Sujia Wu

95 total papers · 1.4k total citations
62 papers, 1.0k citations indexed

About

Sujia Wu is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology and Rheumatology. According to data from OpenAlex, Sujia Wu has authored 62 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Pulmonary and Respiratory Medicine, 21 papers in Molecular Biology and 19 papers in Rheumatology. Recurrent topics in Sujia Wu's work include Sarcoma Diagnosis and Treatment (34 papers), Bone Tumor Diagnosis and Treatments (19 papers) and MicroRNA in disease regulation (9 papers). Sujia Wu is often cited by papers focused on Sarcoma Diagnosis and Treatment (34 papers), Bone Tumor Diagnosis and Treatments (19 papers) and MicroRNA in disease regulation (9 papers). Sujia Wu collaborates with scholars based in China, Belgium and United States. Sujia Wu's co-authors include Xin Shi, Guangxin Zhou, Jianning Zhao, Junfeng Zhang, Xiuchun Yu, Xing Zhou, Xiaozhou Liu, Zhaoming Ye, Jiangning Chen and Chengjun Li and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Scientific Reports.

In The Last Decade

Sujia Wu

61 papers receiving 1.0k citations

Author Peers

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

Author Last Decade Papers Cites
Sujia Wu 505 377 322 212 163 62 1.0k
Wangjun Yan 559 1.1× 462 1.2× 184 0.6× 145 0.7× 200 1.2× 42 1.2k
Kyu Yeoun Won 432 0.9× 256 0.7× 224 0.7× 134 0.6× 285 1.7× 74 1.0k
Nobuo Hoshi 348 0.7× 201 0.5× 277 0.9× 160 0.8× 252 1.5× 54 1.0k
Lu Xie 424 0.8× 268 0.7× 619 1.9× 188 0.9× 427 2.6× 56 1.1k
Philip Kunkel 457 0.9× 245 0.6× 148 0.5× 125 0.6× 167 1.0× 35 1.1k
Concha López‐Ginés 341 0.7× 198 0.5× 253 0.8× 148 0.7× 204 1.3× 66 1.1k
Huiying He 699 1.4× 285 0.8× 534 1.7× 109 0.5× 189 1.2× 62 1.2k
Xiaoling She 685 1.4× 576 1.5× 245 0.8× 179 0.8× 151 0.9× 46 1.2k
Andreas M. Luebke 337 0.7× 164 0.4× 307 1.0× 116 0.5× 249 1.5× 48 811
Eiji Kozawa 352 0.7× 122 0.3× 300 0.9× 313 1.5× 186 1.1× 53 956

Countries citing papers authored by Sujia Wu

Since Specialization
Citations

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

Fields of papers citing papers by Sujia Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sujia Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Sujia Wu. A scholar is included among the top collaborators of Sujia Wu 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 Sujia Wu. Sujia Wu 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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