John P. Barton

2.2k total citations
47 papers, 1.2k citations indexed

About

John P. Barton is a scholar working on Virology, Molecular Biology and Genetics. According to data from OpenAlex, John P. Barton has authored 47 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Virology, 17 papers in Molecular Biology and 16 papers in Genetics. Recurrent topics in John P. Barton's work include HIV Research and Treatment (18 papers), Evolution and Genetic Dynamics (16 papers) and Protein Structure and Dynamics (5 papers). John P. Barton is often cited by papers focused on HIV Research and Treatment (18 papers), Evolution and Genetic Dynamics (16 papers) and Protein Structure and Dynamics (5 papers). John P. Barton collaborates with scholars based in United States, Hong Kong and France. John P. Barton's co-authors include Arup K. Chakraborty, Simona Cocco, Matthew R. McKay, Mehran Kardar, Bruce D. Walker, Raymond H. Y. Louie, Andrew L. Ferguson, Scott A. Schaub, Thomas Butler and Alice Coucke and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

John P. Barton

45 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John P. Barton United States 20 477 452 327 273 179 47 1.2k
F.K.M. Schur Austria 19 922 1.9× 554 1.2× 420 1.3× 164 0.6× 145 0.8× 36 2.0k
Jakub Chojnacki Germany 15 318 0.7× 321 0.7× 174 0.5× 82 0.3× 130 0.7× 26 831
Xin Meng China 18 638 1.3× 424 0.9× 292 0.9× 68 0.2× 69 0.4× 61 1.8k
Juan R. Perilla United States 27 1.5k 3.1× 848 1.9× 651 2.0× 214 0.8× 177 1.0× 63 2.8k
Jiying Ning United States 14 643 1.3× 525 1.2× 356 1.1× 83 0.3× 103 0.6× 19 1.2k
Marco J. Morelli Italy 28 1.5k 3.2× 390 0.9× 307 0.9× 340 1.2× 349 1.9× 64 2.6k
James B. Munro United States 24 1.4k 2.9× 760 1.7× 608 1.9× 320 1.2× 378 2.1× 53 2.5k
Jason Gorman United States 22 1.3k 2.8× 867 1.9× 420 1.3× 222 0.8× 440 2.5× 60 2.2k
Kedar Narayan United States 24 537 1.1× 218 0.5× 148 0.5× 134 0.5× 331 1.8× 51 1.5k
Marko Lampe Germany 20 972 2.0× 284 0.6× 223 0.7× 106 0.4× 152 0.8× 38 1.8k

Countries citing papers authored by John P. Barton

Since Specialization
Citations

This map shows the geographic impact of John P. Barton'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 P. Barton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John P. Barton more than expected).

Fields of papers citing papers by John P. Barton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John P. Barton. 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 P. Barton. The network helps show where John P. Barton may publish in the future.

Co-authorship network of co-authors of John P. Barton

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

All Works

20 of 20 papers shown
1.
2.
Quadeer, Ahmed Abdul, et al.. (2025). Inferring effects of mutations on SARS-CoV-2 transmission from genomic surveillance data. Nature Communications. 16(1). 441–441. 9 indexed citations
3.
Barton, John P., et al.. (2025). Efficient epistasis inference via higher-order covariance matrix factorization. Genetics. 230(4). 1 indexed citations
4.
Barton, John P., et al.. (2024). Correlated Allele Frequency Changes Reveal Clonal Structure and Selection in Temporal Genetic Data. Molecular Biology and Evolution. 41(4). 2 indexed citations
5.
Mace, Emily M., et al.. (2023). An inference model gives insights into innate immune adaptation and repertoire diversity. Proceedings of the National Academy of Sciences. 120(38). e2305859120–e2305859120. 3 indexed citations
6.
Barton, John P., et al.. (2023). Estimating linkage disequilibrium and selection from allele frequency trajectories. Genetics. 223(3). 7 indexed citations
7.
Barton, John P., et al.. (2023). Bézier interpolation improves the inference of dynamical models from data. Physical review. E. 107(2). 24116–24116. 6 indexed citations
8.
Murakowski, Dariusz K., John P. Barton, Lauren Peter, et al.. (2021). Adenovirus-vectored vaccine containing multidimensionally conserved parts of the HIV proteome is immunogenic in rhesus macaques. Proceedings of the National Academy of Sciences. 118(5). 4 indexed citations
9.
Dai, Lei, John P. Barton, Yushen Du, et al.. (2020). Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease. PLoS Genetics. 16(10). e1009009–e1009009. 22 indexed citations
10.
Sohail, Muhammad Saqib, Raymond H. Y. Louie, Matthew R. McKay, & John P. Barton. (2020). MPL resolves genetic linkage in fitness inference from complex evolutionary histories. Nature Biotechnology. 39(4). 472–479. 25 indexed citations
11.
Ahmed, Syed Faraz, Ahmed Abdul Quadeer, John P. Barton, & Matthew R. McKay. (2020). Cross-serotypically conserved epitope recommendations for a universal T cell-based dengue vaccine. PLoS neglected tropical diseases. 14(9). e0008676–e0008676. 16 indexed citations
12.
Coucke, Alice, et al.. (2020). Inference of compressed Potts graphical models. Physical review. E. 101(1). 12309–12309. 14 indexed citations
13.
Vibholm, Line K., Julio C. C. Lorenzi, Joy A. Pai, et al.. (2019). Characterization of Intact Proviruses in Blood and Lymph Node from HIV-Infected Individuals Undergoing Analytical Treatment Interruption. Journal of Virology. 93(8). 51 indexed citations
14.
Ovchinnikov, Victor, et al.. (2018). Role of framework mutations and antibody flexibility in the evolution of broadly neutralizing antibodies. eLife. 7. 64 indexed citations
15.
Louie, Raymond H. Y., et al.. (2018). Fitness landscape of the human immunodeficiency virus envelope protein that is targeted by antibodies. Proceedings of the National Academy of Sciences. 115(4). E564–E573. 73 indexed citations
16.
Bandaru, Pradeep, Neel H. Shah, Moitrayee Bhattacharyya, et al.. (2017). Deconstruction of the Ras switching cycle through saturation mutagenesis. eLife. 6. 70 indexed citations
17.
Barton, John P., et al.. (2016). ACE: adaptive cluster expansion for maximum entropy graphical model inference. Bioinformatics. 32(20). 3089–3097. 54 indexed citations
18.
Barton, John P., Nilu Goonetilleke, Thomas Butler, et al.. (2016). Relative rate and location of intra-host HIV evolution to evade cellular immunity are predictable. Nature Communications. 7(1). 11660–11660. 73 indexed citations
19.
Lorenzi, Julio C. C., Yehuda Z. Cohen, Lillian B. Cohn, et al.. (2016). Paired quantitative and qualitative assessment of the replication-competent HIV-1 reservoir and comparison with integrated proviral DNA. Proceedings of the National Academy of Sciences. 113(49). E7908–E7916. 128 indexed citations
20.
Barton, John P., Mehran Kardar, & Arup K. Chakraborty. (2015). Scaling laws describe memories of host-pathogen riposte in the HIV population. DSpace@MIT (Massachusetts Institute of Technology). 3 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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