Siwei Yang

36 papers receiving 521 citations

Peers

Siwei Yang
Comparison fields: 5 of 107
  • Biophysics 63
  • Structural Biology 8
  • Molecular Biology 263
  • Orthodontics 13
  • Biochemistry 15
Replace Sharon V. King with:
Sharon V. King United States
Julia Walther Germany
Jakob M. A. Mauritz United Kingdom
Shulei Wang China
Minhyeok Kim South Korea
Gaetan G. Lehmann France
Alison M. Forsyth United States
Joana Cerveira United Kingdom
Chao Xin China
Marco Wiltgen Austria
Siwei Yang relative to Sharon V. King United States Sharon V. King's profile →
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Citations per year

Countries citing papers authored by Siwei Yang

Since Specialization
Citations

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

Fields of papers citing papers by Siwei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Siwei Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Siwei Yang Line = papers co-authored together Siwei Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006218
2 202151
3 200839
4 201925
5 202223
6 201817
7 201015
8 202313
9
in vitroでのCr(VI)の超高感度蛍光プローブスイッチとしてのポリドーパミンドット【Powered by NICT】
201711
10 200610
11 202010
12 20199
13
白色発光ダイオード用の高固体発光黒鉛C_3N_4ナノチューブ【JST・京大機械翻訳】
20198
14 20068
15 20188
16 20257
17 20207
18 20216
19 20225
20 20085

About Siwei Yang

Siwei Yang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Hepatology, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 45 papers that have together received 523 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers), AI in cancer detection (3 papers), Gene expression and cancer classification (3 papers), Renal cell carcinoma treatment (2 papers), Medical Image Segmentation Techniques (2 papers), Metallurgy and Material Forming (2 papers) and Air Quality and Health Impacts (2 papers). The work is most often cited by research in Biophysics (63 citations), Structural Biology (8 citations), Molecular Biology (263 citations), Orthodontics (13 citations) and Biochemistry (15 citations). Siwei Yang has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Thomas Cremer, Karl Rohr, Cinzia Tiberi, Irina Solovei, Katrin Küpper, Heinrich Leonhardt, H. Albiez, Lorella Vecchio, Lothar Schermelleh and Boris Joffe. Their work appears in journals such as Computer Networks, Journal of Manufacturing Processes, Sensors and Actuators B Chemical, Academic Radiology and Biochimica et Biophysica Acta (BBA) - Molecular Cell Research.

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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