Xiaocong Pang

2.1k total citations · 1 hit paper
36 papers, 1.3k citations indexed

About

Xiaocong Pang is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Xiaocong Pang has authored 36 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 14 papers in Molecular Biology and 8 papers in Pharmacology. Recurrent topics in Xiaocong Pang's work include Computational Drug Discovery Methods (17 papers), Cholinesterase and Neurodegenerative Diseases (7 papers) and Influenza Virus Research Studies (4 papers). Xiaocong Pang is often cited by papers focused on Computational Drug Discovery Methods (17 papers), Cholinesterase and Neurodegenerative Diseases (7 papers) and Influenza Virus Research Studies (4 papers). Xiaocong Pang collaborates with scholars based in China, United States and United Kingdom. Xiaocong Pang's co-authors include Yimin Cui, Qian Xiang, Hanxu Zhang, Guanhua Du, Zhiwei Qiu, Yanlun Gu, Zhiyan Liu, Nan Zhao, Ran Xie and He Xu and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Journal of the American Society of Nephrology.

In The Last Decade

Xiaocong Pang

35 papers receiving 1.3k citations

Hit Papers

Targeting integrin pathwa... 2023 2026 2024 2023 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
Xiaocong Pang China 18 525 276 160 146 134 36 1.3k
Ahmed Elkamhawy South Korea 24 601 1.1× 131 0.5× 184 1.1× 244 1.7× 58 0.4× 67 1.4k
Xin Lü China 22 397 0.8× 167 0.6× 248 1.6× 103 0.7× 125 0.9× 63 1.2k
Scott J. Weir United States 29 928 1.8× 81 0.3× 191 1.2× 560 3.8× 187 1.4× 106 2.2k
Tomohiro Kawamoto Japan 24 1.1k 2.1× 161 0.6× 105 0.7× 301 2.1× 243 1.8× 61 1.9k
Mi Yang United States 18 883 1.7× 72 0.3× 56 0.3× 235 1.6× 138 1.0× 31 1.4k
Francesca Cirillo Italy 29 895 1.7× 85 0.3× 78 0.5× 513 3.5× 207 1.5× 68 2.2k
Anjali Pandey United States 24 832 1.6× 92 0.3× 129 0.8× 267 1.8× 310 2.3× 82 2.2k
Nikolay Borisov Russia 18 947 1.8× 184 0.7× 71 0.4× 147 1.0× 61 0.5× 37 1.5k
Chia‐Ron Yang Taiwan 25 1.0k 2.0× 63 0.2× 219 1.4× 316 2.2× 263 2.0× 56 1.7k
Cristina Nogueira United States 20 949 1.8× 183 0.7× 271 1.7× 376 2.6× 309 2.3× 24 1.8k

Countries citing papers authored by Xiaocong Pang

Since Specialization
Citations

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

Fields of papers citing papers by Xiaocong Pang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaocong Pang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaocong Pang. A scholar is included among the top collaborators of Xiaocong Pang 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 Xiaocong Pang. Xiaocong Pang 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
2.
Liu, Zhenming, et al.. (2024). The applications and advances of artificial intelligence in drug regulation: A global perspective. Acta Pharmaceutica Sinica B. 15(1). 1–14. 7 indexed citations
3.
Liu, Zhiyan, Longtu Li, Hanxu Zhang, et al.. (2023). Platelet factor 4(PF4) and its multiple roles in diseases. Blood Reviews. 64. 101155–101155. 22 indexed citations
4.
Li, Wenhui, Mingli Gong, Yanlun Gu, et al.. (2023). Risk of venous thromboembolism with janus kinase inhibitors in inflammatory immune diseases: a systematic review and meta-analysis. Frontiers in Pharmacology. 14. 1189389–1189389. 23 indexed citations
5.
Pang, Xiaocong, He Xu, Zhiwei Qiu, et al.. (2023). Targeting integrin pathways: mechanisms and advances in therapy. Signal Transduction and Targeted Therapy. 8(1). 1–1. 610 indexed citations breakdown →
6.
Liu, Gang, et al.. (2021). Correlation analysis of soil microorganisms and saponins from different origins of Panax notoginseng. Allelopathy Journal. 53(2). 187–208. 1 indexed citations
8.
Zhang, Baoyue, Xiaocong Pang, Miao Chen, et al.. (2020). Network Pharmacology-Based Analysis of Xiao-Xu-Ming Decoction on the Treatment of Alzheimer’s Disease. Frontiers in Pharmacology. 11. 595254–595254. 23 indexed citations
9.
Song, Junke, Wen Zhang, Xiaocong Pang, et al.. (2018). Investigation of common chemical components and inhibitory effect on GES-type β-lactamase (GES22) in methanolic extracts of Algerian seaweeds. Microbial Pathogenesis. 126. 56–62. 11 indexed citations
10.
Pang, Xiaocong, Weiqi Fu, Jinhua Wang, et al.. (2018). Identification of Estrogen Receptor α Antagonists from Natural Products via In Vitro and In Silico Approaches. Oxidative Medicine and Cellular Longevity. 2018(1). 6040149–6040149. 70 indexed citations
11.
Li, Chao, Lvjie Xu, Wenwen Lian, et al.. (2018). Anti-influenza effect and action mechanisms of the chemical constituent gallocatechin-7-gallate from Pithecellobium clypearia Benth. Acta Pharmacologica Sinica. 39(12). 1913–1922. 14 indexed citations
12.
Pang, Xiaocong, De Kang, Jiansong Fang, et al.. (2018). Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease. Chinese Journal of Natural Medicines. 16(1). 53–62. 48 indexed citations
13.
14.
Fang, Jiansong, Ling Wang, Wenwen Lian, et al.. (2017). AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer’s disease. PLoS ONE. 12(5). e0178347–e0178347. 17 indexed citations
15.
Wu, Ping, Yu Yan, Linlin Ma, et al.. (2016). Effects of the Nrf2 Protein Modulator Salvianolic Acid A Alone or Combined with Metformin on Diabetes-associated Macrovascular and Renal Injury. Journal of Biological Chemistry. 291(42). 22288–22301. 44 indexed citations
16.
Yang, Ranyao, Dongmei Wang, Xiaocong Pang, et al.. (2015). DL0410 can reverse cognitive impairment, synaptic loss and reduce plaque load in APP/PS1 transgenic mice. Pharmacology Biochemistry and Behavior. 139(Pt A). 15–26. 25 indexed citations
17.
Li, Chao, Xiaowei Song, Junke Song, et al.. (2015). Pharmacokinetic study of gallocatechin-7-gallate from Pithecellobium clypearia Benth. in rats. Acta Pharmaceutica Sinica B. 6(1). 64–70. 9 indexed citations
18.
Lian, Wenwen, Jiansong Fang, Chao Li, et al.. (2015). Discovery of Influenza A virus neuraminidase inhibitors using support vector machine and Naïve Bayesian models. Molecular Diversity. 20(2). 439–451. 21 indexed citations
19.
Fang, Jiansong, Ranyao Yang, Shengqian Yang, et al.. (2014). Consensus models for CDK5 inhibitors in silico and their application to inhibitor discovery. Molecular Diversity. 19(1). 149–162. 25 indexed citations
20.
Fang, Jiansong, Yongjie Li, Rui Liu, et al.. (2014). Discovery of Multitarget-Directed Ligands against Alzheimer’s Disease through Systematic Prediction of Chemical–Protein Interactions. Journal of Chemical Information and Modeling. 55(1). 149–164. 85 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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