Ji-Xia Ren

571 total citations
21 papers, 451 citations indexed

About

Ji-Xia Ren is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Ji-Xia Ren has authored 21 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Computational Theory and Mathematics and 5 papers in Organic Chemistry. Recurrent topics in Ji-Xia Ren's work include Computational Drug Discovery Methods (12 papers), Synthesis and biological activity (4 papers) and Click Chemistry and Applications (2 papers). Ji-Xia Ren is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Synthesis and biological activity (4 papers) and Click Chemistry and Applications (2 papers). Ji-Xia Ren collaborates with scholars based in China and United States. Ji-Xia Ren's co-authors include Shengyong Yang, Huanzhang Xie, Linli Li, Hui Zhang, Lan Ding, Qingqing Xie, Yuquan Wei, Jun Zou, Jinxiang Ma and Wei-Bao Kong and has published in prestigious journals such as Molecules, Food and Chemical Toxicology and European Journal of Medicinal Chemistry.

In The Last Decade

Ji-Xia Ren

20 papers receiving 438 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ji-Xia Ren China 10 235 192 136 61 35 21 451
Daniel J. Mason United Kingdom 11 313 1.3× 152 0.8× 140 1.0× 51 0.8× 18 0.5× 14 513
Abdeen Tunde Ogunlana Nigeria 9 212 0.9× 169 0.9× 103 0.8× 49 0.8× 28 0.8× 19 413
Ugo Perricone Italy 15 316 1.3× 188 1.0× 134 1.0× 38 0.6× 53 1.5× 40 545
Abdul-Quddus Kehinde Oyedele Nigeria 9 200 0.9× 168 0.9× 101 0.7× 42 0.7× 26 0.7× 14 391
Wei-Zhu Zhong United States 11 384 1.6× 154 0.8× 94 0.7× 72 1.2× 76 2.2× 17 664
Sree Kanth Sivan India 14 221 0.9× 165 0.9× 240 1.8× 106 1.7× 53 1.5× 38 495
Biswajit Kundu India 10 224 1.0× 96 0.5× 151 1.1× 60 1.0× 31 0.9× 17 411
Sorin Avram Romania 13 320 1.4× 289 1.5× 116 0.9× 44 0.7× 24 0.7× 43 555
Sayaka Mizutani Japan 13 504 2.1× 272 1.4× 86 0.6× 80 1.3× 35 1.0× 26 769
Selvaraman Nagamani India 13 195 0.8× 177 0.9× 63 0.5× 35 0.6× 34 1.0× 44 380

Countries citing papers authored by Ji-Xia Ren

Since Specialization
Citations

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

Fields of papers citing papers by Ji-Xia Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ji-Xia Ren. 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 Ji-Xia Ren. The network helps show where Ji-Xia Ren may publish in the future.

Co-authorship network of co-authors of Ji-Xia Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Ji-Xia Ren. A scholar is included among the top collaborators of Ji-Xia Ren 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 Ji-Xia Ren. Ji-Xia Ren 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.
Mao, Jun, et al.. (2024). Identification of Salvianolic acid A as a potent inhibitor of PDEs to enhance proliferation of human neural stem cells. Journal of Molecular Structure. 1324. 140905–140905.
2.
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4.
Zhang, Hui, Jinxiang Ma, Chun‐Tao Liu, Ji-Xia Ren, & Lan Ding. (2018). Development and evaluation of in silico prediction model for drug-induced respiratory toxicity by using naïve Bayes classifier method. Food and Chemical Toxicology. 121. 593–603. 28 indexed citations
5.
Zhang, Hui, Ji-Xia Ren, Jinxiang Ma, & Lan Ding. (2018). Development of an in silico prediction model for chemical-induced urinary tract toxicity by using naïve Bayes classifier. Molecular Diversity. 23(2). 381–392. 39 indexed citations
6.
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Zhang, Hui, Ji-Xia Ren, Junyu Liang, et al.. (2017). Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method. Reproductive Toxicology. 71. 8–15. 26 indexed citations
8.
Zhang, Hui, Peng Yu, Ji-Xia Ren, et al.. (2017). Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method. Food and Chemical Toxicology. 110. 122–129. 30 indexed citations
9.
Zhao, Jingfeng, Ji-Xia Ren, Nan Wang, et al.. (2017). Crystal structure of the second fibronectin type III (FN3) domain from human collagen α1 type XX. Acta Crystallographica Section F Structural Biology Communications. 73(12). 695–700. 6 indexed citations
10.
Ren, Ji-Xia, Ruitao Zhang, Hui Zhang, et al.. (2016). Identification of novel VP35 inhibitors: Virtual screening driven new scaffolds. Biomedicine & Pharmacotherapy. 84. 199–207. 10 indexed citations
11.
Gao, Nana, Ji-Xia Ren, Yue Zhou, et al.. (2016). Identification of novel potent human testis-specific and bromodomain-containing protein (BRDT) inhibitors using crystal structure-based virtual screening. International Journal of Molecular Medicine. 38(1). 39–44. 5 indexed citations
12.
Ren, Ji-Xia, Nana Gao, Xuesong Cao, Quan Hu, & Yong Xie. (2016). Homology modeling and virtual screening for inhibitors of lipid kinase PI(4)K from Plasmodium. Biomedicine & Pharmacotherapy. 83. 798–808. 9 indexed citations
13.
Ren, Ji-Xia, et al.. (2015). Virtual screening for the identification of novel inhibitors of Mycobacterium tuberculosis cell wall synthesis: Inhibitors targeting RmlB and RmlC. Computers in Biology and Medicine. 58. 110–117. 9 indexed citations
14.
Wang, Xiaoying, et al.. (2014). Expression, purification and preliminary crystallographic studies of the C-terminal SH3 domain of human Tks4. Acta Crystallographica Section F Structural Biology Communications. 70(3). 343–346. 1 indexed citations
15.
Xie, Huanzhang, et al.. (2011). Pharmacophore Modeling and Hybrid Virtual Screening for the Discovery of Novel IκB Kinase 2 (IKK2) Inhibitors. Journal of Biomolecular Structure and Dynamics. 29(1). 165–179. 6 indexed citations
16.
Ren, Ji-Xia, Linli Li, Renlin Zheng, et al.. (2011). Discovery of Novel Pim-1 Kinase Inhibitors by a Hierarchical Multistage Virtual Screening Approach Based on SVM Model, Pharmacophore, and Molecular Docking. Journal of Chemical Information and Modeling. 51(6). 1364–1375. 59 indexed citations
17.
Xie, Huanzhang, Linli Li, Ji-Xia Ren, et al.. (2009). Pharmacophore modeling study based on known Spleen tyrosine kinase inhibitors together with virtual screening for identifying novel inhibitors. Bioorganic & Medicinal Chemistry Letters. 19(7). 1944–1949. 34 indexed citations
18.
Ren, Ji-Xia, et al.. (2009). Pharmacophore modeling and virtual screening for the discovery of new transforming growth factor-β type I receptor (ALK5) inhibitors. European Journal of Medicinal Chemistry. 44(11). 4259–4265. 15 indexed citations
19.
Zou, Jun, et al.. (2008). Towards more accurate pharmacophore modeling: Multicomplex-based comprehensive pharmacophore map and most-frequent-feature pharmacophore model of CDK2. Journal of Molecular Graphics and Modelling. 27(4). 430–438. 58 indexed citations
20.
Xie, Qingqing, Huanzhang Xie, Ji-Xia Ren, Linli Li, & Shengyong Yang. (2008). Pharmacophore modeling studies of type I and type II kinase inhibitors of Tie2. Journal of Molecular Graphics and Modelling. 27(6). 751–758. 99 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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