Fugang Yan

418 total citations
12 papers, 350 citations indexed

About

Fugang Yan is a scholar working on Mechanical Engineering, Molecular Biology and Mechanics of Materials. According to data from OpenAlex, Fugang Yan has authored 12 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Mechanical Engineering, 4 papers in Molecular Biology and 4 papers in Mechanics of Materials. Recurrent topics in Fugang Yan's work include Advanced machining processes and optimization (4 papers), Protein Structure and Dynamics (2 papers) and Advanced Measurement and Detection Methods (2 papers). Fugang Yan is often cited by papers focused on Advanced machining processes and optimization (4 papers), Protein Structure and Dynamics (2 papers) and Advanced Measurement and Detection Methods (2 papers). Fugang Yan collaborates with scholars based in China, Sweden and United States. Fugang Yan's co-authors include Peng Zhou, Qingqing Miao, Yang Meng, Zhongyan Li, Li Wen, Zheng Chen, Heyi Wang, Zhong-Yan Li, Bin Lin and Shuai Yan and has published in prestigious journals such as Journal of Theoretical Biology, Current Drug Metabolism and Journal of Biomolecular Structure and Dynamics.

In The Last Decade

Fugang Yan

12 papers receiving 350 citations

Peers

Fugang Yan

MB

ONCOL

CTM

RNMI

ME

Nilesh Kumar India

Antonio Palmeri Italy

Pravin Muthu United States

Fei Shen China

Seyed Ali Madani Tonekaboni Canada

Ramesh Utharala Germany

Xuhong Wang China

Dacheng Ma China

J. Ptáček Czechia

Curtis J. Layton United States

Nilesh Kumar India

Fugang Yan

176 ×0.7

MB

20 ×0.2

ONCOL

19 ×0.2

CTM

12 ×0.2

RNMI

19 ×0.4

ME

Citations per year, relative to Fugang Yan Fugang Yan (= 1×) peers Nilesh Kumar

Countries citing papers authored by Fugang Yan

Since Specialization

Citations

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

Fields of papers citing papers by Fugang Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fugang Yan

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

All Works

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12 of 12 papers shown

1.

Hua, Qiang, et al.. (2021). Multi-target tracking of vehicles based on optimized DeepSort. Journal of ZheJiang University (Engineering Science). 55(6). 1056–1064. 3 indexed citations

2.

Yue, Caixu, et al.. (2020). Research on TANH Material Constitutive Model Based on Analytical Method. Journal of Mechanical Engineering. 56(9). 252–252. 4 indexed citations

3.

Yue, Caixu, Xia Ji, Xianli Liu, et al.. (2020). Analytical Prediction of Residual Stress in the Machined Surface during Milling. Metals. 10(4). 498–498. 14 indexed citations

4.

Zhou, Peng, Qingqing Miao, Fugang Yan, et al.. (2019). Is protein context responsible for peptide-mediated interactions?. Molecular Omics. 15(4). 280–295. 94 indexed citations

5.

Li, Zhong-Yan, Fugang Yan, Qingqing Miao, et al.. (2019). Self-binding peptides: Binding-upon-folding versus folding-upon-binding. Journal of Theoretical Biology. 469. 25–34. 65 indexed citations

6.

Zhou, Peng, Fugang Yan, Qingqing Miao, Zheng Chen, & Heyi Wang. (2019). Why the first self-binding peptide of human c-Src kinase does not contain class II motif but can bind to its cognate Src homology 3 domain in class II mode?. Journal of Biomolecular Structure and Dynamics. 39(1). 310–318. 54 indexed citations

7.

Li, Zhongyan, Qingqing Miao, Fugang Yan, Yang Meng, & Peng Zhou. (2018). Machine Learning in Quantitative Protein–peptide Affinity Prediction: Implications for Therapeutic Peptide Design. Current Drug Metabolism. 20(3). 170–176. 80 indexed citations

8.

Cheng, Yaonan, et al.. (2018). Study on damage behavior of carbide tool for milling difficult-to-machine material. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science. 233(2). 735–747. 5 indexed citations

9.

Liu, Xianli, et al.. (2015). Large chip production mechanism under the extreme load cutting conditions. Chinese Journal of Mechanical Engineering. 28(2). 343–352. 1 indexed citations

10.

Liu, Xianli, et al.. (2012). Research on the dynamic mechanical characteristics and turning tool life under the conditions of excessively heavy-duty turning. Frontiers of Mechanical Engineering. 7(3). 329–334. 7 indexed citations

11.

Yan, Shuai, et al.. (2012). Friction and wear of self-mated SiC and Si3N4 in green water-based lubricant. International Journal of Precision Engineering and Manufacturing. 13(7). 1067–1072. 22 indexed citations

12.

Liu, Xianli, et al.. (2005). Quality measurement of cutting and grinding surfaces based on image. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5632. 139–139. 1 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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