Xingbo Song

1.2k total citations
53 papers, 865 citations indexed

About

Xingbo Song is a scholar working on Molecular Biology, Cancer Research and Infectious Diseases. According to data from OpenAlex, Xingbo Song has authored 53 papers receiving a total of 865 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 16 papers in Cancer Research and 11 papers in Infectious Diseases. Recurrent topics in Xingbo Song's work include Cancer-related molecular mechanisms research (13 papers), Tuberculosis Research and Epidemiology (10 papers) and MicroRNA in disease regulation (9 papers). Xingbo Song is often cited by papers focused on Cancer-related molecular mechanisms research (13 papers), Tuberculosis Research and Epidemiology (10 papers) and MicroRNA in disease regulation (9 papers). Xingbo Song collaborates with scholars based in China, United States and Spain. Xingbo Song's co-authors include Binwu Ying, Lanlan Wang, Xiaojun Lu, Yi Zhou, Juan Zhou, Xuejiao Hu, Yuanxin Ye, Yunying Shi, Qian Wu and Bei Cai and has published in prestigious journals such as PLoS ONE, Clinical Infectious Diseases and Scientific Reports.

In The Last Decade

Xingbo Song

53 papers receiving 861 citations

Peers

Xingbo Song
Comparison fields: 5 of 89
  • Molecular Biology 460
  • Cancer Research 341
  • Epidemiology 151
  • Infectious Diseases 139
  • Immunology 110
Replace Xiangyang Lin with:
Xiangyang Lin China
Abdolkarim Moazeni‐Roodi Iran
Shijie Zhang China
Ryoko Minekawa Japan
Zhongmou Jin United States
Susanne Roser United States
Sheng-Fung Lin Taiwan
Jian Ding China
Xingye Wu China
Xiangyang Lin China View profile →
Citations per field, relative to Xingbo Song
Xingbo Song · 1×
Citations per year, relative to Xingbo Song
Xingbo Song · 1×

Countries citing papers authored by Xingbo Song

Since Specialization
Citations

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

Fields of papers citing papers by Xingbo Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingbo Song

This figure shows the co-authorship network connecting the top 25 collaborators of Xingbo Song. A scholar is included among the top collaborators of Xingbo 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 Xingbo Song. Xingbo 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 1
2 4
3 1
4 5
5 15
6 24
7 1
8
[Gene Mutation Spectrum Analysis of 170 Patients with Duchenne/Bayesian Muscular Dystrophy in Southwest of China].
1
9 13
10 11
11 10
12 12
13 40
14 62
15 24
16 20
17 53
18 11
19 17
20 64

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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