Jin Sima
Impact in
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- Cellular Automata and Applications
- Quantum-Dot Cellular Automata
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- Advanced Data Storage Technologies
- Error Correcting Code Techniques
Papers in
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- DNA and Biological Computing 20
- Advanced biosensing and bioanalysis techniques 13
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- Algorithms and Data Compression 12
- Co-authors
- Jehoshua Bruck (19 shared papers)Ryan Gabrys (4 shared papers)Netanel Raviv (7 shared papers)Farzad Farnoud (2 shared papers)Wei Chen (2 shared papers)Zhang Bao (1 shared paper)Yong Mao (1 shared paper)Olgica Milenković (4 shared papers)
- Journals
- IEEE Transactions on Information Theory (6 papers)Tumor Biology (1 paper)Entropy (1 paper)Neoplasma (1 paper)PubMed (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Jin Sima
31 papers receiving 345 citations
Peers
Comparison fields: 5 of 28
- Computational Theory and Mathematics 92
- Computer Networks and Communications 117
- Artificial Intelligence 148
- Molecular Biology 283
- Cancer Research 9
Countries citing papers authored by Jin Sima
This map shows the geographic impact of Jin Sima'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 Jin Sima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Sima more than expected).
Fields of papers citing papers by Jin Sima
This network shows the impact of papers produced by Jin Sima. 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 Jin Sima. The network helps show where Jin Sima may publish in the future.
Co-authors
The 20 scholars most cited alongside Jin Sima, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 46 | |
| 2 | 2020 | 46 | |
| 3 | 2019 | 37 | |
| 4 | 2019 | 36 | |
| 5 | 2020 | 26 | |
| 6 | 2020 | 22 | |
| 7 | 2021 | 17 | |
| 8 | 2014 | 15 | |
| 9 | 2020 | 12 | |
| 10 | 2019 | 12 | |
| 11 | 2021 | 11 | |
| 12 | 2016 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2021 | 7 | |
| 15 | 2019 | 5 | |
| 16 | 2018 | 5 | |
| 17 | 2014 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2023 | 3 | |
| 20 | [Expression analysis of NOTCH1/HES1/PTEN signaling pathway in invasive bladder transitional cell carcinoma]. | 2012 | 3 |
About Jin Sima
Jin Sima is a scholar working on Molecular Biology, Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 32 papers that have together received 348 indexed citations. Recurring topics across this work include DNA and Biological Computing (20 papers), Advanced biosensing and bioanalysis techniques (13 papers), Algorithms and Data Compression (12 papers), Error Correcting Code Techniques (4 papers), Cellular Automata and Applications (3 papers), Cooperative Communication and Network Coding (3 papers), Advanced Data Storage Technologies (3 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Computational Theory and Mathematics (92 citations), Computer Networks and Communications (117 citations), Artificial Intelligence (148 citations), Molecular Biology (283 citations) and Cancer Research (9 citations). Jin Sima has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Jehoshua Bruck, Ryan Gabrys, Netanel Raviv, Farzad Farnoud, Wei Chen, Zhang Bao, Yong Mao, Olgica Milenković, Moshe Schwartz and Ilan Shomorony. Their work appears in journals such as IEEE Transactions on Information Theory, Tumor Biology, Entropy, Neoplasma and PubMed.
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.