Di Peng

9.7k total citations
79 papers, 1.9k citations indexed

About

Di Peng is a scholar working on Molecular Biology, Immunology and Aquatic Science. According to data from OpenAlex, Di Peng has authored 79 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 22 papers in Immunology and 21 papers in Aquatic Science. Recurrent topics in Di Peng's work include Aquaculture Nutrition and Growth (21 papers), Aquaculture disease management and microbiota (13 papers) and Ubiquitin and proteasome pathways (9 papers). Di Peng is often cited by papers focused on Aquaculture Nutrition and Growth (21 papers), Aquaculture disease management and microbiota (13 papers) and Ubiquitin and proteasome pathways (9 papers). Di Peng collaborates with scholars based in China, United States and Canada. Di Peng's co-authors include Yu Xue, Shaofeng Lin, Chenwei Wang, Wankun Deng, Haodong Xu, Jiaqi Zhou, Wanshan Ning, Ying Shi, Ying Zhang and Xiaodan Tan and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Di Peng

71 papers receiving 1.9k citations

Peers

Di Peng
Aurélien Naldi France
Kosuke Hashimoto Japan
Xiaodong Zhao China
Qiao Liu China
Zhijian Li China
Feng Xiao China
Dongmin Jung South Korea
Rainer König Germany
Dan Zhao China
Aurélien Naldi France
Di Peng
Citations per year, relative to Di Peng Di Peng (= 1×) peers Aurélien Naldi

Countries citing papers authored by Di Peng

Since Specialization
Citations

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

Fields of papers citing papers by Di Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Di Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Di Peng. A scholar is included among the top collaborators of Di Peng 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 Di Peng. Di Peng 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.
Peng, Di, Yongjun Tan, Dapeng Zhang, et al.. (2025). Hormonal dynamics reveal a stimulatory role for secretoneurin in zebrafish ovulation. PNAS Nexus. 4(4). pgaf097–pgaf097. 2 indexed citations
2.
3.
Gou, Yujie, et al.. (2025). EPSD 2.0: An Updated Database of Protein Phosphorylation Sites Across Eukaryotic Species. Genomics Proteomics & Bioinformatics. 23(3).
4.
Zhang, Xinyao, Lixue Dong, Qingyong Li, et al.. (2025). Mechanisms of hepatic dysfunction in Nile tilapia (Oreochromis niloticus) fed a high-fava bean (Vicia faba L.) diet. Animal nutrition. 22. 61–71.
5.
Cheng, Han, Shanshan Fu, Miaomiao Chen, et al.. (2024). GPSD: a hybrid learning framework for the prediction of phosphatase-specific dephosphorylation sites. Briefings in Bioinformatics. 26(1).
6.
Huang, Xinhe, Dan Liu, Yujie Gou, et al.. (2024). PTMD 2.0: an updated database of disease-associated post-translational modifications. Nucleic Acids Research. 53(D1). D554–D563. 7 indexed citations
7.
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Gou, Yujie, Dan Liu, Miaomiao Chen, et al.. (2024). GPS-SUMO 2.0: an updated online service for the prediction of SUMOylation sites and SUMO-interacting motifs. Nucleic Acids Research. 52(W1). W238–W247. 13 indexed citations
9.
Tang, Dachao, Yujie Gou, Miaomiao Chen, et al.. (2024). GPS-pPLM: A Language Model for Prediction of Prokaryotic Phosphorylation Sites. Cells. 13(22). 1854–1854. 1 indexed citations
10.
Peng, Di, et al.. (2023). Simultaneous extraction and detection of peptides, steroids, and proteins in small tissue samples. Frontiers in Endocrinology. 14. 1266985–1266985. 6 indexed citations
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Peng, Di, et al.. (2023). Dietary zinc levels affect growth, appetite, and lipid metabolism of Chinese perch (Siniperca chuatsi). Fish Physiology and Biochemistry. 49(5). 1017–1030. 7 indexed citations
13.
Xu, Jiabao, Di Peng, Xiaogang Xu, et al.. (2022). High-Speed Diagnosis of Bacterial Pathogens at the Single Cell Level by Raman Microspectroscopy with Machine Learning Filters and Denoising Autoencoders. ACS Chemical Biology. 17(2). 376–385. 39 indexed citations
14.
Tang, Dachao, Shaofeng Lin, Xiaodan Tan, et al.. (2022). iPCD: A Comprehensive Data Resource of Regulatory Proteins in Programmed Cell Death. Cells. 11(13). 2018–2018. 3 indexed citations
15.
Peng, Di, Chen Ruan, Shanshan Fu, et al.. (2021). Atg9-centered multi-omics integration reveals new autophagy regulators inSaccharomyces cerevisiae. Autophagy. 17(12). 4453–4476. 7 indexed citations
16.
Xu, Xiaoyan, Yaqin Sun, Xufeng Cen, et al.. (2021). Metformin activates chaperone-mediated autophagy and improves disease pathologies in an Alzheimer disease mouse model. Protein & Cell. 12(10). 769–787. 121 indexed citations
17.
Ruan, Chen, Chenwei Wang, Xuanqing Gong, et al.. (2020). An integrative multi-omics approach uncovers the regulatory role of CDK7 and CDK4 in autophagy activation induced by silica nanoparticles. Autophagy. 17(6). 1426–1447. 40 indexed citations
18.
Guo, Yaping, Wanshan Ning, Peiran Jiang, et al.. (2020). GPS-PBS: A Deep Learning Framework to Predict Phosphorylation Sites that Specifically Interact with Phosphoprotein-Binding Domains. Cells. 9(5). 1266–1266. 14 indexed citations
19.
Zhang, Ying, Yubin Xie, Wenzhong Liu, et al.. (2019). DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae. Autophagy. 16(4). 626–640. 17 indexed citations
20.
Guo, Hui, Di Peng, Xige Yang, et al.. (2014). A Higher Frequency of Circulating IL-22+CD4+ T Cells in Chinese Patients with Newly Diagnosed Hashimoto’s Thyroiditis. PLoS ONE. 9(1). e84545–e84545. 17 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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