Xiaorui Wang

45 total papers · 525 total citations
28 papers, 300 citations indexed

About

Xiaorui Wang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Xiaorui Wang has authored 28 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 8 papers in Materials Chemistry. Recurrent topics in Xiaorui Wang's work include Computational Drug Discovery Methods (14 papers), Protein Structure and Dynamics (10 papers) and Machine Learning in Materials Science (7 papers). Xiaorui Wang is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Protein Structure and Dynamics (10 papers) and Machine Learning in Materials Science (7 papers). Xiaorui Wang collaborates with scholars based in China, Macao and United States. Xiaorui Wang's co-authors include Tingjun Hou, Dejun Jiang, Chang‐Yu Hsieh, Hanqing Feng, Yafeng Deng, Jike Wang, Odin Zhang, Quan‐Xiang Wu, Hongyan Du and Yan‐Ping Shi and has published in prestigious journals such as Chemical Reviews, Nucleic Acids Research and Nature Communications.

In The Last Decade

Xiaorui Wang

21 papers receiving 295 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Xiaorui Wang	151	99	63	33	28	28	300
Kamlesh Kumar Sahu	134 0.9×	29 0.3×	8 0.1×	25 0.8×	16 0.6×	39	346
Ryunosuke Yoshino	215 1.4×	119 1.2×	17 0.3×	14 0.4×	46 1.6×	24	358
Duc-Hung Pham	115 0.8×	93 0.9×	35 0.6×	20 0.6×	58 2.1×	18	332
Geeta Kumari	96 0.6×	8 0.1×	26 0.4×	27 0.8×	9 0.3×	26	245
Shazia Shamas	122 0.8×	23 0.2×	10 0.2×	32 1.0×	19 0.7×	31	290
Diego E. B. Gomes	193 1.3×	83 0.8×	68 1.1×	13 0.4×	14 0.5×	23	311
Mohammed Haris Siddiqui	100 0.7×	85 0.9×	30 0.5×	37 1.1×	32 1.1×	22	298
Eveline M. Bezerra	165 1.1×	55 0.6×	32 0.5×	10 0.3×	17 0.6×	25	357
João Vítor de Assis	72 0.5×	13 0.1×	55 0.9×	18 0.5×	23 0.8×	17	338
Abhishek Thakur	138 0.9×	72 0.7×	43 0.7×	14 0.4×	55 2.0×	24	323

Countries citing papers authored by Xiaorui Wang

Since Specialization

Citations

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

Fields of papers citing papers by Xiaorui Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaorui Wang

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

All Works

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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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