Yu Luan

1.2k total citations
27 papers, 417 citations indexed

About

Yu Luan is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Yu Luan has authored 27 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 11 papers in Cancer Research and 4 papers in Genetics. Recurrent topics in Yu Luan's work include Cancer-related molecular mechanisms research (7 papers), Genomics and Chromatin Dynamics (7 papers) and RNA Research and Splicing (6 papers). Yu Luan is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), Genomics and Chromatin Dynamics (7 papers) and RNA Research and Splicing (6 papers). Yu Luan collaborates with scholars based in China, United States and United Kingdom. Yu Luan's co-authors include Ye Hou, Shuhong Zhao, Feng Yue, Xinyun Li, Yunxia Zhao, Xiaotao Wang, Yueyuan Xu, Xiaolong Qi, Mingyang Hu and Huanhuan Zhou and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Yu Luan

27 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu Luan China 11 278 138 128 48 35 27 417
Hongbao Wang China 12 194 0.7× 126 0.9× 85 0.7× 75 1.6× 29 0.8× 25 342
Jieping Huang China 12 234 0.8× 171 1.2× 125 1.0× 74 1.5× 56 1.6× 52 448
Kaiqing Liu China 11 219 0.8× 144 1.0× 46 0.4× 56 1.2× 35 1.0× 16 340
Yumin Zhao China 10 137 0.5× 158 1.1× 128 1.0× 29 0.6× 40 1.1× 23 320
Itishri Sahu India 12 234 0.8× 63 0.5× 47 0.4× 59 1.2× 26 0.7× 25 418
Lisheng Dai China 14 412 1.5× 361 2.6× 116 0.9× 34 0.7× 24 0.7× 28 639
Xinglei Qi China 17 470 1.7× 310 2.2× 329 2.6× 48 1.0× 47 1.3× 40 692
Mengyi Huang China 12 207 0.7× 134 1.0× 26 0.2× 20 0.4× 29 0.8× 25 347
Po-Ju Chen United States 8 227 0.8× 146 1.1× 60 0.5× 60 1.3× 6 0.2× 13 376
Xinping Wang China 11 211 0.8× 191 1.4× 87 0.7× 48 1.0× 36 1.0× 33 385

Countries citing papers authored by Yu Luan

Since Specialization
Citations

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

Fields of papers citing papers by Yu Luan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Luan

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Luan. A scholar is included among the top collaborators of Yu Luan 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 Yu Luan. Yu Luan 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.
Luan, Yu, Shanshan Zhao, Meiyan Li, et al.. (2025). Single-cell RNA sequencing for characterizing the immune communication and iron metabolism roles in CD31+ glioma cells. Translational Cancer Research. 14(4). 2421–2439. 1 indexed citations
3.
Li, Jue, Jie Bai, Michihiro Hashimoto, et al.. (2025). Loss of Cpt1a results in elevated glucose-fueled mitochondrial oxidative phosphorylation and defective hematopoietic stem cells. Journal of Clinical Investigation. 135(5). 2 indexed citations
4.
Duan, Ziheng, Siwei Xu, Ahyeon Hwang, et al.. (2024). scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding. Briefings in Bioinformatics. 25(2). 4 indexed citations
5.
Zhang, Lixia, Xinyue Zhou, Pengcheng Zhang, et al.. (2024). CRISPR screen of venetoclax response-associated genes identifies transcription factor ZNF740 as a key functional regulator. Cell Death and Disease. 15(8). 627–627. 2 indexed citations
6.
7.
Yang, Hongbo, Qiushi Jin, Xiaotao Wang, et al.. (2023). Enhancer Coamplification and Hijacking Promote Oncogene Expression in Liposarcoma. Cancer Research. 83(9). 1517–1530. 14 indexed citations
8.
Xu, Bing, Yi Sui, Hui Li, et al.. (2023). Cytohesin-4 Upregulation in Glioma-Associated M2 Macrophages Is Correlated with Pyroptosis and Poor Prognosis. Journal of Molecular Neuroscience. 73(2-3). 143–158. 8 indexed citations
9.
Xu, Bing, Yi Sui, Yu Luan, et al.. (2022). Pan-Cancer Analysis and Validation Reveals that D-Dimer-Related Genes are Prognostic and Downregulate CD8+ T Cells via TGF-Beta Signaling in Gastric Cancer. Frontiers in Molecular Biosciences. 9. 790706–790706. 6 indexed citations
10.
Sun, Fei, Jianhong Ou, Adam R. Shoffner, et al.. (2022). Enhancer selection dictates gene expression responses in remote organs during tissue regeneration. Nature Cell Biology. 24(5). 685–696. 30 indexed citations
11.
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
12.
Luan, Yu, et al.. (2021). The Role of Mondo Family Transcription Factors in Nutrient-Sensing and Obesity. Frontiers in Endocrinology. 12. 653972–653972. 11 indexed citations
13.
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
14.
Zhao, Changzhi, Shengsong Xie, Hui Wu, et al.. (2019). Quantification of allelic differential expression using a simple Fluorescence primer PCR-RFLP-based method. Scientific Reports. 9(1). 6334–6334. 1 indexed citations
15.
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
16.
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
17.
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
18.
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
19.
Li, Cencen, Xiao Wang, Huimin Cai, et al.. (2016). Molecular microevolution and epigenetic patterns of the long non-coding gene H19 show its potential function in pig domestication and breed divergence. BMC Evolutionary Biology. 16(1). 87–87. 13 indexed citations
20.
Zhao, Yunxia, Ye Hou, Fei Liu, et al.. (2016). Transcriptome Analysis Reveals that Vitamin A Metabolism in the Liver Affects Feed Efficiency in Pigs. G3 Genes Genomes Genetics. 6(11). 3615–3624. 37 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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