Chenghong Peng

8.4k total citations
200 papers, 5.1k citations indexed

About

Chenghong Peng is a scholar working on Oncology, Surgery and Molecular Biology. According to data from OpenAlex, Chenghong Peng has authored 200 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Oncology, 102 papers in Surgery and 49 papers in Molecular Biology. Recurrent topics in Chenghong Peng's work include Pancreatic and Hepatic Oncology Research (97 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (28 papers) and Organ Transplantation Techniques and Outcomes (27 papers). Chenghong Peng is often cited by papers focused on Pancreatic and Hepatic Oncology Research (97 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (28 papers) and Organ Transplantation Techniques and Outcomes (27 papers). Chenghong Peng collaborates with scholars based in China, United States and United Kingdom. Chenghong Peng's co-authors include Baiyong Shen, Xiaxing Deng, Hao Chen, Qian Zhan, Minmin Shi, Xiaxing Deng, Dongfeng Cheng, Jiabin Jin, Junjie Xie and Xinjing Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Cancer Research.

In The Last Decade

Chenghong Peng

197 papers receiving 5.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenghong Peng China 41 2.1k 2.0k 1.8k 1.6k 1.1k 200 5.1k
Daniela Campani Italy 38 2.0k 0.9× 1.4k 0.7× 1.3k 0.7× 906 0.6× 660 0.6× 176 4.8k
Niccola Funel Italy 38 2.2k 1.0× 2.1k 1.1× 626 0.4× 1.8k 1.1× 603 0.5× 121 4.5k
Koichi Kawamoto Japan 35 1.4k 0.6× 2.3k 1.1× 914 0.5× 1.7k 1.1× 406 0.4× 164 4.2k
Yan‐Shen Shan Taiwan 33 1.7k 0.8× 1.4k 0.7× 1.2k 0.7× 758 0.5× 890 0.8× 216 4.2k
Jie Cai United States 41 1.0k 0.5× 2.0k 1.0× 2.1k 1.2× 819 0.5× 1.5k 1.4× 170 5.7k
Rishu Takimoto Japan 40 1.6k 0.8× 2.6k 1.3× 777 0.4× 564 0.4× 503 0.5× 155 5.8k
Yusuke Mizukami Japan 37 2.5k 1.2× 2.1k 1.1× 1.6k 0.9× 1.4k 0.9× 779 0.7× 209 5.4k
Ilona Kovalszky Hungary 40 932 0.4× 2.1k 1.1× 617 0.4× 1.0k 0.6× 607 0.5× 182 4.8k
Mengchao Wu China 37 1.1k 0.5× 1.9k 1.0× 872 0.5× 958 0.6× 406 0.4× 120 4.5k
Koji Miyanishi Japan 32 1.0k 0.5× 1.5k 0.7× 823 0.5× 449 0.3× 582 0.5× 151 4.0k

Countries citing papers authored by Chenghong Peng

Since Specialization
Citations

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

Fields of papers citing papers by Chenghong Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenghong Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Chenghong Peng. A scholar is included among the top collaborators of Chenghong 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 Chenghong Peng. Chenghong 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
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Wang, Xuelong, Youwei Zhu, Yizhi Cao, et al.. (2022). The CTCF/LncRNA‐PACERR complex recruits E1A binding protein p300 to induce pro‐tumour macrophages in pancreatic ductal adenocarcinoma via directly regulating PTGS2 expression. Clinical and Translational Medicine. 12(2). e654–e654. 32 indexed citations
4.
Jiang, Yu, et al.. (2022). The impact of Omicron pandemic and COVID‐19 vaccination on the pancreatic adenocarcinoma patients. SHILAP Revista de lepidopterología. 3(3-4). 161–168. 1 indexed citations
5.
Wang, Weishen, Dongfeng Cheng, Jiancheng Wang, et al.. (2021). Original study: The rescue staging for pancreatic ductal adenocarcinoma with inadequate examined lymph nodes. Pancreatology. 21(4). 724–730. 3 indexed citations
6.
Tong, Huili, Xiyong Liu, Li T, et al.. (2020). NR1D2 Accelerates Hepatocellular Carcinoma Progression by Driving the Epithelial-to-Mesenchymal Transition. SHILAP Revista de lepidopterología. 1 indexed citations
7.
Wen, Chenlei, Xiaxing Deng, Song Xue, et al.. (2020). Tumor copy number instability is a significant predictor for late recurrence after radical surgery of pancreatic ductal adenocarcinoma. Cancer Medicine. 9(20). 7626–7636. 2 indexed citations
8.
Xie, Junjie, Zhiwei Xu, Xiaxing Deng, et al.. (2020). The Necessity of Dissection of No. 14 Lymph Nodes to Patients With Pancreatic Ductal Adenocarcinoma Based on the Embryonic Development of the Head of the Pancreas. Frontiers in Oncology. 10. 1343–1343. 4 indexed citations
9.
Wang, Yue, Jingfeng Li, Yuanchi Weng, et al.. (2019). A new enhanced recovery after surgery pathway for left-sided pancreatic cancer patients after distal pancreatectomy. Translational Cancer Research. 8(7). 2613–2620. 3 indexed citations
10.
Chen, Shi, Jiang-Zhi Chen, Jiaqiang Zhang, et al.. (2019). Silencing of long noncoding RNA LINC00958 prevents tumor initiation of pancreatic cancer by acting as a sponge of microRNA-330-5p to down-regulate PAX8. Cancer Letters. 446. 49–61. 80 indexed citations
11.
Chen, Haoda, Weishen Wang, Xiayang Ying, et al.. (2019). Predictive factors for postoperative pancreatitis after pancreaticoduodenectomy: A single-center retrospective analysis of 1465 patients. Pancreatology. 20(2). 211–216. 32 indexed citations
12.
Zhou, Yiran, Wei Wang, Hao Chen, et al.. (2019). Should a standard lymphadenectomy include the No. 9 lymph nodes for body and tail pancreatic ductal adenocarcinoma?. Pancreatology. 19(3). 414–418. 8 indexed citations
13.
Li, Ke, Baiyong Shen, Xi Cheng, et al.. (2016). Phenotypic and Signaling Consequences of a Novel Aberrantly Spliced Transcript FGF Receptor-3 in Hepatocellular Carcinoma. Cancer Research. 76(14). 4205–4215. 18 indexed citations
14.
Shen, Baiyong, et al.. (2016). TMEM45B promotes proliferation, invasion and migration and inhibits apoptosis in pancreatic cancer cells. Molecular BioSystems. 12(6). 1860–1870. 12 indexed citations
15.
Li, Tao, Junjie Xie, Chuan Shen, et al.. (2015). Amplification of Long Noncoding RNA ZFAS1 Promotes Metastasis in Hepatocellular Carcinoma. Cancer Research. 75(15). 3181–3191. 260 indexed citations
16.
Xu, Hong, Jiamin Wang, Yi Zhu, et al.. (2014). Snail Recruits Ring1B to Mediate Transcriptional Repression and Cell Migration in Pancreatic Cancer Cells. Cancer Research. 74(16). 4353–4363. 55 indexed citations
17.
Zhan, Qian, Chenghong Peng, Xiaxing Deng, et al.. (2013). Robot-assisted distal pancreatectomy. Zhonghua putong waike zazhi. 28(5). 337–340. 1 indexed citations
18.
Yang, Weiping, Jiayu Wang, Andy Lin, et al.. (2012). The Different Induction Mechanisms of Growth Arrest DNA Damage Inducible Gene 45 β in Human Hepatoma Cell Lines. Chemotherapy. 58(2). 165–174. 7 indexed citations
19.
Zhang, Zhuo, Jiancheng Wang, Baiyong Shen, Chenghong Peng, & Minhua Zheng. (2011). The ABCC4 gene is a promising target for pancreatic cancer therapy. Gene. 491(2). 194–199. 37 indexed citations
20.
Peng, Chenghong. (2007). The effect of self-assembly multiplayer microcapsules loaded with doxorubicin on the cellular metabolism and apoptosis of the rabbit VX2 hepatic tumor model. 1 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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