |
| 12 | Investigating the Arden hypothesis: a pilot investigation of the prevention of dark adaptation as complementary therapy for diabetic retinopathy and macular edema | 0 |
| 13 | 37 | |
| 14 | 125 | |
| 15 | 220 | |
| 16 | 133 | |
| 17 | 96 | |
| 18 | 48 | |
| 19 | 56 | |
| 20 | Edinburgh-Stanford TREC-2003 Genomics Track. | 4 |
About Jeffrey T. Chang
Jeffrey T. Chang is a scholar working on Cancer Research, Oncology and Molecular Biology, having authored 109 papers that have together received 9.5k indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (20 papers), Bioinformatics and Genomic Networks (15 papers) and Cancer Genomics and Diagnostics (11 papers). The work is most often cited by research in Cancer Research (1.6k citations), Molecular Biology (6.6k citations) and Oncology (1.5k citations). Jeffrey T. Chang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Brad Chapman, Joseph R. Nevins, Peter Cock, Frank Kauff, Bartek Wilczyński, Iddo Friedberg, Cymon J. Cox, Tiago Antão, Thomas Hamelryck and Michiel de Hoon. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids 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.