Allon Wagner

3.6k total citations · 2 hit papers
24 papers, 1.7k citations indexed

About

Allon Wagner is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Allon Wagner has authored 24 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Immunology and 3 papers in Cancer Research. Recurrent topics in Allon Wagner's work include Single-cell and spatial transcriptomics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Microbial Metabolic Engineering and Bioproduction (6 papers). Allon Wagner is often cited by papers focused on Single-cell and spatial transcriptomics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Microbial Metabolic Engineering and Bioproduction (6 papers). Allon Wagner collaborates with scholars based in United States, Israel and United Kingdom. Allon Wagner's co-authors include Nir Yosef, Aviv Regev, Eytan Ruppin, Davide Risso, John Ngai, Michael B. Cole, Elizabeth Purdom, Sandrine Dudoit, Rolf Bjerkvig and Susan C. Barnett and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Clinical Investigation.

In The Last Decade

Allon Wagner

22 papers receiving 1.6k citations

Hit Papers

Glutamine synthetase activity fuels nucleotide biosynthes... 2015 2026 2018 2022 2015 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Allon Wagner United States 14 1.1k 462 263 139 134 24 1.7k
Liang Hong United States 28 1.8k 1.7× 127 0.3× 190 0.7× 70 0.5× 200 1.5× 106 2.6k
Lauren M. Saunders United States 18 984 0.9× 134 0.3× 111 0.4× 121 0.9× 57 0.4× 27 1.5k
Kristina Warton Australia 15 1.1k 1.0× 480 1.0× 107 0.4× 71 0.5× 266 2.0× 33 1.6k
Serena J. Silver United States 12 1.5k 1.4× 215 0.5× 158 0.6× 204 1.5× 243 1.8× 25 1.9k
Gregory M. Findlay United States 12 1.6k 1.5× 412 0.9× 133 0.5× 106 0.8× 109 0.8× 16 2.1k
Angus Harding Australia 19 1.8k 1.7× 240 0.5× 270 1.0× 67 0.5× 402 3.0× 23 2.4k
Thomas P. Stauffer Switzerland 11 1.7k 1.5× 64 0.1× 188 0.7× 72 0.5× 73 0.5× 17 2.2k
Irene Weibrecht Sweden 11 1.0k 0.9× 115 0.2× 149 0.6× 54 0.4× 161 1.2× 15 1.3k
Charles Vaske United States 17 1.1k 1.0× 421 0.9× 129 0.5× 46 0.3× 318 2.4× 39 1.6k
Zhengyan Kan United States 15 3.1k 2.9× 593 1.3× 572 2.2× 55 0.4× 612 4.6× 28 3.9k

Countries citing papers authored by Allon Wagner

Since Specialization
Citations

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

Fields of papers citing papers by Allon Wagner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Allon Wagner. 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 Allon Wagner. The network helps show where Allon Wagner may publish in the future.

Co-authorship network of co-authors of Allon Wagner

This figure shows the co-authorship network connecting the top 25 collaborators of Allon Wagner. A scholar is included among the top collaborators of Allon Wagner 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 Allon Wagner. Allon Wagner 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.
Zheng, Rongbin, Yang Zhang, Tadataka Tsuji, et al.. (2025). MEBOCOST maps metabolite-mediated intercellular communications using single-cell RNA-seq. Nucleic Acids Research. 53(12). 5 indexed citations
2.
Wang, Chao, Allon Wagner, Johannes Fessler, et al.. (2025). The glycolytic reaction PGAM restrains Th17 pathogenicity and Th17-dependent autoimmunity. Cell Reports. 44(6). 115799–115799.
3.
Courau, Tristan, Arpita Desai, Allon Wagner, Alexis J. Combes, & Matthew F. Krummel. (2025). The coming era of nudge drugs for cancer. Cancer Cell. 43(11). 1973–1979.
4.
Lopez, Romain, Baoguo Li, Hadas Keren‐Shaul, et al.. (2022). DestVI identifies continuums of cell types in spatial transcriptomics data. Nature Biotechnology. 40(9). 1360–1369. 118 indexed citations
5.
Purohit, Vinee, Allon Wagner, Nir Yosef, & Vijay K. Kuchroo. (2022). Systems-based approaches to study immunometabolism. Cellular and Molecular Immunology. 19(3). 409–420. 36 indexed citations
6.
Wagner, Allon, et al.. (2020). Is There a Faction in This List?. Lirias (KU Leuven). 4(2). 347–389. 2 indexed citations
7.
Wagner, Allon, et al.. (2020). Oleic acid restores suppressive defects in tissue-resident FOXP3 Tregs from patients with multiple sclerosis. Journal of Clinical Investigation. 131(2). 69 indexed citations
8.
Sungnak, Waradon, Allon Wagner, Monika S. Kowalczyk, et al.. (2020). T Follicular Regulatory Cell–Derived Fibrinogen-like Protein 2 Regulates Production of Autoantibodies and Induction of Systemic Autoimmunity. The Journal of Immunology. 205(12). 3247–3262. 18 indexed citations
9.
Cole, Michael B., Davide Risso, Allon Wagner, et al.. (2019). Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq. Cell Systems. 8(4). 315–328.e8. 97 indexed citations
10.
Fletcher, Russell B., Diya Das, Kelly Street, et al.. (2017). Deconstructing Olfactory Stem Cell Trajectories at Single-Cell Resolution. Cell stem cell. 20(6). 817–830.e8. 144 indexed citations
11.
Das, Diya, Kelly Street, Ariane Baudhuin, et al.. (2017). Injury Activates Transient Olfactory Stem Cell States with Diverse Lineage Capacities. Cell stem cell. 21(6). 775–790.e9. 66 indexed citations
12.
Mokryn, Osnat, Allon Wagner, Marcel Blattner, Eytan Ruppin, & Yuval Shavitt. (2016). The Role of Temporal Trends in Growing Networks. PLoS ONE. 11(8). e0156505–e0156505. 11 indexed citations
13.
Auslander, Noam, Allon Wagner, Matthew Oberhardt, & Eytan Ruppin. (2016). Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction. PLoS Computational Biology. 12(9). e1005125–e1005125. 7 indexed citations
14.
Wagner, Allon, Aviv Regev, & Nir Yosef. (2016). Revealing the vectors of cellular identity with single-cell genomics. Nature Biotechnology. 34(11). 1145–1160. 401 indexed citations breakdown →
15.
Mazza, Arnon, Allon Wagner, Eytan Ruppin, & Roded Sharan. (2016). Functional Alignment of Metabolic Networks. Journal of Computational Biology. 23(5). 390–399. 3 indexed citations
16.
Tardito, Saverio, Anaïs Oudin, Shafiq U. Ahmed, et al.. (2015). Glutamine synthetase activity fuels nucleotide biosynthesis and supports growth of glutamine-restricted glioblastoma. Nature Cell Biology. 17(12). 1556–1568. 426 indexed citations breakdown →
17.
Wagner, Allon, Noa Cohen, Thomas Kelder, et al.. (2015). Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia. Molecular Systems Biology. 11(3). 791–791. 33 indexed citations
18.
Langgut, Dafna, Frank Neumann, Mordechai Stein, et al.. (2014). Dead Sea pollen record and history of human activity in the Judean Highlands (Israel) from the Intermediate Bronze into the Iron Ages (∼2500–500 BCE). Palynology. 38(2). 280–302. 77 indexed citations
19.
Zarecki, Raphy, Matthew Oberhardt, Keren Yizhak, et al.. (2014). Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms. PLoS ONE. 9(5). e98372–e98372. 8 indexed citations
20.
Wagner, Allon, Raphy Zarecki, Leah Reshef, et al.. (2013). Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious. Proceedings of the National Academy of Sciences. 110(47). 19166–19171. 18 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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