Hu Meng

2.1k citations
69 papers · 1.5k · h-index 21

Impact in

Papers in

    • RNA and protein synthesis mechanisms 10
    • RNA modifications and cancer 4
    • Machine Learning in Bioinformatics 4
    • Inflammatory mediators and NSAID effects 9

Hu Meng

62 papers receiving 1.5k citations

Peers

Hu Meng
Comparison fields: 5 of 121
  • Cancer Research 240
  • Biomaterials 145
  • Molecular Biology 751
  • Neurology 54
  • Pharmacology 108
Replace Toshihiko Hayashi with:
Toshihiko Hayashi Japan
Karim Bordji France
Alessandra Fiorio Italy
Qibing Liu China
Jiao Wang China
Weimin Hou China
Hyun Min Kim South Korea
Quanwei Wang China
Shiming Liu China
Weiping Liu China
Hu Meng relative to Toshihiko Hayashi Japan Toshihiko Hayashi's profile →
Citations per field
00.5×
Toshihiko Hayashi · 1×
Citations per year

Countries citing papers authored by Hu Meng

Since Specialization
Citations

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

Fields of papers citing papers by Hu Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017174
2 2020134
3 2015106
4 201696
5 201674
6 201671
7 201565
8 201960
9 201544
10 201944
11 201541
12 202030
13 200930
14 201829
15 201926
16 200826
17 202326
18 201826
19 202224
20 201724

About Hu Meng

Hu Meng is a scholar working on Molecular Biology, Pharmacology, Genetics, Physiology and Immunology, having authored 69 papers that have together received 1.5k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (10 papers), Inflammatory mediators and NSAID effects (9 papers), Eicosanoids and Hypertension Pharmacology (6 papers), Alzheimer's disease research and treatments (5 papers), Cancer-related molecular mechanisms research (5 papers), RNA modifications and cancer (4 papers), Estrogen and related hormone effects (4 papers) and Machine Learning in Bioinformatics (4 papers). The work is most often cited by research in Cancer Research (240 citations), Biomaterials (145 citations), Molecular Biology (751 citations), Neurology (54 citations) and Pharmacology (108 citations). Hu Meng has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Luhua Lai, Xiaoling Gao, Qingxiang Song, Hongzhuan Chen, Xiao Gu, Huahua Song, Qinglong An, Weiwei Ming, Jialin Huang and Ming Chen. Their work appears in journals such as Genomics, Leukemia Research, Bioorganic & Medicinal Chemistry Letters, Neuroscience Bulletin and Journal of Lipid Research.

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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