Qinxin Song

938 total citations
64 papers, 735 citations indexed

About

Qinxin Song is a scholar working on Molecular Biology, Biomedical Engineering and Ecology. According to data from OpenAlex, Qinxin Song has authored 64 papers receiving a total of 735 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 17 papers in Biomedical Engineering and 7 papers in Ecology. Recurrent topics in Qinxin Song's work include Advanced biosensing and bioanalysis techniques (23 papers), Biosensors and Analytical Detection (16 papers) and Molecular Biology Techniques and Applications (12 papers). Qinxin Song is often cited by papers focused on Advanced biosensing and bioanalysis techniques (23 papers), Biosensors and Analytical Detection (16 papers) and Molecular Biology Techniques and Applications (12 papers). Qinxin Song collaborates with scholars based in China, Japan and New Zealand. Qinxin Song's co-authors include Guohua Zhou, Bingjie Zou, Hideki Kambara, Tomoharu Kajiyama, Jian‐Ping Wang, Haiping Wu, Jingyuan Wen, Danhui Li, Jie Yang and Wanqi Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Analytical Chemistry and Chemical Communications.

In The Last Decade

Qinxin Song

61 papers receiving 723 citations

Peers

Qinxin Song
Comparison fields: 5 of 93
  • Molecular Biology 459
  • Biomedical Engineering 219
  • Cancer Research 85
  • Materials Chemistry 77
  • Electronic, Optical and Magnetic Materials 53
Replace Haimei Shi with:
Haimei Shi China
Senbiao Fang China
Alireza Nezami Iran
Hitesh Kumar Dewangan India
Yu‐Wei Chou Taiwan
Wanwei Qiu China
Jianyuan Wu China
Bagganahalli S. Somashekar India
Petr Michálek Czechia
Chandan Singh India
Haimei Shi China View profile →
Citations per field, relative to Qinxin Song
Qinxin Song · 1×
Citations per year, relative to Qinxin Song
Qinxin Song · 1×

Countries citing papers authored by Qinxin Song

Since Specialization
Citations

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

Fields of papers citing papers by Qinxin Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qinxin Song

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 0
3 0
4 7
5 9
6 1
7 1
8 4
9 14
10 4
11 19
12 15
13 34
14 78
15 15
16 7
17 2
18 37
19 6
20 10

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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