Mengkun Zhang
- Molecular Biology top 10%
- Cell Biology top 2%
- Oncology top 5%
- Immunology top 5%
- Rheumatology top 5%
- Co-authors
- Jean‐Pierre PelletierJohn A. Di BattistaJohanne Martel‐PelletierYulan HeFrançois MineauDragan JovanovićJessica J. HuckMark Manfredi
- Topics
- Microtubule and mitosis dynamics (14 papers)Cancer-related Molecular Pathways (7 papers)Inflammatory mediators and NSAID effects (4 papers)
- Cited by
- Cell BiologyImmunologyOncology
- Partner nations
- United StatesCanadaJapan
In The Last Decade
Mengkun Zhang
23 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 728
- Cell Biology 681
- Oncology 677
- Immunology 524
- Rheumatology 172
Countries citing papers authored by Mengkun Zhang
This map shows the geographic impact of Mengkun Zhang'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 Mengkun Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mengkun Zhang more than expected).
Fields of papers citing papers by Mengkun Zhang
This network shows the impact of papers produced by Mengkun Zhang. 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 Mengkun Zhang. The network helps show where Mengkun Zhang may publish in the future.
Co-authorship network of co-authors of Mengkun Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Mengkun Zhang. A scholar is included among the top collaborators of Mengkun Zhang 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 Mengkun Zhang. Mengkun Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 83 | |
| 3 | 27 | |
| 4 | 16 | |
| 5 | 4 | |
| 6 | 19 | |
| 7 | 1 | |
| 8 | 44 | |
| 9 | 242 | |
| 10 | 103 | |
| 11 | MLN8237: an orally active small molecule inhibitor of Aurora A kinase in phase I clinical trials | 14 |
| 12 | 6 | |
| 13 | Preclinical PK/PD/Efficacy relationship of MLN8054, a small molecule Aurora A kinase inhibitor | 2 |
| 14 | 334 | |
| 15 | Preclinical antitumor activity with MLN8054, a small molecule Aurora A kinase inhibitor | 8 |
| 16 | MLN8054, an orally active Aurora A kinase small molecule inhibitor in phase I clinical trials | 5 |
| 17 | 15 | |
| 18 | 23 | |
| 19 | IL-17 Stimulates the Production and Expression of Proinflammatory Cytokines, IL-β and TNF-α, by Human Macrophagesbreakdown → | 774 |
| 20 | 75 |
About Mengkun Zhang
Mengkun Zhang is a scholar working on Cell Biology, Oncology and Pharmacology, having authored 24 papers that have together received 1.8k indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (14 papers), Cancer-related Molecular Pathways (7 papers) and Inflammatory mediators and NSAID effects (4 papers). The work is most often cited by research in Cell Biology (681 citations), Immunology (524 citations) and Oncology (677 citations). Mengkun Zhang has collaborated with scholars based in United States, Canada and Japan. Frequent co-authors include Jean‐Pierre Pelletier, John A. Di Battista, Johanne Martel‐Pelletier, Yulan He, François Mineau, Dragan Jovanović, Jessica J. Huck, Mark Manfredi, Kara M. Hoar and Jeffrey Ecsedy. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Blood.
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.