Jun Meng
Impact in
- Endocrinology top 1%
- Plant and Fungal Interactions Research
- Plant Science top 1%
- Plant Molecular Biology Research
- Plant-Microbe Interactions and Immunity
- Plant Disease Resistance and Genetics
- Plant Virus Research Studies
- Plant Stress Responses and Tolerance
Papers in
-
- Genomics and Phylogenetic Studies 12
- RNA and protein synthesis mechanisms 10
- Machine Learning in Bioinformatics 9
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- Plant Molecular Biology Research 24
- Plant-Microbe Interactions and Immunity 19
- Plant Disease Resistance and Genetics 13
- Co-authors
- Yushi Luan (54 shared papers)Jun Cui (24 shared papers)Ning Jiang (11 shared papers)Xinxin Hou (8 shared papers)Xiaoxu Zhou (8 shared papers)Guanglei Yang (6 shared papers)Ning Jiang (2 shared papers)Weiwei Liu (3 shared papers)
- Journals
- Gene (4 papers)The Plant Journal (4 papers)Phytopathology (4 papers)BMC Bioinformatics (4 papers)Mathematical Biosciences (3 papers)
- Partner nations
- ChinaUnited StatesKenya
In The Last Decade
Jun Meng
97 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 117
- Endocrinology 452
- Plant Science 1.6k
- Cancer Research 452
- Horticulture 18
- Molecular Biology 1.1k
Countries citing papers authored by Jun Meng
This map shows the geographic impact of Jun 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 Jun Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Meng more than expected).
Fields of papers citing papers by Jun Meng
This network shows the impact of papers produced by Jun 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 Jun Meng. The network helps show where Jun Meng may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Meng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 216 | |
| 2 | 2019 | 149 | |
| 3 | 2018 | 137 | |
| 4 | 2018 | 113 | |
| 5 | 2018 | 107 | |
| 6 | 2020 | 87 | |
| 7 | 2017 | 86 | |
| 8 | 2017 | 80 | |
| 9 | 2019 | 77 | |
| 10 | 2019 | 74 | |
| 11 | 2020 | 71 | |
| 12 | 2015 | 70 | |
| 13 | 2017 | 63 | |
| 14 | 2022 | 57 | |
| 15 | 2020 | 53 | |
| 16 | 2019 | 47 | |
| 17 | 2020 | 43 | |
| 18 | 2018 | 37 | |
| 19 | 2017 | 34 | |
| 20 | 2010 | 34 |
About Jun Meng
Jun Meng is a scholar working on Molecular Biology, Plant Science, Cancer Research, Endocrinology and Computational Theory and Mathematics, having authored 103 papers that have together received 2.5k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (25 papers), Plant Molecular Biology Research (24 papers), Plant-Microbe Interactions and Immunity (19 papers), Plant and Fungal Interactions Research (13 papers), Plant Disease Resistance and Genetics (13 papers), Genomics and Phylogenetic Studies (12 papers), RNA and protein synthesis mechanisms (10 papers) and Machine Learning in Bioinformatics (9 papers). The work is most often cited by research in Endocrinology (452 citations), Plant Science (1.6k citations), Cancer Research (452 citations), Horticulture (18 citations) and Molecular Biology (1.1k citations). Jun Meng has collaborated with scholars based in China, United States and Kenya. Frequent co-authors include Yushi Luan, Jun Cui, Ning Jiang, Xinxin Hou, Xiaoxu Zhou, Guanglei Yang, Ning Jiang, Weiwei Liu, Qiang Kang and Yuhui Hong. Their work appears in journals such as Gene, The Plant Journal, Phytopathology, BMC Bioinformatics and Mathematical Biosciences.
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.