Xiaoke Ma
Impact in
- Computational Mathematics top 5%
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in ⓘ
-
- Complex Network Analysis Techniques 41
- Opinion Dynamics and Social Influence 19
- Co-authors
- Lin Gao (13 shared papers)Di Dong (2 shared papers)Penggang Sun (5 shared papers)Quan Wang (3 shared papers)Guimin Qin (2 shared papers)Maoguo Gong (9 shared papers)Dongyuan Li (6 shared papers)Xuerong Yong (2 shared papers)
- Journals
- IEEE/ACM Transactions on Computational Biology and Bioinformatics (9 papers)Information Sciences (6 papers)Knowledge-Based Systems (5 papers)Briefings in Bioinformatics (5 papers)IEEE Transactions on Big Data (4 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaoke Ma
132 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 142
- Computational Mathematics 39
- Statistical and Nonlinear Physics 802
- Artificial Intelligence 774
- Cancer Research 288
- Molecular Biology 1.1k
Countries citing papers authored by Xiaoke Ma
This map shows the geographic impact of Xiaoke Ma'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 Xiaoke Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoke Ma more than expected).
Fields of papers citing papers by Xiaoke Ma
This network shows the impact of papers produced by Xiaoke Ma. 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 Xiaoke Ma. The network helps show where Xiaoke Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoke Ma, 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 144 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 160 | |
| 2 | 2018 | 126 | |
| 3 | 2017 | 124 | |
| 4 | 2009 | 114 | |
| 5 | 2017 | 91 | |
| 6 | 2017 | 81 | |
| 7 | 2022 | 76 | |
| 8 | 2022 | 58 | |
| 9 | 2014 | 53 | |
| 10 | 2017 | 47 | |
| 11 | 2021 | 45 | |
| 12 | 2022 | 44 | |
| 13 | 2012 | 44 | |
| 14 | 2015 | 43 | |
| 15 | 2011 | 43 | |
| 16 | 2020 | 41 | |
| 17 | 2018 | 40 | |
| 18 | 2021 | 40 | |
| 19 | 2016 | 36 | |
| 20 | 2020 | 35 |
About Xiaoke Ma
Xiaoke Ma is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics, Artificial Intelligence, Molecular Biology and Biophysics, having authored 144 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (41 papers), Complex Network Analysis Techniques (41 papers), Gene expression and cancer classification (25 papers), Advanced Graph Neural Networks (23 papers), Opinion Dynamics and Social Influence (19 papers), Single-cell and spatial transcriptomics (11 papers), Gene Regulatory Network Analysis (11 papers) and Computational Drug Discovery Methods (9 papers). The work is most often cited by research in Computational Mathematics (39 citations), Statistical and Nonlinear Physics (802 citations), Artificial Intelligence (774 citations), Cancer Research (288 citations) and Molecular Biology (1.1k citations). Xiaoke Ma has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Lin Gao, Di Dong, Penggang Sun, Quan Wang, Guimin Qin, Maoguo Gong, Dongyuan Li, Xuerong Yong, Kai Tan and Haiyue Wang. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Sciences, Knowledge-Based Systems, Briefings in Bioinformatics and IEEE Transactions on Big Data.
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.