Tailong Lei

1.2k citations
22 papers · 933 · h-index 14

Impact in

Papers in

Tailong Lei

21 papers receiving 929 citations

Peers

Tailong Lei
Comparison fields: 5 of 124
  • Computational Theory and Mathematics 486
  • Molecular Medicine 73
  • Pharmacology 69
  • Molecular Biology 430
  • Pharmacology 77
Replace Prabha Garg with:
Prabha Garg India
George Nicola United States
Sarah Naomi Bolz Germany
Cecilia Bossa Italy
Jayaraman Muthukumaran India
Jonathan Cheong United States
Max K. Leong Taiwan
Ali Ryan United Kingdom
Rafael Gozalbes Spain
Yiqun Chang China
Tailong Lei relative to Prabha Garg India Prabha Garg's profile →
Citations per field
00.5×2.5×
Prabha Garg · 1×
Citations per year

Countries citing papers authored by Tailong Lei

Since Specialization
Citations

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

Fields of papers citing papers by Tailong Lei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016137
2 2020134
3 2018103
4 2019101
5 201876
6 201769
7 201764
8 202062
9 201839
10 201828
11 201719
12 202219
13 202217
14 202413
15 202313
16 201912
17 20249
18 20239
19 20235
20 20243

About Tailong Lei

Tailong Lei is a scholar working on Molecular Biology, Computational Theory and Mathematics, Molecular Medicine, Infectious Diseases and Plant Science, having authored 22 papers that have together received 933 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Antibiotic Resistance in Bacteria (8 papers), Bacterial biofilms and quorum sensing (3 papers), Protein Structure and Dynamics (3 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Analytical Methods in Pharmaceuticals (2 papers), Machine Learning in Materials Science (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (486 citations), Molecular Medicine (73 citations), Pharmacology (69 citations), Molecular Biology (430 citations) and Pharmacology (77 citations). Tailong Lei has collaborated with scholars based in China, Macao and Germany. Frequent co-authors include Tingjun Hou, Zhe Wang, Youyong Li, Dan Li, Huiyong Sun, Dongsheng Cao, Yu Kang, Feng Zhu, Zhenhua Wu and Chao Shen. Their work appears in journals such as Emerging Microbes & Infections, Briefings in Bioinformatics, Molecular Pharmaceutics, Clinical Microbiology and Infection and Microbiology Spectrum.

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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