Feng Ren

3.0k citations
86 papers · 1.5k indexed · 2 hit papers · h-index 23

Impact in

Papers in

    • Cancer therapeutics and mechanisms 6
    • Sphingolipid Metabolism and Signaling 4
    • Histone Deacetylase Inhibitors Research 4
    • Epigenetics and DNA Methylation 4
    • Catalytic C–H Functionalization Methods 4

Feng Ren

80 papers receiving 1.4k citations

Hit Papers

PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery 2024 · 65 citations
650+1+2Years since publication255075100

Peers

Feng Ren
Comparison fields: 5 of 134
  • Health Informatics 29
  • Catalysis 141
  • Aging 25
  • Computational Theory and Mathematics 220
  • Organic Chemistry 366
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Feng Ren relative to Andrea Adamo United States Andrea Adamo's profile →
Citations per field
00.5×6.3×
Andrea Adamo · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Feng 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 Feng Ren Line = papers co-authored together Feng Ren links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Chemistry42: An AI-Driven Platform for Molecular Design and Optimization
Hit paper breakdown →
2023109
2 201476
3
PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
Hit paper breakdown →
202465
4 202259
5 201550
6 201650
7 202346
8 201445
9 202240
10 202339
11 201339
12 201538
13 200738
14 200737
15 199337
16 202335
17 199932
18 201526
19 199326
20 202324

About Feng Ren

Feng Ren is a scholar working on Molecular Biology, Organic Chemistry, Materials Chemistry, Oncology and Computational Theory and Mathematics, having authored 86 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Cancer therapeutics and mechanisms (6 papers), Catalysis and Oxidation Reactions (5 papers), Sphingolipid Metabolism and Signaling (4 papers), Histone Deacetylase Inhibitors Research (4 papers), Epigenetics and DNA Methylation (4 papers), Catalytic C–H Functionalization Methods (4 papers) and Catalytic Processes in Materials Science (4 papers). The work is most often cited by research in Health Informatics (29 citations), Catalysis (141 citations), Aging (25 citations), Computational Theory and Mathematics (220 citations) and Organic Chemistry (366 citations). Feng Ren has collaborated with scholars based in China, United States and Hong Kong. Frequent 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. Their work appears in journals such as Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters, ACS Medicinal Chemistry Letters, Bioorganic & Medicinal Chemistry and Tetrahedron.

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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