John Haliburton
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Single-cell and spatial transcriptomics
- Microbial Metabolic Engineering and Bioproduction
- Plant biochemistry and biosynthesis
- CRISPR and Genetic Engineering
Papers in
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- Single-cell and spatial transcriptomics 5
- Gene Regulatory Network Analysis 2
- Microbial Metabolic Engineering and Bioproduction 2
- Plant biochemistry and biosynthesis 1
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- Innovative Microfluidic and Catalytic Techniques Innovation 4
- Biosensors and Analytical Detection 2
- Co-authors
- Adam R. Abate (6 shared papers)Samuel Kim (3 shared papers)Zev J. Gartner (2 shared papers)Payam Shahi (1 shared paper)Freeman Lan (1 shared paper)Gregory D. Friedland (1 shared paper)Taek Soon Lee (1 shared paper)Rossana Chan (1 shared paper)
- Journals
- Nature Communications (1 paper)Life Science Alliance (1 paper)Blood (1 paper)Scientific Reports (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United States
In The Last Decade
John Haliburton
10 papers receiving 600 citations
Peers
Comparison fields: 5 of 75
- Biophysics 46
- Molecular Biology 467
- Hematology 47
- Biomedical Engineering 187
- Cancer Research 46
Countries citing papers authored by John Haliburton
This map shows the geographic impact of John Haliburton'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 Haliburton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Haliburton more than expected).
Fields of papers citing papers by John Haliburton
This network shows the impact of papers produced by John Haliburton. 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 Haliburton. The network helps show where John Haliburton may publish in the future.
Co-authors
The 25 scholars most cited alongside John Haliburton, 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 | 2017 | 201 | |
| 2 | 2011 | 143 | |
| 3 | 2016 | 79 | |
| 4 | 2022 | 56 | |
| 5 | 2014 | 50 | |
| 6 | 2014 | 40 | |
| 7 | 2020 | 20 | |
| 8 | 2017 | 13 | |
| 9 | 2017 | 8 | |
| 10 | 2021 | 1 |
About John Haliburton
John Haliburton is a scholar working on Molecular Biology, Biomedical Engineering, Genetics, Immunology and Pharmacology, having authored 10 papers that have together received 611 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (4 papers), T-cell and B-cell Immunology (2 papers), Biosensors and Analytical Detection (2 papers), Gene Regulatory Network Analysis (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Acute Myeloid Leukemia Research (1 paper) and Plant biochemistry and biosynthesis (1 paper). The work is most often cited by research in Biophysics (46 citations), Molecular Biology (467 citations), Hematology (47 citations), Biomedical Engineering (187 citations) and Cancer Research (46 citations). John Haliburton has collaborated with scholars based in United States. Frequent co-authors include Adam R. Abate, Samuel Kim, Zev J. Gartner, Payam Shahi, Freeman Lan, Gregory D. Friedland, Taek Soon Lee, Rossana Chan, Jay D. Keasling and Christopher J. Petzold. Their work appears in journals such as Nature Communications, Life Science Alliance, Blood, Scientific Reports and Proceedings of the National Academy of Sciences.
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.