Mengnan He

906 total citations
20 papers, 372 citations indexed

About

Mengnan He is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Mengnan He has authored 20 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Cancer Research. Recurrent topics in Mengnan He's work include Genomics and Chromatin Dynamics (7 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and RNA modifications and cancer (4 papers). Mengnan He is often cited by papers focused on Genomics and Chromatin Dynamics (7 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and RNA modifications and cancer (4 papers). Mengnan He collaborates with scholars based in China and United Kingdom. Mengnan He's co-authors include Mingzhou Li, Long Jin, Diyan Li, George F. Gao, Shuguang Tan, Jianxun Qi, Jinghua Yan, Yi Shi, Yan Chai and Zhou Tong and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Mengnan He

19 papers receiving 365 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mengnan He China 10 217 105 94 63 61 20 372
Xicai Wang China 13 238 1.1× 82 0.8× 67 0.7× 142 2.3× 28 0.5× 31 397
Taro Hihara Japan 9 350 1.6× 30 0.3× 40 0.4× 42 0.7× 29 0.5× 14 482
Véronique Joliot France 13 583 2.7× 52 0.5× 94 1.0× 30 0.5× 77 1.3× 19 697
Jennifer Clark United States 9 212 1.0× 120 1.1× 26 0.3× 23 0.4× 22 0.4× 16 347
Olga P. Ryabinina United States 9 242 1.1× 47 0.4× 103 1.1× 35 0.6× 23 0.4× 12 396
Luca Triboli Italy 5 341 1.6× 62 0.6× 29 0.3× 22 0.3× 29 0.5× 6 430
Tomoaki Sobajima Japan 11 301 1.4× 31 0.3× 101 1.1× 14 0.2× 65 1.1× 21 455
Yael Nevo‐Caspi Israel 13 361 1.7× 43 0.4× 41 0.4× 95 1.5× 20 0.3× 20 463
Florence Maurier France 7 371 1.7× 40 0.4× 40 0.4× 39 0.6× 32 0.5× 11 458
Henry Pratt United States 12 419 1.9× 39 0.4× 55 0.6× 74 1.2× 54 0.9× 24 532

Countries citing papers authored by Mengnan He

Since Specialization
Citations

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

Fields of papers citing papers by Mengnan He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mengnan He

This figure shows the co-authorship network connecting the top 25 collaborators of Mengnan He. A scholar is included among the top collaborators of Mengnan He 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 Mengnan He. Mengnan He 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.
Liu, Ailian, Tianyu Wang, Yanyan Zhang, et al.. (2025). A model for the adaptation of Euryale ferox leaves to aquatic environments through EfCGT1‐controlled flavonoid C‐glycoside‐specific accumulation in epidermis cells. Plant Biotechnology Journal. 23(8). 3333–3348. 3 indexed citations
2.
Zhang, Han, Wenfeng Lu, Lan Qiu, et al.. (2024). Circ_0025373 inhibits carbon black nanoparticles-induced malignant transformation of human bronchial epithelial cells by affecting DNA damage through binding to MSH2. Environment International. 191. 109001–109001. 2 indexed citations
3.
Wang, Tao, Wei Zhu, Ziyu Li, et al.. (2024). 3D genomic alterations during development of skeletal muscle in chicken. Journal of Integrative Agriculture. 25(1). 207–226. 2 indexed citations
4.
Gao, Guangliang, Rui Liu, Silu Hu, et al.. (2024). Exploring the dynamic three-dimensional chromatin architecture and transcriptional landscape in goose liver tissues underlying metabolic adaptations induced by a high-fat diet. Journal of Animal Science and Biotechnology. 15(1). 60–60. 1 indexed citations
5.
Li, Jing, Diyan Li, Mengnan He, et al.. (2024). Building Haplotype‐Resolved 3D Genome Maps of Chicken Skeletal Muscle. Advanced Science. 11(24). e2305706–e2305706. 7 indexed citations
6.
Liu, Pengliang, Diyan Li, Jiaman Zhang, et al.. (2023). Comparative three-dimensional genome architectures of adipose tissues provide insight into human-specific regulation of metabolic homeostasis. Journal of Biological Chemistry. 299(6). 104757–104757. 2 indexed citations
7.
Liu, Pengliang, Diyan Li, Jiaman Zhang, et al.. (2023). Transcriptomic and lipidomic profiling of subcutaneous and visceral adipose tissues in 15 vertebrates. Scientific Data. 10(1). 5 indexed citations
8.
Zhang, Jiaman, Pengliang Liu, Mengnan He, et al.. (2022). Reorganization of 3D genome architecture across wild boar and Bama pig adipose tissues. Journal of Animal Science and Biotechnology. 13(1). 32–32. 9 indexed citations
9.
Li, Diyan, Chunyou Ning, Jiaman Zhang, et al.. (2022). Dynamic transcriptome and chromatin architecture in granulosa cells during chicken folliculogenesis. Nature Communications. 13(1). 131–131. 57 indexed citations
10.
Li, Diyan, Mengnan He, Qianzi Tang, et al.. (2022). Comparative 3D genome architecture in vertebrates. BMC Biology. 20(1). 99–99. 33 indexed citations
11.
Su, Yuan, Shilin Tian, Diyan Li, et al.. (2021). Association of female reproductive tract microbiota with egg production in layer chickens. GigaScience. 10(9). 22 indexed citations
12.
13.
Lin, Yu, Qianzi Tang, Yán Li, et al.. (2019). Genomic analyses provide insights into breed-of-origin effects from purebreds on three-way crossbred pigs. PeerJ. 7. e8009–e8009. 5 indexed citations
14.
He, Mengnan, Yán Li, Qianzi Tang, et al.. (2018). Genome-Wide Chromatin Structure Changes During Adipogenesis and Myogenesis. International Journal of Biological Sciences. 14(11). 1571–1585. 21 indexed citations
15.
Li, Yan, Shuguang Tan, Chang Zhang, et al.. (2018). Limited Cross-Linking of 4-1BB by 4-1BB Ligand and the Agonist Monoclonal Antibody Utomilumab. Cell Reports. 25(4). 909–920.e4. 34 indexed citations
16.
He, Shen, Hong Wang, Rui Liu, et al.. (2017). mRNA N6-methyladenosine methylation of postnatal liver development in pig. PLoS ONE. 12(3). e0173421–e0173421. 54 indexed citations
17.
He, Mengnan, Yan Chai, Jianxun Qi, et al.. (2017). Remarkably similar CTLA-4 binding properties of therapeutic ipilimumab and tremelimumab antibodies. Oncotarget. 8(40). 67129–67139. 69 indexed citations
18.
Tan, Shuguang, Danqing Chen, Kefang Liu, et al.. (2016). Crystal clear: visualizing the intervention mechanism of the PD-1/PD-L1 interaction by two cancer therapeutic monoclonal antibodies. Protein & Cell. 7(12). 866–877. 31 indexed citations
19.
Xie, Yue, et al.. (2015). Quantitative changes in mitochondrial DNA copy number in various tissues of pigs during growth. Genetics and Molecular Research. 14(1). 1662–1670. 12 indexed citations
20.
Jin, Long, et al.. (2014). Development-related expression patterns of protein-coding and miRNA genes involved in porcine muscle growth. Genetics and Molecular Research. 13(4). 9921–9930. 3 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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