Maiying Kong
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- Alcohol Consumption and Health Effects 15
- Biological Psychiatry top 5%
- Cancer Research top 5%
- Statistics and Probability top 2%
- Statistical Methods in Clinical Trials 10
- Advanced Causal Inference Techniques 8
- Statistical Methods and Bayesian Inference 8
- Statistical Methods and Inference 7
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- Liver Disease Diagnosis and Treatment 13
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- Computational Drug Discovery Methods 7
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- Optimal Experimental Design Methods 6
- Co-authors
- J. Jack LeeCraig J. McClainMaxwell BoakyeWenke FengLu CaiLeila GobejishviliBeatrice UgiliwenezaShirish Barve
- Journals
- Nature Communications (2 papers)Journal of Clinical Oncology (1 paper)SHILAP Revista de lepidopterología (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Maiying Kong
119 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Pathology and Forensic Medicine 587
- Biological Psychiatry 74
- Cancer Research 376
- Statistics and Probability 195
- Applied Microbiology and Biotechnology 38
Countries citing papers authored by Maiying Kong
This map shows the geographic impact of Maiying Kong'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 Maiying Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maiying Kong more than expected).
Fields of papers citing papers by Maiying Kong
This network shows the impact of papers produced by Maiying Kong. 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 Maiying Kong. The network helps show where Maiying Kong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Maiying Kong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | Plant-nanoparticles enhance anti-PD-L1 efficacy by shaping human commensal microbiota metabolitesbreakdown → | 2025 | 28 |
| 3 | 2024 | 0 | |
| 4 | 2024 | 9 | |
| 5 | 2024 | 16 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 40 | |
| 9 | 2022 | 5 | |
| 10 | 2021 | 8 | |
| 11 | 2021 | 12 | |
| 12 | 2020 | 0 | |
| 13 | 2020 | 3 | |
| 14 | 2020 | 8 | |
| 15 | 2018 | 15 | |
| 16 | 2017 | 11 | |
| 17 | 2016 | 38 | |
| 18 | 2012 | 23 | |
| 19 | 2011 | 4 | |
| 20 | 2006 | 49 |
About Maiying Kong
Maiying Kong is a scholar working on Statistics and Probability, Applied Microbiology and Biotechnology and Pathology and Forensic Medicine, having authored 128 papers that have together received 3.2k indexed citations. Recurring topics across this work include Alcohol Consumption and Health Effects (15 papers), Liver Disease Diagnosis and Treatment (13 papers), Statistical Methods in Clinical Trials (10 papers), Advanced Causal Inference Techniques (8 papers), Statistical Methods and Bayesian Inference (8 papers), Computational Drug Discovery Methods (7 papers), Statistical Methods and Inference (7 papers) and Optimal Experimental Design Methods (6 papers). The work is most often cited by research in Pathology and Forensic Medicine (587 citations), Biological Psychiatry (74 citations) and Cancer Research (376 citations). Maiying Kong has collaborated with scholars based in United States, China and Australia. Frequent co-authors include J. Jack Lee, Craig J. McClain, Maxwell Boakye, Wenke Feng, Lu Cai, Leila Gobejishvili, Beatrice Ugiliweneza, Shirish Barve, Swati Joshi‐Barve and Irina Kirpich. Their work appears in journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.