Chuanli Ren

3.4k citations
95 papers · 2.3k indexed · 1 hit paper · h-index 29

Impact in

Papers in

Chuanli Ren

89 papers receiving 2.3k citations

Hit Papers

iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction 2025 · 57 citations
57202520261020304050

Peers

Chuanli Ren
Comparison fields: 5 of 110
  • Process Chemistry and Technology 349
  • Cancer Research 478
  • Biomaterials 404
  • Organic Chemistry 482
  • Electrochemistry 88
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Kouji Iida Japan
Tuck−Yun Cheang China
Xin Shang China
Ye Wang China
Yuan Huang China
Yūsuke Izumi Japan
Haiyang Yu China
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Chuanli Ren relative to Kouji Iida Japan Kouji Iida's profile →
Citations per field
00.5×5.5×
Kouji Iida · 1×
Citations per year

Countries citing papers authored by Chuanli Ren

Since Specialization
Citations

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

Fields of papers citing papers by Chuanli Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chuanli Ren, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chuanli Ren Line = papers co-authored together Chuanli Ren links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20255
2
iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction
Hit paper breakdown →
202557
3 20250
4 20250
5 20252
6 20250
7 20251
8 20244
9 202314
10 202139
11 201874
12 201625
13 201547
14 201526
15 201543
16 20157
17 201444
18 20126
19 201210
20 20112

About Chuanli Ren

Chuanli Ren is a scholar working on Process Chemistry and Technology, Cancer Research, Biomaterials, Electrochemistry and Oncology, having authored 95 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (15 papers), Carbon dioxide utilization in catalysis (13 papers), biodegradable polymer synthesis and properties (13 papers), Cancer Cells and Metastasis (9 papers), MicroRNA in disease regulation (8 papers), Advanced Nanomaterials in Catalysis (7 papers), Electrochemical sensors and biosensors (6 papers) and Pancreatic and Hepatic Oncology Research (6 papers). The work is most often cited by research in Process Chemistry and Technology (349 citations), Cancer Research (478 citations), Biomaterials (404 citations), Organic Chemistry (482 citations) and Electrochemistry (88 citations). Chuanli Ren has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Zhibo Li, Na Zhao, Shaofeng Liu, Zhanjun Yang, Deyuan Fu, Chongxu Han, Huaike Li, Li Liu, Yunxin Li and Xiao Hu. Their work appears in journals such as Tumor Biology, Chemical Communications, Carcinogenesis, Analytical Chemistry and PLoS ONE.

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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