Xiaoke Ma

3.6k citations
147 papers · 2.8k · h-index 31

Impact in

Papers in

    • Bioinformatics and Genomic Networks 39
    • Gene expression and cancer classification 21
    • Single-cell and spatial transcriptomics 12
    • Gene Regulatory Network Analysis 10
    • Complex Network Analysis Techniques 42
    • Opinion Dynamics and Social Influence 19

Xiaoke Ma

138 papers receiving 2.7k citations

Peers

Xiaoke Ma
Comparison fields: 5 of 141
  • Statistical and Nonlinear Physics 857
  • Computational Mathematics 39
  • Artificial Intelligence 823
  • Cancer Research 273
  • Molecular Biology 1.1k
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Lin Gao China
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Citations per field
00.5×5.6×
Lin Gao · 1×
Citations per year

Countries citing papers authored by Xiaoke Ma

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Xiaoke Ma Line = papers co-authored together Xiaoke Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 147 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012162
2 2017134
3 2018131
4 2009124
5 201798
6 201791
7 202281
8 202263
9 201455
10 201749
11 201249
12 202248
13 202147
14 202145
15 201543
16 201143
17 202043
18 201842
19 201638
20 202037

About Xiaoke Ma

Xiaoke Ma is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 147 papers that have together received 2.8k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (42 papers), Bioinformatics and Genomic Networks (39 papers), Advanced Graph Neural Networks (22 papers), Gene expression and cancer classification (21 papers), Opinion Dynamics and Social Influence (19 papers), Single-cell and spatial transcriptomics (12 papers), Gene Regulatory Network Analysis (10 papers) and Advanced Clustering Algorithms Research (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (857 citations), Computational Mathematics (39 citations), Artificial Intelligence (823 citations), Cancer Research (273 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, Xuerong Yong, Dongyuan Li, Haiyue Wang and Kai Tan. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Sciences, Knowledge-Based Systems, Briefings in Bioinformatics and Neurocomputing.

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.

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