Feng Ren

3.0k total citations · 2 hit papers
86 papers, 1.5k citations indexed

About

Feng Ren is a scholar working on Molecular Biology, Organic Chemistry and Materials Chemistry. According to data from OpenAlex, Feng Ren has authored 86 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 21 papers in Organic Chemistry and 15 papers in Materials Chemistry. Recurrent topics in Feng Ren's work include Computational Drug Discovery Methods (11 papers), Cancer therapeutics and mechanisms (6 papers) and Catalysis and Oxidation Reactions (5 papers). Feng Ren is often cited by papers focused on Computational Drug Discovery Methods (11 papers), Cancer therapeutics and mechanisms (6 papers) and Catalysis and Oxidation Reactions (5 papers). Feng Ren collaborates with scholars based in China, United States and Hong Kong. Feng Ren's co-authors include Alex Zhavoronkov, Alex Aliper, Shingo Ishida, Li Wang, Ji‐Jun Zou, Xiangwen Zhang, Petrina Kamya, Daniil Polykovskiy, Xichen Lin and Ting Yang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and American Journal of Respiratory and Critical Care Medicine.

In The Last Decade

Feng Ren

80 papers receiving 1.4k 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.

Chemistry42: An AI-Driven Platform for Molecular Design and Optimization

2023 109 citations Yan A. Ivanenkov, Daniil Polykovskiy et al. Journal of Chemical Information and Modeling profile →
PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery

2024 65 citations Petrina Kamya, Ivan V. Ozerov et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Feng Ren China	23	419	397	366	220	147	86	1.5k
Hakan Günaydin United States	22	522 1.2×	233 0.6×	265 0.7×	79 0.4×	57 0.4×	32	1.3k
Tohru Nakamura Japan	21	228 0.5×	502 1.3×	313 0.9×	36 0.2×	119 0.8×	132	1.8k
Michael Wagner Germany	30	936 2.2×	235 0.6×	757 2.1×	120 0.5×	339 2.3×	117	2.6k
Yifeng Liu China	19	468 1.1×	690 1.7×	168 0.5×	60 0.3×	177 1.2×	77	1.5k
Jiyong Park South Korea	23	733 1.7×	574 1.4×	432 1.2×	102 0.5×	196 1.3×	74	2.1k
Jingfei Chen China	24	458 1.1×	339 0.9×	263 0.7×	29 0.1×	110 0.7×	105	1.5k
Christopher N. Johnson United Kingdom	21	865 2.1×	185 0.5×	637 1.7×	282 1.3×	53 0.4×	41	1.7k
Jiabo Li China	19	487 1.2×	77 0.2×	203 0.6×	58 0.3×	56 0.4×	60	1.4k
Surya K. De United States	33	1.3k 3.1×	209 0.5×	2.0k 5.6×	130 0.6×	236 1.6×	121	3.2k
Nian Wu United States	30	1.0k 2.4×	584 1.5×	125 0.3×	181 0.8×	33 0.2×	70	2.8k

Countries citing papers authored by Feng Ren

Since Specialization

Citations

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

Fields of papers citing papers by Feng Ren

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Ren

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Yazhou, Xiaomin Wang, Tingting Liu, et al.. (2025). Discovery of a bifunctional PKMYT1-targeting PROTAC empowered by AI-generation. Nature Communications. 16(1). 10759–10759.

Xu, Zefeng, Ping Wang, Jie Cao, et al.. (2025). INS018-055, A Novel Traf2- and NCK-interacting Kinase (TNIK) Inhibitor, Improves Lung Function in Patients With Idiopathic Pulmonary Fibrosis: Results From a Randomized, Double-blind, Placebo-controlled Phase 2a Study. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A2904–A2904.

Wang, Yazhou, Jinxin Liu, Yihong Zhang, et al.. (2025). Rational Design and Identification of ISM7594 as a Tissue-Agnostic FGFR2/3 Inhibitor. Journal of Medicinal Chemistry. 68(13). 13887–13906. 3 indexed citations

Sun, Deheng, Xin Cai, Xiao Ding, et al.. (2025). Design, Synthesis and Biological Evaluation of Novel, Potent, Selective and Orally Available DGKα Inhibitors for the Treatment of Tumors. Journal of Medicinal Chemistry. 68(23). 25011–25025.

Sun, Deheng, Zhen Wang, Lihua Min, et al.. (2025). Design, Synthesis, and Biological Evaluation of Novel Orally Available Covalent CDK12/13 Dual Inhibitors for the Treatment of Tumors. Journal of Medicinal Chemistry. 68(4). 4148–4167. 6 indexed citations

Galkin, Fedor, Shan Chen, Alexander Aliper, Alex Zhavoronkov, & Feng Ren. (2025). AI-driven toolset for IPF and aging research associates lung fibrosis with accelerated aging. Aging. 17(8). 1999–2014. 2 indexed citations

Zhavoronkov, Alex, Yujie Liu, Wenbin Hou, et al.. (2025). A Standardized Protocol for Mouse Longevity Studies in Preclinical Drug Development. Aging and Disease. 1 indexed citations

Kamya, Petrina, Ivan V. Ozerov, Frank W. Pun, et al.. (2024). PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery. Journal of Chemical Information and Modeling. 64(10). 3961–3969. 65 indexed citations breakdown →

Long, Xi, Barbara Steurer, Владимир Наумов, et al.. (2024). AI-enabled cancer target prioritization with optimal profiles balancing novelty, confidence and commercial tractability. 2(1). 1 indexed citations

10.

Wang, Qian, Ying Liu, Mingzhe Yan, et al.. (2024). Seasonal shifts in respiratory pathogen co-infections and the associated differential induction of cytokines in children. Cytokine. 186. 156847–156847. 1 indexed citations

11.

Wang, Yazhou, Chao Wang, Jinxin Liu, et al.. (2024). Discovery of 3-hydroxymethyl-azetidine derivatives as potent polymerase theta inhibitors. Bioorganic & Medicinal Chemistry. 103. 117662–117662. 9 indexed citations

12.

Meng, Fanye, Jinxin Liu, Zhongying Cao, et al.. (2024). Discovery of macrocyclic CDK2/4/6 inhibitors with improved potency and DMPK properties through a highly efficient macrocyclic drug design platform. Bioorganic Chemistry. 146. 107285–107285. 4 indexed citations

13.

Ivanenkov, Yan A., Daniil Polykovskiy, Dmitry S. Bezrukov, et al.. (2023). Chemistry42: An AI-Driven Platform for Molecular Design and Optimization. Journal of Chemical Information and Modeling. 63(3). 695–701. 109 indexed citations breakdown →

14.

Wang, Chi Chiu, et al.. (2023). #296 : Identification and Validation of Two Novel Therapeutic Targets for Endometriosis with Artificial Intelligence (AI). SHILAP Revista de lepidopterología. 5(4). 645–645.

15.

Pun, Frank W., Hoi-Wing Leung, Tomas Schmauck‐Medina, et al.. (2023). A comprehensive AI‐driven analysis of large‐scale omic datasets reveals novel dual‐purpose targets for the treatment of cancer and aging. Aging Cell. 22(12). e14017–e14017. 19 indexed citations

16.

Naumov, Vladimir, Hoi-Wing Leung, Frank W. Pun, et al.. (2023). Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery. Aging. 15(11). 4649–4666. 19 indexed citations

17.

Pun, Frank W., Bonnie Hei Man Liu, Xi Long, et al.. (2022). Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics – An AI-Enabled Biological Target Discovery Platform. Frontiers in Aging Neuroscience. 14. 59 indexed citations

18.

Yang, Ting, Paul Wren, Yueting Zhang, et al.. (2014). 2-Aminopyrimidin-4(1H)-one as the novel bioisostere of urea: Discovery of novel and potent CXCR2 antagonists. Bioorganic & Medicinal Chemistry Letters. 24(23). 5493–5496. 11 indexed citations

19.

Deng, Guanghui, Baowei Zhao, Yingli Ma, et al.. (2013). Novel complex crystal structure of prolyl hydroxylase domain-containing protein 2 (PHD2): 2,8-Diazaspiro[4.5]decan-1-ones as potent, orally bioavailable PHD2 inhibitors. Bioorganic & Medicinal Chemistry. 21(21). 6349–6358. 14 indexed citations

20.

Zhao, Baowei, Xuesong Xu, Guanghui Deng, et al.. (2012). Indole-propionic acid derivatives as potent, S1P3-sparing and EAE efficacious sphingosine-1-phosphate 1 (S1P1) receptor agonists. Bioorganic & Medicinal Chemistry Letters. 22(8). 2794–2797. 14 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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