Shuxing Zhang

6.8k citations
87 papers · 4.2k · h-index 35

Impact in

Papers in

    • Protein Structure and Dynamics 11
    • PI3K/AKT/mTOR signaling in cancer 10
    • Protein Kinase Regulation and GTPase Signaling 8
    • Ubiquitin and proteasome pathways 7
    • Receptor Mechanisms and Signaling 6
    • RNA modifications and cancer 6
    • Computational Drug Discovery Methods 29

Shuxing Zhang

83 papers receiving 4.1k citations

Peers

Shuxing Zhang
Comparison fields: 5 of 142
  • Computational Theory and Mathematics 824
  • Molecular Biology 2.8k
  • Pharmacology 309
  • Cancer Research 467
  • Oncology 631
Replace Yong Xu with:
Yong Xu China
Giorgio Cozza Italy
Elaine Lai‐Han Leung Macao
Vincent Kam Wai Wong Macao
Takahiro Seki Japan
Yanqiong Zhang China
Bridget K. Wagner United States
Sheng Tian China
Mee‐Hyun Lee South Korea
Shuxing Zhang relative to Yong Xu China Yong Xu's profile →
Citations per field
00.5×1.5×2.1×
Yong Xu · 1×
Citations per year

Countries citing papers authored by Shuxing Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Shuxing Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012336
2 2013318
3 2017246
4 2011241
5 2006199
6 2001184
7 2012156
8 2018139
9 2019138
10 2014132
11 1994122
12 2022113
13 201587
14 201276
15 201776
16 200874
17 201973
18 201066
19 200666
20 200863

About Shuxing Zhang

Shuxing Zhang is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Oncology and Pharmacology, having authored 87 papers that have together received 4.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (29 papers), Protein Structure and Dynamics (11 papers), PI3K/AKT/mTOR signaling in cancer (10 papers), Protein Kinase Regulation and GTPase Signaling (8 papers), Ubiquitin and proteasome pathways (7 papers), Receptor Mechanisms and Signaling (6 papers), RNA modifications and cancer (6 papers) and Pharmacogenetics and Drug Metabolism (6 papers). The work is most often cited by research in Computational Theory and Mathematics (824 citations), Molecular Biology (2.8k citations), Pharmacology (309 citations), Cancer Research (467 citations) and Oncology (631 citations). Shuxing Zhang has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include A. Srinivas Reddy, John Kenneth Morrow, Lu Chen, Baojian Wu, Ming Hu, Zhi Tan, Alexander Tropsha, Alexander Golbraikh, Lei Du‐Cuny and George A. Călin. Their work appears in journals such as Cancer Research, Journal of Chemical Information and Modeling, Scientific Reports, Nature Communications and Expert Opinion on Drug Discovery.

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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