John W. Hickey
- Molecular Biology top 10%
- Immunology top 5%
- Oncology top 5%
- Biomedical Engineering top 10%
- Biomaterials top 5%
- Co-authors
- Hai‐Quan MaoJonathan P. SchneckJohn‐Michael WillifordJosé Luís SantosGarry P. NolanYury GoltsevNikolay SamusikJulia Kennedy‐Darling
- Topics
- Immunotherapy and Immune Responses (13 papers)CAR-T cell therapy research (13 papers)Single-cell and spatial transcriptomics (7 papers)
- Cited by
- ImmunologyBiophysicsOncology
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
John W. Hickey
44 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 879
- Immunology 592
- Oncology 527
- Biomedical Engineering 460
- Biomaterials 221
Countries citing papers authored by John W. Hickey
This map shows the geographic impact of John W. Hickey'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 John W. Hickey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John W. Hickey more than expected).
Fields of papers citing papers by John W. Hickey
This network shows the impact of papers produced by John W. Hickey. 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 John W. Hickey. The network helps show where John W. Hickey may publish in the future.
Co-authorship network of co-authors of John W. Hickey
This figure shows the co-authorship network connecting the top 25 collaborators of John W. Hickey. A scholar is included among the top collaborators of John W. Hickey 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 John W. Hickey. John W. Hickey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancerbreakdown → | 62 |
| 5 | 25 | |
| 6 | 5 | |
| 7 | 45 | |
| 8 | 13 | |
| 9 | 12 | |
| 10 | 44 | |
| 11 | 26 | |
| 12 | 14 | |
| 13 | 52 | |
| 14 | Identification of causal variants using one million individuals with whole–genome sequence information | 1 |
| 15 | 1 | |
| 16 | 9 | |
| 17 | 294 | |
| 18 | 13 | |
| 19 | nHow would different models of genetic variation affect genomic selection | 1 |
| 20 | Recursive Long Range Phasing and Long Haplotype Library Imputation: Building a Global Haplotype Library for Holstein cattle | 7 |
About John W. Hickey
John W. Hickey is a scholar working on Biophysics, Immunology and Oncology, having authored 48 papers that have together received 1.9k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (13 papers), CAR-T cell therapy research (13 papers) and Single-cell and spatial transcriptomics (7 papers). The work is most often cited by research in Immunology (592 citations), Biophysics (152 citations) and Oncology (527 citations). John W. Hickey has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Hai‐Quan Mao, Jonathan P. Schneck, John‐Michael Williford, José Luís Santos, Garry P. Nolan, Yury Goltsev, Nikolay Samusik, Julia Kennedy‐Darling, Christian M. Schürch and Sarah Black. Their work appears in journals such as Advanced Materials, Nature Communications and Nano Letters.
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.