Menglong Li

4.2k citations
162 papers · 2.5k indexed · 1 hit paper · h-index 23
Topics
Machine Learning in Bioinformatics (52 papers)Protein Structure and Dynamics (33 papers)RNA and protein synthesis mechanisms (31 papers)
Partner nations
ChinaUnited StatesIsrael

In The Last Decade

Menglong Li

153 papers receiving 2.5k citations

Hit Papers

Using support vector machine combined with auto covarianc...20082026201420202008100200300400500

Peers

Menglong Li
Comparison fields: 5 of 136
  • Molecular Biology 2.1k
  • Computational Theory and Mathematics 457
  • Cancer Research 195
  • Materials Chemistry 127
  • Biomedical Engineering 105
Replace Jing Tang with:
Jing Tang China
G. Sitta Sittampalam United States
Peichen Pan China
Zhenqiang Su United States
Michaela Spitzer United Kingdom
Yifei Wang China
Lei Deng China
Shandar Ahmad Japan
Yijie Ding China
Menglong Li relative to Jing Tang China Jing Tang's profile →
Citations per field
00.5×10×16.3×
Jing Tang · 1×
Citations per year

Countries citing papers authored by Menglong Li

Since Specialization
Citations

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

Fields of papers citing papers by Menglong Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Menglong Li

This figure shows the co-authorship network connecting the top 25 collaborators of Menglong Li. A scholar is included among the top collaborators of Menglong Li 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 Menglong Li. Menglong Li 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
#WorkIndexed citations
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Complex network-based random forest algorithm for predicting the impact of amino acid mutation on protein stability
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18 34
19 32
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About Menglong Li

Menglong Li is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research, having authored 162 papers that have together received 2.5k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (52 papers), Protein Structure and Dynamics (33 papers) and RNA and protein synthesis mechanisms (31 papers). The work is most often cited by research in Molecular Biology (2.1k citations), Computational Theory and Mathematics (457 citations) and Cancer Research (195 citations). Menglong Li has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Yanzhi Guo, Lezheng Yu, Zhining Wen, Xuemei Pu, Yizhou Li, Jiesi Luo, Yuhong Zeng, Li V. Yang, Rong-quan Xiao and Runyu Jing. Their work appears in journals such as Nucleic Acids Research, PLoS ONE and The Journal of Physical Chemistry B.

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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