Xiaoli Lin

728 citations
54 papers · 344 · h-index 11

Impact in

Papers in

    • Protein Structure and Dynamics 9
    • Machine Learning in Bioinformatics 7
    • Bioinformatics and Genomic Networks 6
    • RNA and protein synthesis mechanisms 4
    • Gut microbiota and health 2
    • Computational Drug Discovery Methods 14

Xiaoli Lin

48 papers receiving 338 citations

Peers

Xiaoli Lin
Comparison fields: 5 of 107
  • Computational Theory and Mathematics 93
  • Molecular Biology 144
  • Obstetrics and Gynecology 10
  • Transplantation 3
  • Cancer Research 13
Replace Cheng-Yan Kao with:
Cheng-Yan Kao Taiwan
Tzu-Yi Chen United States
Frédéric Lafitte Belgium
Mihai Glont United Kingdom
Jun Ren China
Chunyan Ao China
Sébastien Géhant Switzerland
Jessica Binder United States
Elzbieta Rembeza Sweden
Xiaoli Lin relative to Cheng-Yan Kao Taiwan Cheng-Yan Kao's profile →
Citations per field
00.5×10.9×
Cheng-Yan Kao · 1×
Citations per year

Countries citing papers authored by Xiaoli Lin

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoli Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoli Lin, 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 Xiaoli Lin Line = papers co-authored together Xiaoli Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201932
2 202519
3 202318
4 201818
5 202018
6 201416
7 202315
8 201813
9 202212
10 202211
11 201811
12 202310
13 202310
14
Guanxi and word-of-mouth
200310
15 20219
16 20099
17 20218
18 20208
19 20226
20 20236

About Xiaoli Lin

Xiaoli Lin is a scholar working on Molecular Biology, Computational Theory and Mathematics, Plant Science, Biomedical Engineering and Materials Chemistry, having authored 54 papers that have together received 344 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), Protein Structure and Dynamics (9 papers), Machine Learning in Bioinformatics (7 papers), Bioinformatics and Genomic Networks (6 papers), RNA and protein synthesis mechanisms (4 papers), Machine Learning in Materials Science (3 papers), Gut microbiota and health (2 papers) and Customer Service Quality and Loyalty (2 papers). The work is most often cited by research in Computational Theory and Mathematics (93 citations), Molecular Biology (144 citations), Obstetrics and Gynecology (10 citations), Transplantation (3 citations) and Cancer Research (13 citations). Xiaoli Lin has collaborated with scholars based in China, Japan and Hong Kong. Frequent co-authors include Xiaolong Zhang, Xin Xu, Qing Ye, Desmond Lam, Qianqian Huang, Nan Mu, Shuo Zhang, Shuai Xu, Yifan Huang and William S.B. Yeung. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Frontiers in Immunology, BMC Bioinformatics, International Journal of Biological Macromolecules and Frontiers in Plant Science.

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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