Binbin Ji
Impact in
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- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
- MicroRNA in disease regulation
Papers in
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- Circular RNAs in diseases 3
- Machine Learning in Bioinformatics 2
- Genomics and Phylogenetic Studies 2
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- Cancer-related molecular mechanisms research 4
- MicroRNA in disease regulation 2
- Co-authors
- Jialiang Yang (6 shared papers)Geng Tian (4 shared papers)Yuebin Liang (3 shared papers)Lei Guo (1 shared paper)Zixuan Yang (1 shared paper)Peng Yuan (1 shared paper)Yuan Xu (1 shared paper)Songlin Gao (1 shared paper)
- Journals
- Frontiers in Genetics (5 papers)Journal of Applied Polymer Science (1 paper)Forests (1 paper)Frontiers in Aging Neuroscience (1 paper)Cell Death and Disease (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Binbin Ji
21 papers receiving 396 citations
Binbin Ji's Hit Papers
Peers
Comparison fields: 5 of 87
- Cancer Research 123
- Health Informatics 8
- Radiology, Nuclear Medicine and Imaging 93
- Neurology 27
- Oncology 78
Countries citing papers authored by Binbin Ji
This map shows the geographic impact of Binbin Ji'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 Binbin Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binbin Ji more than expected).
Fields of papers citing papers by Binbin Ji
This network shows the impact of papers produced by Binbin Ji. 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 Binbin Ji. The network helps show where Binbin Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Binbin Ji, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Prediction of HER2-positive breast cancer recurrence and metastasis risk from histopathological images and clinical information via multimodal deep learning Hit paper breakdown → | 2021 | 158 |
| 2 | 2018 | 40 | |
| 3 | 2022 | 39 | |
| 4 | 2021 | 26 | |
| 5 | 2018 | 24 | |
| 6 | 2021 | 17 | |
| 7 | 2016 | 15 | |
| 8 | 2019 | 13 | |
| 9 | 2020 | 11 | |
| 10 | 2019 | 11 | |
| 11 | 2022 | 11 | |
| 12 | 2011 | 9 | |
| 13 | 2021 | 6 | |
| 14 | 2024 | 5 | |
| 15 | 2015 | 5 | |
| 16 | 2024 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2022 | 2 | |
| 19 | 2021 | 2 | |
| 20 | 2020 | 2 |
About Binbin Ji
Binbin Ji is a scholar working on Molecular Biology, Cancer Research, Radiology, Nuclear Medicine and Imaging, Physiology and Genetics, having authored 23 papers that have together received 403 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (4 papers), Circular RNAs in diseases (3 papers), Pain Mechanisms and Treatments (3 papers), MicroRNA in disease regulation (2 papers), Machine Learning in Bioinformatics (2 papers), Computational Drug Discovery Methods (2 papers), Genomics and Phylogenetic Studies (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Cancer Research (123 citations), Health Informatics (8 citations), Radiology, Nuclear Medicine and Imaging (93 citations), Neurology (27 citations) and Oncology (78 citations). Binbin Ji has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Jialiang Yang, Geng Tian, Yuebin Liang, Lei Guo, Zixuan Yang, Peng Yuan, Yuan Xu, Songlin Gao, Yuhua Yao and Bo Liao. Their work appears in journals such as Frontiers in Genetics, Journal of Applied Polymer Science, Forests, Frontiers in Aging Neuroscience and Cell Death and Disease.
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.