Maxim Markovic
Impact in
- Immunology top 2%
- Immune cells in cancer
- Phagocytosis and Immune Regulation
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Galectins and Cancer Biology
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers
Papers in
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- Phagocytosis and Immune Regulation 4
- Immune Cell Function and Interaction 3
- T-cell and B-cell Immunology 2
- Immune cells in cancer 2
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- Single-cell and spatial transcriptomics 2
- Advanced biosensing and bioanalysis techniques 1
- Co-authors
- Irving L. Weissman (4 shared papers)Amira Barkal (2 shared papers)Layla J. Barkal (2 shared papers)Mark Kowarsky (1 shared paper)Oliver Dorigo (1 shared paper)Jason Hatakeyama (1 shared paper)Venkatesh Krishnan (1 shared paper)Balyn W. Zaro (1 shared paper)
- Journals
- Nature Communications (2 papers)Nature Immunology (1 paper)Nature (1 paper)Frontiers in Immunology (1 paper)Cancer Cell (1 paper)
- Partner nations
- United StatesIndiaTaiwan
In The Last Decade
Maxim Markovic
7 papers receiving 1.6k citations
Maxim Markovic's Hit Papers
Peers
Comparison fields: 5 of 80
- Immunology 1.2k
- Oncology 482
- Cancer Research 154
- Molecular Biology 558
- Physiology 29
Countries citing papers authored by Maxim Markovic
This map shows the geographic impact of Maxim Markovic'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 Maxim Markovic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxim Markovic more than expected).
Fields of papers citing papers by Maxim Markovic
This network shows the impact of papers produced by Maxim Markovic. 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 Maxim Markovic. The network helps show where Maxim Markovic may publish in the future.
Co-authors
The 25 scholars most cited alongside Maxim Markovic, 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 | CD24 signalling through macrophage Siglec-10 is a target for cancer immunotherapy Hit paper breakdown → | 2019 | 956 |
| 2 | Engagement of MHC class I by the inhibitory receptor LILRB1 suppresses macrophages and is a target of cancer immunotherapy Hit paper breakdown → | 2017 | 428 |
| 3 | 2018 | 129 | |
| 4 | 2019 | 41 | |
| 5 | 2021 | 29 | |
| 6 | 2022 | 18 | |
| 7 | 2021 | 2 |
About Maxim Markovic
Maxim Markovic is a scholar working on Immunology, Molecular Biology, Oncology, Cancer Research and Media Technology, having authored 7 papers that have together received 1.6k indexed citations. Recurring topics across this work include Phagocytosis and Immune Regulation (4 papers), Immune Cell Function and Interaction (3 papers), Cancer Genomics and Diagnostics (2 papers), Single-cell and spatial transcriptomics (2 papers), T-cell and B-cell Immunology (2 papers), Lung Cancer Research Studies (2 papers), Immune cells in cancer (2 papers) and Advanced biosensing and bioanalysis techniques (1 paper). The work is most often cited by research in Immunology (1.2k citations), Oncology (482 citations), Cancer Research (154 citations), Molecular Biology (558 citations) and Physiology (29 citations). Maxim Markovic has collaborated with scholars based in United States, India and Taiwan. Frequent co-authors include Irving L. Weissman, Amira Barkal, Layla J. Barkal, Mark Kowarsky, Oliver Dorigo, Jason Hatakeyama, Venkatesh Krishnan, Balyn W. Zaro, Rachel Brewer and Kevin S. Kao. Their work appears in journals such as Nature Communications, Nature Immunology, Nature, Frontiers in Immunology and Cancer Cell.
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.