SJ Li
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Cancer Research
- Biomedical Engineering
- Materials Chemistry
- Co-authors
- Borko FurhtDaniel SocekR.D.K. MisraXin GaiZhihong LiuYujie WangYen‐Hsu ChenJosé M. Amigó
- Topics
- Chaos-based Image/Signal Encryption (3 papers)Cancer-related molecular mechanisms research (3 papers)Neuroscience and Neuropharmacology Research (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
SJ Li
23 papers receiving 283 citations
Peers
Comparison fields: 5 of 85
- Molecular Biology 67
- Computer Vision and Pattern Recognition 61
- Cancer Research 48
- Biomedical Engineering 32
- Materials Chemistry 29
Countries citing papers authored by SJ Li
This map shows the geographic impact of SJ Li'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 SJ Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites SJ Li more than expected).
Fields of papers citing papers by SJ Li
This network shows the impact of papers produced by SJ Li. 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 SJ Li. The network helps show where SJ Li may publish in the future.
Co-authorship network of co-authors of SJ Li
This figure shows the co-authorship network connecting the top 25 collaborators of SJ Li. A scholar is included among the top collaborators of SJ Li 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 SJ Li. SJ Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 6 | |
| 4 | 6 | |
| 5 | 30 | |
| 6 | 46 | |
| 7 | 3 | |
| 8 | Expression level and distribution of HMGB1 in Sombati's cell model and kainic acid-induced epilepsy model. | 11 |
| 9 | 5 | |
| 10 | 19 | |
| 11 | Action learning to improve nursing students’ capacity in disaster preparedness | 3 |
| 12 | 8 | |
| 13 | 1 | |
| 14 | On the inadequacy of unimodal maps for cryptographic applications | 13 |
| 15 | 28 | |
| 16 | Distribution of Mo in Mo/ZSM-5 catalyst prepared by impregnation method | 3 |
| 17 | Enhanced 1-D Chaotic Key-Based Algorithm for Image Encryption | 47 |
| 18 | Cryptanalysis of a Class of Chaotic Stream Ciphers (一类混沌流密码的分析) | 1 |
| 19 | 1 | |
| 20 | 16 |
About SJ Li
SJ Li is a scholar working on Transplantation, Behavioral Neuroscience and Cancer Research, having authored 24 papers that have together received 299 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (3 papers), Cancer-related molecular mechanisms research (3 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Nephrology (23 citations), Cancer Research (48 citations) and Computer Vision and Pattern Recognition (61 citations). SJ Li has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Borko Furht, Daniel Socek, R.D.K. Misra, Xin Gai, Zhihong Liu, Yujie Wang, Yen‐Hsu Chen, José M. Amigó, Jian‐Ming Yang and David Arroyo. Their work appears in journals such as NeuroImage, American Journal of Clinical Nutrition and Translational Psychiatry.
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.