Alex Rubinsteyn

2.1k total citations
35 papers, 892 citations indexed

About

Alex Rubinsteyn is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Alex Rubinsteyn has authored 35 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 14 papers in Molecular Biology and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Alex Rubinsteyn's work include Immunotherapy and Immune Responses (15 papers), vaccines and immunoinformatics approaches (9 papers) and Monoclonal and Polyclonal Antibodies Research (8 papers). Alex Rubinsteyn is often cited by papers focused on Immunotherapy and Immune Responses (15 papers), vaccines and immunoinformatics approaches (9 papers) and Monoclonal and Polyclonal Antibodies Research (8 papers). Alex Rubinsteyn collaborates with scholars based in United States, Switzerland and China. Alex Rubinsteyn's co-authors include Timothy J. O’Donnell, Uri Laserson, Jeff Hammerbacher, Angelika B. Riemer, Maria Bonsack, Bülent Arman Aksoy, Julia Kodysh, Diana Miao, Tavi Nathanson and Eliezer M. Van Allen and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Bioinformatics.

In The Last Decade

Alex Rubinsteyn

30 papers receiving 866 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alex Rubinsteyn United States 9 529 492 288 240 77 35 892
Jeff Hammerbacher United States 15 538 1.0× 467 0.9× 455 1.6× 148 0.6× 97 1.3× 20 1.1k
Lars Rønn Olsen Denmark 22 676 1.3× 397 0.8× 282 1.0× 107 0.4× 167 2.2× 51 1.3k
Eckhart Kaempgen Germany 13 471 0.9× 591 1.2× 578 2.0× 71 0.3× 41 0.5× 21 1.0k
Arianna Palladini Italy 18 439 0.8× 287 0.6× 459 1.6× 169 0.7× 131 1.7× 48 964
Weiwen Yang China 19 492 0.9× 581 1.2× 697 2.4× 84 0.3× 126 1.6× 48 1.4k
Jason M. Link United States 15 377 0.7× 353 0.7× 117 0.4× 268 1.1× 57 0.7× 32 791
Kalet León Cuba 19 256 0.5× 526 1.1× 242 0.8× 137 0.6× 24 0.3× 59 887
Guang Sheng Ling Hong Kong 18 312 0.6× 754 1.5× 184 0.6× 61 0.3× 77 1.0× 31 1.5k
Sylvia Nagl United Kingdom 15 451 0.9× 166 0.3× 102 0.4× 151 0.6× 77 1.0× 34 981
Siranush Sarkizova United States 10 630 1.2× 674 1.4× 249 0.9× 150 0.6× 73 0.9× 16 1.0k

Countries citing papers authored by Alex Rubinsteyn

Since Specialization
Citations

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

Fields of papers citing papers by Alex Rubinsteyn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Rubinsteyn

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Rubinsteyn. A scholar is included among the top collaborators of Alex Rubinsteyn 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 Alex Rubinsteyn. Alex Rubinsteyn 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.
Gihawi, Abraham, Henry M. Wood, J. W. Clark, et al.. (2025). The landscape of microbial associations in human cancer. Science Translational Medicine. 17(814). eads6166–eads6166. 2 indexed citations
2.
Vincent, Benjamin G., et al.. (2025). Conditional generation of real antigen-specific T cell receptor sequences. Nature Machine Intelligence. 7(9). 1494–1509.
3.
Saxena, Mansi, Jonathan F. Anker, Julia Kodysh, et al.. (2025). Atezolizumab plus personalized neoantigen vaccination in urothelial cancer: a phase 1 trial. Nature Cancer. 6(6). 988–999. 2 indexed citations
4.
Bozkus, Cansu Cimen, Julia Kodysh, Simon K. Cheng, et al.. (2024). CTIM-10. PHASE 1 TRIAL OF PERSONALIZED NEOANTIGEN VACCINES IN COMBINATION WITH STANDARD CARE TO TREAT GLIOBLASTOMA. Neuro-Oncology. 26(Supplement_8). viii86–viii87. 1 indexed citations
5.
Lee, Jin Seok, et al.. (2023). ACE configurator for ELISpot: optimizing combinatorial design of pooled ELISpot assays with an epitope similarity model. Briefings in Bioinformatics. 25(1). 2 indexed citations
6.
Bortone, Dante S., et al.. (2023). LENS: Landscape of Effective Neoantigens Software. Bioinformatics. 39(6). 10 indexed citations
7.
Kodysh, Julia, Alex Rubinsteyn, Ana-Belén Blázquez, et al.. (2020). CTIM-17. PHASE I STUDY OF THE SAFETY AND IMMUNOGENICITY OF PERSONALIZED NEOANTIGEN VACCINES AND TUMOR TREATING FIELDS IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA. Neuro-Oncology. 22(Supplement_2). ii36–ii36. 4 indexed citations
8.
O’Donnell, Timothy J., Alex Rubinsteyn, & Uri Laserson. (2020). MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing. Cell Systems. 11(1). 42–48.e7. 225 indexed citations
9.
Boegel, Sebastian, John C. Castle, Julia Kodysh, Timothy J. O’Donnell, & Alex Rubinsteyn. (2019). Bioinformatic methods for cancer neoantigen prediction. Progress in molecular biology and translational science. 164. 25–60. 29 indexed citations
10.
O’Donnell, Timothy J., Marcia Meseck, Phillip Friedlander, et al.. (2019). Abstract B032: PhIP-seq assessment of the serum antibody repertoire before and after immune-related adverse events in four melanoma patients treated with checkpoint blockade immunotherapy. Cancer Immunology Research. 7(2_Supplement). B032–B032.
11.
Hormigo, Adı́lia, Alex Rubinsteyn, Julia Kodysh, Ana-Belén Blázquez, & Nina Bhardwaj. (2019). Abstract CT062: A Phase I study of the safety and immunogenicity of personalized mutation-derived tumor vaccine and treatment fields in patients with newly diagnosed glioblastoma. Cancer Research. 79(13_Supplement). CT062–CT062. 1 indexed citations
12.
O’Donnell, Timothy J., Alex Rubinsteyn, Maria Bonsack, et al.. (2018). MHCflurry: Open-Source Class I MHC Binding Affinity Prediction. Cell Systems. 7(1). 129–132.e4. 273 indexed citations
13.
Rubinsteyn, Alex, Julia Kodysh, Bülent Arman Aksoy, et al.. (2018). Computational Pipeline for the PGV-001 Neoantigen Vaccine Trial. Frontiers in Immunology. 8. 1807–1807. 49 indexed citations
14.
Rubinsteyn, Alex, et al.. (2017). hammerlab/isovar: Version 0.7.0. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
15.
Nathanson, Tavi, Arun Ahuja, Alex Rubinsteyn, et al.. (2016). Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 Blockade. Cancer Immunology Research. 5(1). 84–91. 122 indexed citations
16.
Oermann, Eric K., Alex Rubinsteyn, Dale Ding, et al.. (2016). Using a Machine Learning Approach to Predict Outcomes after Radiosurgery for Cerebral Arteriovenous Malformations. Scientific Reports. 6(1). 21161–21161. 83 indexed citations
17.
Unterthiner, Thomas, Eric B. Larson, Sander Dieleman, et al.. (2015). scikit-cuda 0.5.1. Zenodo (CERN European Organization for Nuclear Research). 5 indexed citations
18.
Rubinsteyn, Alex. (2014). Runtime Compilation of Array-Oriented Python Programs. 1 indexed citations
19.
Rubinsteyn, Alex, et al.. (2013). Learning Random Forests on the GPU. 7 indexed citations
20.
Rubinsteyn, Alex, et al.. (2012). Parakeet: a just-in-time parallel accelerator for python. 14–14. 17 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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