John Haliburton

1.0k total citations
10 papers, 574 citations indexed

About

John Haliburton is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, John Haliburton has authored 10 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Biomedical Engineering and 2 papers in Genetics. Recurrent topics in John Haliburton's work include Single-cell and spatial transcriptomics (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (4 papers) and Gene Regulatory Network Analysis (2 papers). John Haliburton is often cited by papers focused on Single-cell and spatial transcriptomics (5 papers), Innovative Microfluidic and Catalytic Techniques Innovation (4 papers) and Gene Regulatory Network Analysis (2 papers). John Haliburton collaborates with scholars based in United States. John Haliburton's co-authors include Adam R. Abate, Samuel Kim, Zev J. Gartner, Payam Shahi, Freeman Lan, Gregory D. Friedland, Jay D. Keasling, Christopher J. Petzold, Dylan Chivian and Tanveer S. Batth and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Blood.

In The Last Decade

John Haliburton

9 papers receiving 564 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
John Haliburton United States	9	445	184	56	50	47	10	574
Gaetano Orsini Italy	15	252 0.6×	55 0.3×	25 0.4×	22 0.4×	9 0.2×	22	469
Marius Müller Switzerland	9	502 1.1×	127 0.7×	19 0.3×	32 0.6×	22 0.5×	19	640
Arnaud Amzallag United States	11	359 0.8×	29 0.2×	23 0.4×	6 0.1×	7 0.1×	16	460
Ana Martínez‐Val Denmark	12	652 1.5×	44 0.2×	35 0.6×	3 0.1×	22 0.5×	22	846
Diane Tkach United States	11	384 0.9×	81 0.4×	58 1.0×	30 0.6×	2 0.0×	15	600
Benjamin C. Carter United States	10	487 1.1×	26 0.1×	55 1.0×	7 0.1×	12 0.3×	11	591
Rohit Gupte United States	7	229 0.5×	93 0.5×	24 0.4×	30 0.6×	35 0.7×	11	331
Stefan K. Maier Germany	6	295 0.7×	22 0.1×	16 0.3×	18 0.4×	13 0.3×	8	488
Joseph A. Wawrzyniak United States	9	351 0.8×	26 0.1×	32 0.6×	34 0.7×	4 0.1×	9	494
Yan Tong China	7	510 1.1×	21 0.1×	24 0.4×	10 0.2×	5 0.1×	17	733

Countries citing papers authored by John Haliburton

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of John Haliburton

This figure shows the co-authorship network connecting the top 25 collaborators of John Haliburton. A scholar is included among the top collaborators of John Haliburton 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 Haliburton. John Haliburton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Liu, Jonathan, Venkata N. P. Vemuri, Ashley Byrne, et al.. (2022). Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing. Life Science Alliance. 6(1). e202201701–e202201701. 51 indexed citations

Kim, Samuel, John Haliburton, Zev J. Gartner, & Adam R. Abate. (2021). Single-Cell Protein Profiling by Microdroplet Barcoding and Next-Generation Sequencing. Methods in molecular biology. 2386. 101–111. 1 indexed citations

Chen, Sisi, Jong‐Hwan Park, Emeric Charles, et al.. (2020). Dissecting heterogeneous cell populations across drug and disease conditions with PopAlign. Proceedings of the National Academy of Sciences. 117(46). 28784–28794. 19 indexed citations

Shahi, Payam, Samuel Kim, John Haliburton, Zev J. Gartner, & Adam R. Abate. (2017). Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding. Scientific Reports. 7(1). 44447–44447. 192 indexed citations

Haliburton, John, Wenjun Shao, Adam M. Deutschbauer, Adam P. Arkin, & Adam R. Abate. (2017). Genetic interaction mapping with microfluidic-based single cell sequencing. PLoS ONE. 12(2). e0171302–e0171302. 8 indexed citations

Haliburton, John, Samuel Kim, Iain C. Clark, et al.. (2017). Efficient extraction of oil from droplet microfluidic emulsions. Biomicrofluidics. 11(3). 34111–34111. 13 indexed citations

Lan, Freeman, et al.. (2016). Droplet barcoding for massively parallel single-molecule deep sequencing. Nature Communications. 7(1). 11784–11784. 74 indexed citations

Stieglitz, Elliot, Camille Troup, John Haliburton, et al.. (2014). Subclonal mutations in SETBP1 confer a poor prognosis in juvenile myelomonocytic leukemia. Blood. 125(3). 516–524. 48 indexed citations

Ji, Weiyue, Derrick Lee, Eric B. Wong, et al.. (2014). Specific Gene Repression by CRISPRi System Transferred through Bacterial Conjugation. ACS Synthetic Biology. 3(12). 929–931. 40 indexed citations

10.

Suzanne, Magali, Alyssa M. Redding‐Johanson, Gregory D. Friedland, et al.. (2011). Optimization of a heterologous mevalonate pathway through the use of variant HMG-CoA reductases. Metabolic Engineering. 13(5). 588–597. 128 indexed citations

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.

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