Nicole M. Chapman
- Immunology top 1%
- Immune Cell Function and Interaction 31
- T-cell and B-cell Immunology 26
- Immunotherapy and Immune Responses 7
- Immune cells in cancer 5
- Cancer Research top 5%
- Oncology top 5%
- CAR-T cell therapy research 4
- Biological Psychiatry top 10%
- Molecular Biology top 10%
- PI3K/AKT/mTOR signaling in cancer 4
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- Diabetes and associated disorders 4
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- Cell Adhesion Molecules Research 3
- Cited by
- ImmunologyCancer ResearchOncology
- Partner nations
- United StatesAustraliaBelgium
In The Last Decade
Nicole M. Chapman
44 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Immunology 1.8k
- Cancer Research 537
- Oncology 750
- Biological Psychiatry 51
- Molecular Biology 1.1k
Countries citing papers authored by Nicole M. Chapman
This map shows the geographic impact of Nicole M. Chapman'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 Nicole M. Chapman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicole M. Chapman more than expected).
Fields of papers citing papers by Nicole M. Chapman
This network shows the impact of papers produced by Nicole M. Chapman. 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 Nicole M. Chapman. The network helps show where Nicole M. Chapman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nicole M. Chapman, 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 | VDAC2 loss elicits tumour destruction and inflammation for cancer therapybreakdown → | 2025 | 17 |
| 2 | 2025 | 1 | |
| 3 | 2025 | 5 | |
| 4 | 2024 | 13 | |
| 5 | SLC38A2 and glutamine signalling in cDC1s dictate anti-tumour immunitybreakdown → | 2023 | 154 |
| 6 | Lipid metabolism in T cell signaling and functionbreakdown → | 2022 | 172 |
| 7 | 2022 | 142 | |
| 8 | Lipid signalling enforces functional specialization of Treg cells in tumoursbreakdown → | 2021 | 286 |
| 9 | 2021 | 95 | |
| 10 | 2021 | 29 | |
| 11 | 2020 | 60 | |
| 12 | 2020 | 158 | |
| 13 | 2020 | 39 | |
| 14 | 2019 | 91 | |
| 15 | Helper T cell differentiationbreakdown → | 2019 | 353 |
| 16 | 2018 | 132 | |
| 17 | 2017 | 17 | |
| 18 | 2016 | 37 | |
| 19 | 2016 | 18 | |
| 20 | 2012 | 20 |
About Nicole M. Chapman
Nicole M. Chapman is a scholar working on Immunology, Immunology and Allergy and General Social Sciences, having authored 45 papers that have together received 3.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (31 papers), T-cell and B-cell Immunology (26 papers), Immunotherapy and Immune Responses (7 papers), Immune cells in cancer (5 papers), CAR-T cell therapy research (4 papers), PI3K/AKT/mTOR signaling in cancer (4 papers), Diabetes and associated disorders (4 papers) and Cell Adhesion Molecules Research (3 papers). The work is most often cited by research in Immunology (1.8k citations), Cancer Research (537 citations) and Oncology (750 citations). Nicole M. Chapman has collaborated with scholars based in United States, Australia and Belgium. Frequent co-authors include Hongbo Chi, Jordy Saravia, Mark Boothby, Seon Ah Lim, Yogesh Dhungana, Wei Su, Lingyun Long, Hao Shi, Jon C. D. Houtman and Peter Vogel. Their work appears in journals such as Nature, Cell and Nature Communications.
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.