Xinqiang Ding

835 total citations
19 papers, 444 citations indexed

About

Xinqiang Ding is a scholar working on Molecular Biology, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Xinqiang Ding has authored 19 papers receiving a total of 444 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 6 papers in Materials Chemistry and 5 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Xinqiang Ding's work include Protein Structure and Dynamics (11 papers), Machine Learning in Materials Science (5 papers) and Spectroscopy and Quantum Chemical Studies (4 papers). Xinqiang Ding is often cited by papers focused on Protein Structure and Dynamics (11 papers), Machine Learning in Materials Science (5 papers) and Spectroscopy and Quantum Chemical Studies (4 papers). Xinqiang Ding collaborates with scholars based in United States, Hong Kong and United Kingdom. Xinqiang Ding's co-authors include Charles L. Brooks, Bin Zhang, Jonah Z. Vilseck, Zhengting Zou, Ryan L. Hayes, Xingcheng Lin, Yujin Wu, Yanming Wang, Zhi John Lu and Zheng Rong Yang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The Journal of Physical Chemistry B.

In The Last Decade

Xinqiang Ding

19 papers receiving 439 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xinqiang Ding United States 13 363 70 66 41 25 19 444
Nicholas B. Rego United States 6 330 0.9× 116 1.7× 73 1.1× 74 1.8× 47 1.9× 7 515
Surl-Hee Ahn United States 9 275 0.8× 43 0.6× 56 0.8× 43 1.0× 17 0.7× 24 449
Stefano Raniolo Switzerland 9 358 1.0× 73 1.0× 105 1.6× 39 1.0× 31 1.2× 14 439
Duy Phuoc Tran Japan 13 430 1.2× 83 1.2× 82 1.2× 41 1.0× 73 2.9× 22 562
Wanda Niemyska Poland 11 358 1.0× 103 1.5× 64 1.0× 88 2.1× 31 1.2× 23 509
Yusuke Naritomi Japan 3 267 0.7× 72 1.0× 22 0.3× 43 1.0× 55 2.2× 5 312
Steven Lettieri United States 8 171 0.5× 50 0.7× 32 0.5× 28 0.7× 34 1.4× 11 304
Diego Prada‐Gracia Mexico 14 350 1.0× 117 1.7× 83 1.3× 147 3.6× 46 1.8× 26 606
Yousuke Ohno Japan 11 195 0.5× 69 1.0× 62 0.9× 71 1.7× 40 1.6× 19 402
Gentaro Morimoto Japan 9 200 0.6× 59 0.8× 121 1.8× 38 0.9× 22 0.9× 13 373

Countries citing papers authored by Xinqiang Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xinqiang Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinqiang Ding

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

All Works

19 of 19 papers shown
1.
Ding, Xinqiang. (2024). Bayesian Multistate Bennett Acceptance Ratio Methods. Journal of Chemical Theory and Computation. 20(5). 1878–1888. 2 indexed citations
2.
Ding, Xinqiang, et al.. (2024). Bayesian Approach for Computing Free Energy on Perturbation Graphs with Cycles. Journal of Chemical Theory and Computation. 20(23). 10384–10392. 1 indexed citations
3.
Ding, Xinqiang. (2024). Optimizing Force Fields with Experimental Data Using Ensemble Reweighting and Potential Contrasting. The Journal of Physical Chemistry B. 128(28). 6760–6769. 4 indexed citations
4.
Ding, Xinqiang, et al.. (2023). Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure prediction. Biophysical Journal. 122(17). 3425–3438. 6 indexed citations
5.
Hayes, Ryan L., et al.. (2023). Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling. Nature Communications. 14(1). 8515–8515. 12 indexed citations
6.
Wang, Cong, et al.. (2023). OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates. PLoS Computational Biology. 19(9). e1011442–e1011442. 14 indexed citations
7.
Ding, Xinqiang, et al.. (2023). Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks. ACS Central Science. 9(12). 2286–2297. 14 indexed citations
8.
Ding, Xinqiang, Xingcheng Lin, & Bin Zhang. (2021). Stability and folding pathways of tetra-nucleosome from six-dimensional free energy surface. Nature Communications. 12(1). 1091–1091. 39 indexed citations
9.
Ding, Xinqiang & Bin Zhang. (2021). DeepBAR: A Fast and Exact Method for Binding Free Energy Computation. The Journal of Physical Chemistry Letters. 12(10). 2509–2515. 28 indexed citations
10.
Vilseck, Jonah Z., Xinqiang Ding, Ryan L. Hayes, & Charles L. Brooks. (2021). Generalizing the Discrete Gibbs Sampler-Based λ-Dynamics Approach for Multisite Sampling of Many Ligands. Journal of Chemical Theory and Computation. 17(7). 3895–3907. 11 indexed citations
11.
Ding, Xinqiang & Bin Zhang. (2021). Computing Absolute Free Energy with Deep Generative Models. Biophysical Journal. 120(3). 195a–195a. 2 indexed citations
12.
Ding, Xinqiang, Yujin Wu, Yanming Wang, Jonah Z. Vilseck, & Charles L. Brooks. (2020). Accelerated CDOCKER with GPUs, Parallel Simulated Annealing, and Fast Fourier Transforms. Journal of Chemical Theory and Computation. 16(6). 3910–3919. 42 indexed citations
13.
Ding, Xinqiang & Bin Zhang. (2020). Computing Absolute Free Energy with Deep Generative Models. The Journal of Physical Chemistry B. 124(45). 10166–10172. 14 indexed citations
14.
Ding, Xinqiang, Zhengting Zou, & Charles L. Brooks. (2019). Deciphering protein evolution and fitness landscapes with latent space models. Nature Communications. 10(1). 5644–5644. 61 indexed citations
15.
Ding, Xinqiang, Jonah Z. Vilseck, & Charles L. Brooks. (2019). Fast Solver for Large Scale Multistate Bennett Acceptance Ratio Equations. Journal of Chemical Theory and Computation. 15(2). 799–802. 40 indexed citations
16.
Su, Min, Xinqiang Ding, Yan Li, et al.. (2017). Mechanism of Vps4 hexamer function revealed by cryo-EM. Science Advances. 3(4). e1700325–e1700325. 42 indexed citations
17.
Ding, Xinqiang, et al.. (2017). CDOCKER and $$\lambda$$-dynamics for prospective prediction in D3R Grand Challenge 2. Journal of Computer-Aided Molecular Design. 32(1). 89–102. 14 indexed citations
18.
Ding, Xinqiang, Jonah Z. Vilseck, Ryan L. Hayes, & Charles L. Brooks. (2017). Gibbs Sampler-Based λ-Dynamics and Rao–Blackwell Estimator for Alchemical Free Energy Calculation. Journal of Chemical Theory and Computation. 13(6). 2501–2510. 33 indexed citations
19.
Wu, Yang, Binbin Shi, Xinqiang Ding, et al.. (2015). Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data. Nucleic Acids Research. 43(15). 7247–7259. 65 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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