Xiaoming Ju
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Oncology top 5%
- Cancer-related Molecular Pathways
- Cancer Cells and Metastasis
Papers in
-
- DNA Repair Mechanisms 3
- PI3K/AKT/mTOR signaling in cancer 3
- Oncology 9
- Cancer-related Molecular Pathways 6
- Cancer Cells and Metastasis 4
- Co-authors
- Richard G. Pestell (19 shared papers)Chenguang Wang (11 shared papers)Manran Liu (8 shared papers)Mathew C. Casimiro (12 shared papers)Xuanmao Jiao (10 shared papers)Zhiping Li (9 shared papers)Sanjay Katiyar (9 shared papers)Michael P. Lisanti (9 shared papers)
- Journals
- Cancer Research (6 papers)Proceedings of the National Academy of Sciences (3 papers)Molecular Biology of the Cell (2 papers)Oncotarget (2 papers)Nature Communications (1 paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Xiaoming Ju
29 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 107
- Cancer Research 550
- Oncology 540
- Molecular Biology 1.0k
- Cell Biology 135
- Immunology 103
Countries citing papers authored by Xiaoming Ju
This map shows the geographic impact of Xiaoming Ju'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 Xiaoming Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoming Ju more than expected).
Fields of papers citing papers by Xiaoming Ju
This network shows the impact of papers produced by Xiaoming Ju. 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 Xiaoming Ju. The network helps show where Xiaoming Ju may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoming Ju, 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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 295 | |
| 2 | 2010 | 177 | |
| 3 | 2007 | 162 | |
| 4 | 2009 | 159 | |
| 5 | 2006 | 147 | |
| 6 | 2006 | 107 | |
| 7 | 2008 | 73 | |
| 8 | 2015 | 60 | |
| 9 | 2013 | 53 | |
| 10 | 2009 | 38 | |
| 11 | 2008 | 36 | |
| 12 | 2014 | 33 | |
| 13 | 2015 | 32 | |
| 14 | 2008 | 29 | |
| 15 | 2014 | 29 | |
| 16 | 2018 | 27 | |
| 17 | 2010 | 21 | |
| 18 | 2019 | 20 | |
| 19 | 2012 | 16 | |
| 20 | 2020 | 12 |
About Xiaoming Ju
Xiaoming Ju is a scholar working on Molecular Biology, Oncology, Computer Vision and Pattern Recognition, Cancer Research and Artificial Intelligence, having authored 34 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Cancer-related Molecular Pathways (6 papers), Cancer Cells and Metastasis (4 papers), MicroRNA in disease regulation (4 papers), DNA Repair Mechanisms (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), PI3K/AKT/mTOR signaling in cancer (3 papers) and Hippo pathway signaling and YAP/TAZ (2 papers). The work is most often cited by research in Cancer Research (550 citations), Oncology (540 citations), Molecular Biology (1.0k citations), Cell Biology (135 citations) and Immunology (103 citations). Xiaoming Ju has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Richard G. Pestell, Chenguang Wang, Manran Liu, Mathew C. Casimiro, Xuanmao Jiao, Zhiping Li, Sanjay Katiyar, Michael P. Lisanti, Zuoren Yu and Kongming Wu. Their work appears in journals such as Cancer Research, Proceedings of the National Academy of Sciences, Molecular Biology of the Cell, Oncotarget and Nature Communications.
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.