Jiesi Luo

1.3k total citations · 1 hit paper
55 papers, 993 citations indexed

About

Jiesi Luo is a scholar working on Molecular Biology, Computational Theory and Mathematics and Hematology. According to data from OpenAlex, Jiesi Luo has authored 55 papers receiving a total of 993 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 6 papers in Hematology. Recurrent topics in Jiesi Luo's work include Machine Learning in Bioinformatics (22 papers), RNA and protein synthesis mechanisms (13 papers) and Genomics and Phylogenetic Studies (9 papers). Jiesi Luo is often cited by papers focused on Machine Learning in Bioinformatics (22 papers), RNA and protein synthesis mechanisms (13 papers) and Genomics and Phylogenetic Studies (9 papers). Jiesi Luo collaborates with scholars based in China, United States and Hong Kong. Jiesi Luo's co-authors include Menglong Li, Xue Li, Yanzhi Guo, Lezheng Yu, Yizhou Li, Runyu Jing, Fengjuan Liu, Jianming Wu, Wei Chen and Xiaobo Zhou and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Jiesi Luo

52 papers receiving 984 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Macrophage cell membrane-based nanoparticles: a new promising biomimetic platform for targeted delivery and treatment

2022 164 citations Yuesong Wu, Shengli Wan et al. Journal of Nanobiotechnology profile →

Peers

Jiesi Luo

CTM

IMMUN

Christine Wurth Switzerland

Aurélie Bornot France

Gisela Gabernet Switzerland

Grigory Khimulya Russia

Xinglu Zhou China

Wanxu Huang China

Eva Muñoz Spain

Mahendran Botlagunta India

Anuradha Roy United States

Christine Wurth Switzerland

Jiesi Luo

537 ×0.7

59 ×0.5

CTM

61 ×0.6

69 ×0.9

IMMUN

47 ×0.7

Citations per year, relative to Jiesi Luo Jiesi Luo (= 1×) peers Christine Wurth

Countries citing papers authored by Jiesi Luo

Since Specialization

Citations

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

Fields of papers citing papers by Jiesi Luo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiesi Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Jiesi Luo. A scholar is included among the top collaborators of Jiesi Luo 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 Jiesi Luo. Jiesi Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yu, Lezheng, et al.. (2025). Multimodal deep learning for allergenic proteins prediction. BMC Biology. 23(1). 232–232.

Zhang, Yonglin, Lezheng Yu, Li C. Xue, et al.. (2025). Optimizing lipocalin sequence classification with ensemble deep learning models. PLoS ONE. 20(4). e0319329–e0319329. 1 indexed citations

Wang, Long, Qianhui Zhang, Ling Zhou, et al.. (2024). Interleukins in Platelet Biology: Unraveling the Complex Regulatory Network. Pharmaceuticals. 17(1). 109–109. 4 indexed citations

Tang, Xiaoqin, Rui Liao, Xiaogang Zhou, et al.. (2024). Activating SRC/MAPK signaling via 5-HT1A receptor contributes to the effect of vilazodone on improving thrombocytopenia. eLife. 13. 3 indexed citations

Yang, Shuo, Jiesi Luo, Kui Cheng, et al.. (2024). Oxymatrine, a novel TLR2 agonist, promotes megakaryopoiesis and thrombopoiesis through the STING/NF-κB pathway. Journal of Pharmaceutical Analysis. 15(1). 101054–101054.

Tang, Xiaoqin, Rui Liao, Ling Zhou, et al.. (2024). Genistin: A Novel Estrogen Analogue Targeting ERβ to Alleviate Thrombocytopenia. International Journal of Biological Sciences. 20(6). 2236–2260. 9 indexed citations

Luo, Jiesi, et al.. (2024). Development and validation of a predictive model for end-stage renal disease in systemic lupus erythematosus patients. Rheumatology International. 44(10). 1941–1958. 1 indexed citations

Li, Xue, et al.. (2024). Machine learning to guide the use of plasma technology for antibiotic degradation. Journal of Hazardous Materials. 480. 135787–135787. 3 indexed citations

Yu, Lezheng, Yonglin Zhang, Xue Li, et al.. (2023). EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework. Computational and Structural Biotechnology Journal. 21. 4836–4848. 4 indexed citations

10.

Luo, Jiesi, et al.. (2023). Sequence-based malware detection using a single-bidirectional graph embedding and multi-task learning framework. Journal of Computer Security. 32(2). 141–163. 1 indexed citations

11.

Tang, Xiaoqin, Shuo Yang, Long Wang, et al.. (2023). Toll-like Receptors and Thrombopoiesis. International Journal of Molecular Sciences. 24(2). 1010–1010. 22 indexed citations

12.

Zhang, Ting, Nan Jiang, Yuesong Wu, et al.. (2023). The combination of machine learning and transcriptomics reveals a novel megakaryopoiesis inducer, MO-A, that promotes thrombopoiesis by activating FGF1/FGFR1/PI3K/Akt/NF-κB signaling. European Journal of Pharmacology. 944. 175604–175604. 6 indexed citations

13.

Wang, Long, Sha Liu, Jiesi Luo, et al.. (2022). Targeting a thrombopoietin-independent strategy in the discovery of a novel inducer of megakaryocytopoiesis, DMAG, for the treatment of thrombocytopenia. Haematologica. 108(5). 1394–1411. 9 indexed citations

14.

Wu, Yuesong, Shengli Wan, Shuo Yang, et al.. (2022). Macrophage cell membrane-based nanoparticles: a new promising biomimetic platform for targeted delivery and treatment. Journal of Nanobiotechnology. 20(1). 542–542. 164 indexed citations breakdown →

15.

Zhang, Yonglin, et al.. (2021). Evaluation of deep learning approaches for modeling transcription factor sequence specificity. Genomics. 113(6). 3774–3781. 5 indexed citations

16.

Li, Zhong, et al.. (2020). ACNNT3: Attention-CNN Framework for Prediction of Sequence-Based Bacterial Type III Secreted Effectors. Computational and Mathematical Methods in Medicine. 2020. 1–7. 10 indexed citations

17.

Xu, Yungang, Yongcui Wang, Jiesi Luo, Weiling Zhao, & Xiaobo Zhou. (2017). Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision. Nucleic Acids Research. 45(21). 12100–12112. 56 indexed citations

18.

Luo, Jiesi, Liang Liu, Suresh Venkateswaran, Qianqian Song, & Xiaobo Zhou. (2017). RPI-Bind: a structure-based method for accurate identification of RNA-protein binding sites. Scientific Reports. 7(1). 614–614. 22 indexed citations

19.

Guo, Yanzhi, Yuelong Wang, Jiesi Luo, et al.. (2015). Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder. Computational Biology and Chemistry. 56. 41–48. 12 indexed citations

20.

Luo, Jiesi, Zhongyu Liu, Yanzhi Guo, & Menglong Li. (2015). A structural dissection of large protein-protein crystal packing contacts. Scientific Reports. 5(1). 14214–14214. 35 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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