Xiaodan Hou

937 citations
31 papers · 758 · h-index 14

Impact in

    • Cancer, Hypoxia, and Metabolism
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer Cells and Metastasis

Papers in

Xiaodan Hou

28 papers receiving 742 citations

Peers

Xiaodan Hou
Comparison fields: 5 of 88
  • Cancer Research 307
  • Oncology 218
  • Molecular Biology 484
  • Computer Vision and Pattern Recognition 80
  • Immunology 79
Replace Anjia Han with:
Anjia Han China
Eun Jung Choi South Korea
Yuehua Li China
Xinxing Wu China
Ye Chen China
Tao Xie China
Qiangbo Zhang China
Junwei Huang China
Shang Cai China
Xiaodan Hou relative to Anjia Han China Anjia Han's profile →
Citations per field
00.5×1.5×
Anjia Han · 1×
Citations per year

Countries citing papers authored by Xiaodan Hou

Since Specialization
Citations

This map shows the geographic impact of Xiaodan Hou'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 Xiaodan Hou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaodan Hou more than expected).

Fields of papers citing papers by Xiaodan Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaodan Hou. 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 Xiaodan Hou. The network helps show where Xiaodan Hou may publish in the future.

Co-authors

The 25 scholars most cited alongside Xiaodan Hou, 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 Xiaodan Hou Line = papers co-authored together Xiaodan Hou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015265
2 2013158
3 201959
4 201944
5 202124
6 201922
7 201718
8 201418
9 201617
10 200817
11 202116
12 201215
13 201913
14 201313
15 201713
16 200910
17 20126
18 20235
19 20165
20 20164

About Xiaodan Hou

Xiaodan Hou is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Cancer Research, Artificial Intelligence and Oncology, having authored 31 papers that have together received 758 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (13 papers), Digital Media Forensic Detection (13 papers), Ubiquitin and proteasome pathways (4 papers), Chaos-based Image/Signal Encryption (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Anomaly Detection Techniques and Applications (3 papers) and MicroRNA in disease regulation (2 papers). The work is most often cited by research in Cancer Research (307 citations), Oncology (218 citations), Molecular Biology (484 citations), Computer Vision and Pattern Recognition (80 citations) and Immunology (79 citations). Xiaodan Hou has collaborated with scholars based in China and United States. Frequent co-authors include Jun Mi, Daoxiang Zhang, Zhimin Shi, Shimin Zhao, Pan Sun, Jian Zhang, Yong‐Bin Wang, Binhua P. Zhou, Jinyi Liu and Wujun Xiong. Their work appears in journals such as Separation Science and Technology, Signal Processing Image Communication, Molecular Neurobiology, Molecular Cancer Therapeutics and Scientific Reports.

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.

Explore authors with similar magnitude of impact