Hailong Lin

1.6k total citations
39 papers, 613 citations indexed

About

Hailong Lin is a scholar working on Molecular Medicine, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Hailong Lin has authored 39 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Medicine, 8 papers in Infectious Diseases and 7 papers in Molecular Biology. Recurrent topics in Hailong Lin's work include Antibiotic Resistance in Bacteria (9 papers), COVID-19 Clinical Research Studies (5 papers) and Antimicrobial Resistance in Staphylococcus (3 papers). Hailong Lin is often cited by papers focused on Antibiotic Resistance in Bacteria (9 papers), COVID-19 Clinical Research Studies (5 papers) and Antimicrobial Resistance in Staphylococcus (3 papers). Hailong Lin collaborates with scholars based in China and United States. Hailong Lin's co-authors include Lin Lin, Hua‐Jun Chen, Jian Zhou, Juan Du, Qing Duan, Xiaodan Chen, Junwan Lu, Yunjing Xue, Qiaoling Li and Jing Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and Scientific Reports.

In The Last Decade

Hailong Lin

38 papers receiving 607 citations

Peers

Hailong Lin
Comparison fields: 5 of 99
  • Radiology, Nuclear Medicine and Imaging 139
  • Infectious Diseases 108
  • Molecular Biology 92
  • Pulmonary and Respiratory Medicine 81
  • Cognitive Neuroscience 77
Kai-Lin Hwang Taiwan
Shivam Pandey India
James Truong United States
Makoto Onodera Japan
Guang‐Shing Cheng United States
Akihiro Ito Japan
Oliver Hendricks Denmark
Hamidreza Abtahi Iran
Aurel Nechita Romania
Ingrid M. C. Kamerling Netherlands
Kai-Lin Hwang Taiwan View profile →
Citations per field, relative to Hailong Lin
Hailong Lin · 1×
Citations per year, relative to Hailong Lin
Hailong Lin · 1×

Countries citing papers authored by Hailong Lin

Since Specialization
Citations

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

Fields of papers citing papers by Hailong Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hailong Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Lin. A scholar is included among the top collaborators of Hailong Lin 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 Hailong Lin. Hailong Lin 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 2
2 4
3 5
4 3
5 5
6 8
7 9
8 2
9 14
10 13
11 1
12 15
13 13
14 13
15 25
16 43
17 18
18 17
19 10
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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