Jackson Nyman

4.1k total citations · 1 hit paper
7 papers, 756 citations indexed

About

Jackson Nyman is a scholar working on Immunology, Oncology and Infectious Diseases. According to data from OpenAlex, Jackson Nyman has authored 7 papers receiving a total of 756 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Immunology, 2 papers in Oncology and 1 paper in Infectious Diseases. Recurrent topics in Jackson Nyman's work include Cancer Immunotherapy and Biomarkers (2 papers), Immune Cell Function and Interaction (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Jackson Nyman is often cited by papers focused on Cancer Immunotherapy and Biomarkers (2 papers), Immune Cell Function and Interaction (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Jackson Nyman collaborates with scholars based in United States, Israel and Germany. Jackson Nyman's co-authors include Vijay K. Kuchroo, Aviv Regev, Ana C. Anderson, Sema Kurtuluş, Orit Rozenblatt–Rosen, Junrong Xia, Danielle Dionne, Mathias Pawlak, Elena Christian and Giulia Escobar and has published in prestigious journals such as Cell, Immunity and Frontiers in Plant Science.

In The Last Decade

Jackson Nyman

7 papers receiving 750 citations

Hit Papers

Checkpoint Blockade Immunotherapy Induces Dynamic Changes... 2019 2026 2021 2023 2019 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
Jackson Nyman United States 6 526 471 194 50 38 7 756
Valentina Casella Spain 6 486 0.9× 412 0.9× 137 0.7× 40 0.8× 29 0.8× 13 658
Samuel Alsén Sweden 9 513 1.0× 277 0.6× 191 1.0× 41 0.8× 28 0.7× 15 737
Hsiao‐Wei Tsao United States 7 626 1.2× 429 0.9× 249 1.3× 62 1.2× 27 0.7× 7 843
Renee Wu United States 9 726 1.4× 383 0.8× 194 1.0× 30 0.6× 25 0.7× 13 930
Nourredine Himoudi United Kingdom 14 351 0.7× 292 0.6× 164 0.8× 50 1.0× 44 1.2× 18 599
Patrick Roelli Switzerland 7 625 1.2× 418 0.9× 221 1.1× 43 0.9× 26 0.7× 7 852
Jessica Michie Australia 8 329 0.6× 330 0.7× 225 1.2× 47 0.9× 45 1.2× 10 545
Peter O. Hofgaard Norway 13 741 1.4× 500 1.1× 269 1.4× 55 1.1× 26 0.7× 19 1.0k
Mara Valentini Italy 5 450 0.9× 379 0.8× 125 0.6× 20 0.4× 38 1.0× 5 643
Erika J. Crosby United States 13 314 0.6× 256 0.5× 161 0.8× 34 0.7× 28 0.7× 24 573

Countries citing papers authored by Jackson Nyman

Since Specialization
Citations

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

Fields of papers citing papers by Jackson Nyman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jackson Nyman

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

All Works

7 of 7 papers shown
1.
Nyman, Jackson, Thomas Denize, Ziad Bakouny, et al.. (2023). Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states. Cell Reports Medicine. 4(9). 101189–101189. 14 indexed citations
2.
Pawlak, Mathias, David DeTomaso, Alexandra Schnell, et al.. (2022). Induction of a colitogenic phenotype in Th1-like cells depends on interleukin-23 receptor signaling. Immunity. 55(9). 1663–1679.e6. 27 indexed citations
3.
Mangani, Davide, Meromit Singer, Ruitong Li, et al.. (2022). 964 Dynamic immune landscapes during melanoma progression reveal a role for endogenous opioids in driving T cell dysfunction. Regular and Young Investigator Award Abstracts. A1005–A1005. 1 indexed citations
4.
Kurtuluş, Sema, Asaf Madi, Giulia Escobar, et al.. (2019). Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1−CD8+ Tumor-Infiltrating T Cells. Immunity. 50(1). 181–194.e6. 401 indexed citations breakdown →
5.
Schubert, Benjamin, Rohan Maddamsetti, Jackson Nyman, Maha Farhat, & Debora S. Marks. (2018). Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings. Nature Microbiology. 4(2). 328–338. 31 indexed citations
6.
Keppler, Bernhard K., Junqi Song, Jackson Nyman, Christian A. Voigt, & Andrew F. Bent. (2018). 3-Aminobenzamide Blocks MAMP-Induced Callose Deposition Independently of Its Poly(ADPribosyl)ation Inhibiting Activity. Frontiers in Plant Science. 9. 1907–1907. 13 indexed citations
7.
Singer, Meromit, Chao Wang, Le Cong, et al.. (2016). A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells. Cell. 166(6). 1500–1511.e9. 269 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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