Mengjin Zhu

3.7k total citations · 1 hit paper
106 papers, 2.4k citations indexed

About

Mengjin Zhu is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Mengjin Zhu has authored 106 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Molecular Biology, 38 papers in Genetics and 26 papers in Immunology. Recurrent topics in Mengjin Zhu's work include Genetic and phenotypic traits in livestock (23 papers), Genetic Mapping and Diversity in Plants and Animals (21 papers) and Cancer-related molecular mechanisms research (19 papers). Mengjin Zhu is often cited by papers focused on Genetic and phenotypic traits in livestock (23 papers), Genetic Mapping and Diversity in Plants and Animals (21 papers) and Cancer-related molecular mechanisms research (19 papers). Mengjin Zhu collaborates with scholars based in China, United States and France. Mengjin Zhu's co-authors include Shuhong Zhao, Xinyun Li, Xiaolei Liu, Zhenshuang Tang, Jingya Xu, Dong Yin, Lilin Yin, Mei Yu, Haohao Zhang and Xiaohui Yuan and has published in prestigious journals such as Nature Communications, The Journal of Immunology and PLoS ONE.

In The Last Decade

Mengjin Zhu

98 papers receiving 2.3k citations

Hit Papers

rMVP: A Memory-Efficient, Visualization-Enhanced, and Par... 2021 2026 2022 2024 2021 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mengjin Zhu China 21 1.0k 970 511 502 277 106 2.4k
Jonathan E. Beever United States 25 705 0.7× 1.2k 1.2× 398 0.8× 213 0.4× 161 0.6× 86 2.0k
Shujun Zhang China 26 974 1.0× 509 0.5× 282 0.6× 249 0.5× 248 0.9× 132 2.2k
Jiuzhou Song United States 32 2.0k 1.9× 1.8k 1.9× 807 1.6× 827 1.6× 321 1.2× 167 3.9k
Susanna Cirera Denmark 29 1.5k 1.5× 561 0.6× 238 0.5× 790 1.6× 219 0.8× 111 2.8k
Bo Thomsen Denmark 30 1.5k 1.5× 1.1k 1.1× 373 0.7× 325 0.6× 89 0.3× 79 2.6k
Suneel Kumar Onteru India 21 743 0.7× 738 0.8× 145 0.3× 578 1.2× 189 0.7× 95 1.9k
Alex Clop Spain 23 1.3k 1.3× 1.3k 1.4× 260 0.5× 588 1.2× 154 0.6× 52 2.6k
Stephanie McKay United States 25 584 0.6× 1.7k 1.7× 461 0.9× 430 0.9× 66 0.2× 55 2.4k
Tom Goldammer Germany 29 859 0.9× 931 1.0× 313 0.6× 380 0.8× 1.5k 5.4× 148 3.2k
Rachel Hawken Australia 32 726 0.7× 2.4k 2.4× 426 0.8× 403 0.8× 142 0.5× 92 3.1k

Countries citing papers authored by Mengjin Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Mengjin Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mengjin Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Mengjin Zhu. A scholar is included among the top collaborators of Mengjin Zhu 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 Mengjin Zhu. Mengjin Zhu 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.
Li, Wenlin, et al.. (2025). SIGEL: a context-aware genomic representation learning framework for spatial genomics analysis. Genome biology. 26(1). 287–287.
4.
Guo, Yaping, Wei Zhang, Daoyuan Wang, et al.. (2024). Single-Cell RNA-Sequencing Reveals Heterogeneity and Transcriptional Dynamics in Porcine Circulating CD8+ T Cells. Cells. 13(8). 692–692. 1 indexed citations
5.
6.
Zhou, Honghong, Zhao Zhang, Hao Peng, et al.. (2024). H3K27ac modification and transcription characteristics of adipose and muscle tissues in Chuxiang Black pig. Animal Genetics. 55(2). 217–229.
7.
Yin, Lilin, Haohao Zhang, Zhenshuang Tang, et al.. (2021). rMVP: A Memory-Efficient, Visualization-Enhanced, and Parallel-Accelerated Tool for Genome-Wide Association Study. Genomics Proteomics & Bioinformatics. 19(4). 619–628. 653 indexed citations breakdown →
8.
Zhou, Geyu, Tao Xiang, Yunlong Ma, et al.. (2021). Characterization of genetic fundamentals for piglet mortality at birth in Yorkshire, Landrace, and Duroc sows. Animal Genetics. 53(1). 142–145. 2 indexed citations
9.
Zhao, Changzhi, Hailong Liu, Tianhe Xiao, et al.. (2020). CRISPR screening of porcine sgRNA library identifies host factors associated with Japanese encephalitis virus replication. Nature Communications. 11(1). 5178–5178. 61 indexed citations
10.
Fu, Yuhua, Jingya Xu, Zhenshuang Tang, et al.. (2020). A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model. Communications Biology. 3(1). 502–502. 46 indexed citations
11.
Wang, Haiyan, Qiaoxia Zhang, Lilin Yin, et al.. (2017). Transcriptomic basis of neutrophil ratio variation induced by poly I:C stimulation in porcine peripheral blood. Frontiers of Agricultural Science and Engineering. 4(3). 342–342. 2 indexed citations
12.
Yang, Songbai, Yue Pei, Xinyun Li, et al.. (2016). miR-124 attenuates Japanese encephalitis virus replication by targeting DNM2. Virology Journal. 13(1). 105–105. 16 indexed citations
13.
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
14.
Gu, Ting, Mengjin Zhu, Martine Schroyen, et al.. (2014). Endometrial gene expression profiling in pregnant Meishan and Yorkshire pigs on day 12 of gestation. BMC Genomics. 15(1). 156–156. 29 indexed citations
15.
Song, Weiling, Mengjin Zhu, Yaning Mao, & Shusheng Zhang. (2013). A sensitive quartz crystal microbalance assay of adenosine triphosphate via DNAzyme-activated and aptamer-based target-triggering circular amplification. Biosensors and Bioelectronics. 53. 288–294. 26 indexed citations
16.
Zhu, Mengjin, et al.. (2010). Model Optimization of Litter Size and Genetic Analyses of Model Parameters in Sows. Journal of Animal Science and Biotechnology. 1(1). 1–6. 1 indexed citations
17.
Xu, Xiaofei, Kun Li, Shuhong Zhao, et al.. (2008). Molecular characterization, expression and association analysis of the porcine CMYA4 gene with carcass traits. Journal of Animal Breeding and Genetics. 125(4). 234–239. 3 indexed citations
18.
Tang, Zhonglin, Yong Li, Ping Wan, et al.. (2007). LongSAGE analysis of skeletal muscle at three prenatal stages in Tongcheng and Landrace pigs. Genome biology. 8(6). R115–R115. 114 indexed citations
19.
Mo, Delin, Kui Li, Mengjin Zhu, et al.. (2007). Effect of mating combination and environmental factors on hatchability of chicken eggs in Tibet. Frontiers of Agriculture in China. 1(2). 214–219. 4 indexed citations
20.
Yang, Jine, et al.. (2005). Polymorphism detection of porcine PSMC3, PSMC6 and PSMD3 genes and their association with partial growth, carcass traits, meat quality and immune traits. Canadian Journal of Animal Science. 85(4). 475–480. 6 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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