Jeremy E. Wilusz
- Molecular Biology top 0.5%
- Cancer Research top 0.1%
- Plant Science top 10%
- Immunology top 10%
- Genetics top 10%
- Co-authors
- David L. SpectorHongjae SunwooDongming LiangPhillip A. SharpDeirdre C. TatomerSusan M. FreierMei‐Sheng XiaoMichael G. Kearse
- Topics
- RNA Research and Splicing (39 papers)RNA modifications and cancer (32 papers)Circular RNAs in diseases (23 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Jeremy E. Wilusz
52 papers receiving 9.1k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Molecular Biology 8.5k
- Cancer Research 6.1k
- Plant Science 347
- Immunology 313
- Genetics 234
Countries citing papers authored by Jeremy E. Wilusz
This map shows the geographic impact of Jeremy E. Wilusz'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 Jeremy E. Wilusz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeremy E. Wilusz more than expected).
Fields of papers citing papers by Jeremy E. Wilusz
This network shows the impact of papers produced by Jeremy E. Wilusz. 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 Jeremy E. Wilusz. The network helps show where Jeremy E. Wilusz may publish in the future.
Co-authorship network of co-authors of Jeremy E. Wilusz
This figure shows the co-authorship network connecting the top 25 collaborators of Jeremy E. Wilusz. A scholar is included among the top collaborators of Jeremy E. Wilusz 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 Jeremy E. Wilusz. Jeremy E. Wilusz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 8 | |
| 3 | 10 | |
| 4 | 91 | |
| 5 | 11 | |
| 6 | 55 | |
| 7 | 5 | |
| 8 | 15 | |
| 9 | 165 | |
| 10 | 152 | |
| 11 | 53 | |
| 12 | 103 | |
| 13 | 53 | |
| 14 | 362 | |
| 15 | Short intronic repeat sequences facilitate circular RNA productionbreakdown → | 763 |
| 16 | 370 | |
| 17 | 53 | |
| 18 | 3′ End Processing of a Long Nuclear-Retained Noncoding RNA Yields a tRNA-like Cytoplasmic RNAbreakdown → | 575 |
| 19 | MEN ε/β nuclear-retained non-coding RNAs are up-regulated upon muscle differentiation and are essential components of paraspecklesbreakdown → | 528 |
| 20 | 21 |
About Jeremy E. Wilusz
Jeremy E. Wilusz is a scholar working on Cancer Research, Molecular Biology and Aging, having authored 52 papers that have together received 9.1k indexed citations. Recurring topics across this work include RNA Research and Splicing (39 papers), RNA modifications and cancer (32 papers) and Circular RNAs in diseases (23 papers). The work is most often cited by research in Cancer Research (6.1k citations), Molecular Biology (8.5k citations) and Endocrinology (185 citations). Jeremy E. Wilusz has collaborated with scholars based in United States, China and Germany. Frequent co-authors include David L. Spector, Hongjae Sunwoo, Dongming Liang, Phillip A. Sharp, Deirdre C. Tatomer, Susan M. Freier, Mei‐Sheng Xiao, Michael G. Kearse, Yuxi Ai and Sara Cherry. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.