Linli Li

111 papers receiving 2.5k citations

Linli Li's Hit Papers

SARS-CoV-2 M pro inhibitors with antiviral activity in a transgenic mouse model 2021 · 370 citations
3700+1+3Years since publication100200300

Peers

Linli Li
Comparison fields: 5 of 133
  • Computational Theory and Mathematics 818
  • Geriatrics and Gerontology 70
  • Molecular Biology 1.4k
  • Organic Chemistry 565
  • Toxicology 61
Replace Daniel Martinez Molina with:
Daniel Martinez Molina Sweden
Rozbeh Jafari Sweden
Chenzhong Liao China
Teruki Honma Japan
Hwangseo Park South Korea
Marina Ignatushchenko United States
Fabrizio Giordanetto Sweden
Rajesh V. Devraj United States
Jingkang Shen China
Xuben Hou China
Linli Li relative to Daniel Martinez Molina Sweden Daniel Martinez Molina's profile →
Citations per field
00.5×1.5×
Daniel Martinez Molina · 1×
Citations per year

Countries citing papers authored by Linli Li

Since Specialization
Citations

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

Fields of papers citing papers by Linli Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 115 papers — load more, or switch the sort, to bring in the rest.

#Work
1
SARS-CoV-2 M pro inhibitors with antiviral activity in a transgenic mouse model
Hit paper breakdown →
2021370
2 2013155
3 2008107
4 202278
5 201168
6 202066
7 201365
8 202458
9 202256
10 201155
11 201255
12 201052
13 200851
14 202248
15 202248
16 201544
17 201741
18 201841
19 200940
20 201738

About Linli Li

Linli Li is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Oncology and Filtration and Separation, having authored 115 papers that have together received 2.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (25 papers), Synthesis and biological activity (9 papers), Cancer therapeutics and mechanisms (7 papers), Receptor Mechanisms and Signaling (6 papers), Chemical and Physical Properties in Aqueous Solutions (5 papers), Analytical Chemistry and Chromatography (5 papers), Protein Degradation and Inhibitors (5 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). The work is most often cited by research in Computational Theory and Mathematics (818 citations), Geriatrics and Gerontology (70 citations), Molecular Biology (1.4k citations), Organic Chemistry (565 citations) and Toxicology (61 citations). Linli Li has collaborated with scholars based in China, United States and France. Frequent co-authors include Shengyong Yang, Huanzhang Xie, Guo‐Bo Li, Lingling Yang, Qi Huang, Wenjing Wang, Ji-Xia Ren, Jun Zou, Qingqing Xie and Rong Xiang. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Journal of Medicinal Chemistry, European Journal of Medicinal Chemistry, Journal of Chemical Information and Modeling and Journal of Molecular Graphics and Modelling.

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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