Yaoqi Zhou

18.6k total citations · 1 hit paper
270 papers, 13.2k citations indexed

About

Yaoqi Zhou is a scholar working on Molecular Biology, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Yaoqi Zhou has authored 270 papers receiving a total of 13.2k indexed citations (citations by other indexed papers that have themselves been cited), including 214 papers in Molecular Biology, 99 papers in Materials Chemistry and 27 papers in Biomedical Engineering. Recurrent topics in Yaoqi Zhou's work include Protein Structure and Dynamics (131 papers), RNA and protein synthesis mechanisms (93 papers) and Enzyme Structure and Function (76 papers). Yaoqi Zhou is often cited by papers focused on Protein Structure and Dynamics (131 papers), RNA and protein synthesis mechanisms (93 papers) and Enzyme Structure and Function (76 papers). Yaoqi Zhou collaborates with scholars based in United States, China and Australia. Yaoqi Zhou's co-authors include Yuedong Yang, Hongyi Zhou, G. Stell, Kuldip K. Paliwal, Martin Karplus, Eshel Faraggi, Chi Zhang, Jack Hanson, Huiying Zhao and Carol K. Hall and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Yaoqi Zhou

265 papers receiving 12.9k citations

Hit Papers

Distance‐scaled, finite ideal‐gas reference state improve... 2002 2026 2010 2018 2002 200 400 600
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.

  1. Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction
    2002 749 citations Yaoqi Zhou et al. profile →

Peers

Yaoqi Zhou
Andrzej Koliński Poland
Jeffrey Skolnick United States
Jeetain Mittal United States
Eugene I. Shakhnovich United States
Robert L. Jernigan United States
Sándor Vajda United States
Per Larsson Sweden
Huan‐Xiang Zhou United States
Rosemary Braun United States
İvet Bahar United States
Andrzej Koliński Poland
Yaoqi Zhou
Citations per year, relative to Yaoqi Zhou Yaoqi Zhou (= 1×) peers Andrzej Koliński

Countries citing papers authored by Yaoqi Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Yaoqi Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaoqi Zhou

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

All Works

20 of 20 papers shown
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Zhan, Jian, et al.. (2025). On the Completeness of Existing RNA Fragment Structures. Genomics Proteomics & Bioinformatics.
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Li, Qilin, et al.. (2024). Design and synthesis of large Stokes shift DNA dyes with reduced genotoxicity. Biochemical and Biophysical Research Communications. 724. 150224–150224. 1 indexed citations
5.
Peng, Yang, et al.. (2023). Heterogeneous high-entropy catalyst nanoparticles for oxygen evolution reaction: Impact of oxygen and fluorine introduction. International Journal of Hydrogen Energy. 51. 1218–1228. 21 indexed citations
6.
Zhang, Zhe, Hong Xu, Peng Xiong, et al.. (2023). Minimal twister sister-like self-cleaving ribozymes in the human genome revealed by deep mutational scanning. eLife. 12. 2 indexed citations
7.
Zhou, Yaoqi, Thomas Litfin, & Jian Zhan. (2023). 3 = 1 + 2: how the divide conquered de novo protein structure prediction and what is next?. National Science Review. 10(12). 6 indexed citations
8.
Singh, Jaspreet, Thomas Litfin, Jaswinder Singh, Kuldip K. Paliwal, & Yaoqi Zhou. (2022). SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model. Bioinformatics. 38(7). 1888–1894. 34 indexed citations
9.
Zhou, Bailing, Jing Feng, Baohua Ji, et al.. (2022). EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning. Briefings in Bioinformatics. 24(1). 7 indexed citations
10.
Zhang, Tongchuan, Jaswinder Singh, Thomas Litfin, et al.. (2021). RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis. Bioinformatics. 37(20). 3494–3500. 26 indexed citations
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Zhang, Zhe, Peng Xiong, Tongchuan Zhang, et al.. (2019). Accurate inference of the full base-pairing structure of RNA by deep mutational scanning and covariation-induced deviation of activity. Nucleic Acids Research. 48(3). 1451–1465. 13 indexed citations
13.
Cai, Yufeng, Zhe Sun, Yutong Lu, et al.. (2019). SPOT‐Fold: Fragment‐Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map. Journal of Computational Chemistry. 41(8). 745–750. 9 indexed citations
14.
Chen, Pin, Yutong Lu, Yunfei Du, et al.. (2019). DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state. Journal of Cheminformatics. 11(1). 52–52. 36 indexed citations
15.
Taherzadeh, Ghazaleh, et al.. (2019). SPRINT-Gly: predictingN-andO-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties. Bioinformatics. 35(20). 4140–4146. 49 indexed citations
16.
Lin, Hai, Jill L. Reiter, Yue Wang, et al.. (2019). RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants. Genome biology. 20(1). 254–254. 41 indexed citations
17.
Zhao, Huiying, Yuedong Yang, Yutong Lu, et al.. (2017). Quantitative mapping of genetic similarity in human heritable diseases by shared mutations. Human Mutation. 39(2). 292–301. 4 indexed citations
18.
Li, Meng, Weixing Feng, Xinjun Zhang, et al.. (2017). ExonImpact: Prioritizing Pathogenic Alternative Splicing Events. Queensland's institutional digital repository (The University of Queensland). 2 indexed citations
19.
Zhao, Huiying, Yuedong Yang, & Yaoqi Zhou. (2013). Prediction of RNA binding proteins comes of age from low resolution to high resolution. Molecular BioSystems. 9(10). 2417–2425. 33 indexed citations
20.
Zhang, Wei, Song Liu, & Yaoqi Zhou. (2008). SP5: Improving Protein Fold Recognition by Using Torsion Angle Profiles and Profile-Based Gap Penalty Model. PLoS ONE. 3(6). e2325–e2325. 60 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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