Ye Hou

2.8k total citations · 1 hit paper
34 papers, 1.9k citations indexed

About

Ye Hou is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Ye Hou has authored 34 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 10 papers in Cancer Research and 4 papers in Physiology. Recurrent topics in Ye Hou's work include Cancer-related molecular mechanisms research (8 papers), RNA Research and Splicing (8 papers) and RNA modifications and cancer (6 papers). Ye Hou is often cited by papers focused on Cancer-related molecular mechanisms research (8 papers), RNA Research and Splicing (8 papers) and RNA modifications and cancer (6 papers). Ye Hou collaborates with scholars based in China, United States and Bahrain. Ye Hou's co-authors include Jie Liu, Yingwen Cheng, Shuhong Zhao, Xinyun Li, Mingwei Chen, Akihiko Hirata, Takeshi Fujita, Jianli Kang, Yiyu Feng and Hongbo Zhang and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Nano Letters.

In The Last Decade

Ye Hou

33 papers receiving 1.9k citations

Hit Papers

Design and Synthesis of Hierarchical MnO2 Nanospheres/Car... 2010 2026 2015 2020 2010 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ye Hou China 16 929 762 495 393 367 34 1.9k
Yaqun Wang China 22 434 0.5× 1.0k 1.4× 536 1.1× 346 0.9× 299 0.8× 75 2.0k
Nuoxin Wang China 23 531 0.6× 422 0.6× 165 0.3× 610 1.6× 376 1.0× 41 2.0k
Fabien Giroud France 28 256 0.3× 1.6k 2.1× 422 0.9× 489 1.2× 193 0.5× 54 2.6k
Jinzhu Li China 22 872 0.9× 677 0.9× 739 1.5× 225 0.6× 631 1.7× 63 2.3k
Sukhyun Kang South Korea 27 128 0.1× 358 0.5× 106 0.2× 1.3k 3.4× 486 1.3× 60 2.2k
Chuanchuan Li China 26 482 0.5× 1.6k 2.1× 118 0.2× 285 0.7× 415 1.1× 82 2.3k
Jungkyun Im South Korea 17 201 0.2× 876 1.1× 1.0k 2.0× 351 0.9× 353 1.0× 45 2.8k
Chang Li China 28 861 0.9× 3.1k 4.1× 230 0.5× 144 0.4× 395 1.1× 78 3.5k
Qian Ma China 28 90 0.1× 475 0.6× 322 0.7× 368 0.9× 416 1.1× 75 1.9k

Countries citing papers authored by Ye Hou

Since Specialization
Citations

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

Fields of papers citing papers by Ye Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ye Hou

This figure shows the co-authorship network connecting the top 25 collaborators of Ye Hou. A scholar is included among the top collaborators of Ye Hou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ye Hou. Ye Hou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Qixuan, Radhika Mathur, Mark W. Youngblood, et al.. (2025). Spatial 3D genome organization reveals intratumor heterogeneity in primary glioblastoma samples. Science Advances. 11(11). eadn2830–eadn2830. 2 indexed citations
2.
Han, Yaling, et al.. (2024). Dietary supplements in polycystic ovary syndrome–current evidence. Frontiers in Endocrinology. 15. 1456571–1456571. 4 indexed citations
3.
Saleiro, Diana, Ewa M. Kościuczuk, Mariafausta Fischietti, et al.. (2023). Targeting CHAF1B Enhances IFN Activity against Myeloproliferative Neoplasm Cells. Cancer Research Communications. 3(5). 943–951. 3 indexed citations
4.
Hu, Mingyang, Yaping Guo, Ye Hou, et al.. (2022). Epigenomics analysis of miRNA cis-regulatory elements in pig muscle and fat tissues. Genomics. 114(2). 110276–110276. 7 indexed citations
5.
Bi, Honghao, Ye Hou, Juan Wang, et al.. (2022). Chromatin reconstruction during mouse terminal erythropoiesis. iScience. 25(12). 105554–105554. 5 indexed citations
6.
Hou, Ye, et al.. (2022). Research on sustainable design of sports centre based on algorithm verification. Applied Mathematics and Nonlinear Sciences. 7(2). 1023–1032. 3 indexed citations
7.
Hou, Ye, et al.. (2022). Preservation and utilisation of historic buildings in old district of Guangzhou from the perspective of space syntax. Applied Mathematics and Nonlinear Sciences. 7(2). 931–956. 2 indexed citations
8.
Huang, Tina, Ye Hou, Elizabeth T. Bartom, et al.. (2021). Epigenomic landscape and 3D genome structure in pediatric high-grade glioma. Science Advances. 7(23). 50 indexed citations
9.
Zhao, Yunxia, Ye Hou, Yueyuan Xu, et al.. (2021). A compendium and comparative epigenomics analysis of cis-regulatory elements in the pig genome. Nature Communications. 12(1). 2217–2217. 92 indexed citations
10.
Wang, Xiaotao, Jie Xu, Baozhen Zhang, et al.. (2021). Genome-wide detection of enhancer-hijacking events from chromatin interaction data in rearranged genomes. Nature Methods. 18(6). 661–668. 77 indexed citations
11.
Zhou, Huanhuan, Yue Xiang, Mingyang Hu, et al.. (2020). Chromatin accessibility is associated with the changed expression of miRNAs that target members of the Hippo pathway during myoblast differentiation. Cell Death and Disease. 11(2). 148–148. 13 indexed citations
12.
Hou, Ye, Liangliang Fu, Jingjin Li, et al.. (2018). Transcriptome Analysis of Potential miRNA Involved in Adipogenic Differentiation of C2C12 Myoblasts. Lipids. 53(4). 375–386. 19 indexed citations
13.
Xu, Yueyuan, Xiaolong Qi, Mingyang Hu, et al.. (2018). Transcriptome Analysis of Adipose Tissue Indicates That the cAMP Signaling Pathway Affects the Feed Efficiency of Pigs. Genes. 9(7). 336–336. 30 indexed citations
14.
Zou, Cheng, Jingxuan Li, Long Li, et al.. (2017). Transcriptome analysis reveals long intergenic non-coding RNAs involved in skeletal muscle growth and development in pig. Scientific Reports. 7(1). 8704–8704. 20 indexed citations
15.
Fu, Liangliang, Yueyuan Xu, Ye Hou, et al.. (2017). Proteomic analysis indicates that mitochondrial energy metabolism in skeletal muscle tissue is negatively correlated with feed efficiency in pigs. Scientific Reports. 7(1). 45291–45291. 44 indexed citations
16.
Zhao, Yunxia, Ye Hou, Changzhi Zhao, et al.. (2016). Cis-Natural Antisense Transcripts Are Mainly Co-expressed with Their Sense Transcripts and Primarily Related to Energy Metabolic Pathways during Muscle Development. International Journal of Biological Sciences. 12(8). 1010–1021. 7 indexed citations
17.
Lü, Jing, Ye Hou, Hui Wu, et al.. (2015). Transcriptome analysis of mRNA and miRNA in skeletal muscle indicates an important network for differential Residual Feed Intake in pigs. Scientific Reports. 5(1). 11953–11953. 95 indexed citations
18.
Hou, Ye, et al.. (2013). Toward the Theoretical Capacitance of RuO2 Reinforced by Highly Conductive Nanoporous Gold. Advanced Energy Materials. 3(7). 851–856. 190 indexed citations
19.
Hou, Ye. (2010). Experimental study of stress-strain curves of lightweight aggregate concrete. 1 indexed citations
20.
Hou, Ye, Jie Tang, Hongbo Zhang, et al.. (2009). Functionalized Few-Walled Carbon Nanotubes for Mechanical Reinforcement of Polymeric Composites. ACS Nano. 3(5). 1057–1062. 135 indexed citations

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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