Vanessa D. Jönsson

621 total citations · 1 hit paper
16 papers, 359 citations indexed

About

Vanessa D. Jönsson is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Vanessa D. Jönsson has authored 16 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Immunology and 6 papers in Oncology. Recurrent topics in Vanessa D. Jönsson's work include CAR-T cell therapy research (6 papers), Immune Cell Function and Interaction (4 papers) and Single-cell and spatial transcriptomics (3 papers). Vanessa D. Jönsson is often cited by papers focused on CAR-T cell therapy research (6 papers), Immune Cell Function and Interaction (4 papers) and Single-cell and spatial transcriptomics (3 papers). Vanessa D. Jönsson collaborates with scholars based in United States, Sweden and France. Vanessa D. Jönsson's co-authors include Saul J. Priceman, Richard M. Murray, David Baltimore, Aadel A. Chaudhuri, Ryan M. O’Connell, Nikita Sinha, Arnav Mehta, Dinesh S. Rao, Alex Yick‐Lun So and Anders Rantzer and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Vanessa D. Jönsson

15 papers receiving 353 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An age-progressive platelet differentiation path from hematopoietic stem cells causes exacerbated thrombosis

2024 49 citations Atesh Worthington, Stephanie Smith‐Berdan et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vanessa D. Jönsson United States	8	188	129	104	69	43	16	359
Szymon Stoma Switzerland	10	317 1.7×	58 0.4×	114 1.1×	84 1.2×	67 1.6×	13	633
Tamara K. Moyo United States	11	143 0.8×	79 0.6×	84 0.8×	30 0.4×	69 1.6×	32	317
Peter W. Krenn Austria	10	286 1.5×	39 0.3×	58 0.6×	126 1.8×	38 0.9×	18	472
Jakob Kaeppler United Kingdom	8	113 0.6×	54 0.4×	103 1.0×	121 1.8×	13 0.3×	11	337
Ahmed Dahmani France	11	469 2.5×	160 1.2×	133 1.3×	63 0.9×	18 0.4×	22	681
Angeline M.L. Wong Singapore	5	188 1.0×	77 0.6×	163 1.6×	59 0.9×	9 0.2×	5	372
Dana Ishay-Ronen Israel	7	200 1.1×	106 0.8×	188 1.8×	34 0.5×	7 0.2×	11	392
Syed Murtuza Baker United Kingdom	14	282 1.5×	27 0.2×	76 0.7×	167 2.4×	26 0.6×	28	525
Aline Roch Switzerland	11	233 1.2×	51 0.4×	44 0.4×	104 1.5×	185 4.3×	14	557
Rohan P. Joshi United States	10	151 0.8×	56 0.4×	166 1.6×	191 2.8×	9 0.2×	27	469

Countries citing papers authored by Vanessa D. Jönsson

Since Specialization

Citations

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

Fields of papers citing papers by Vanessa D. Jönsson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vanessa D. Jönsson. 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 Vanessa D. Jönsson. The network helps show where Vanessa D. Jönsson may publish in the future.

Co-authorship network of co-authors of Vanessa D. Jönsson

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

All Works

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16 of 16 papers shown

Smith‐Berdan, Stephanie, et al.. (2025). A Rare Hematopoietic Stem Cell‐Derived Megakaryocyte Progenitor Accumulates via Enhanced Survival and Contributes to Exacerbated Thrombopoiesis Upon Aging. Aging Cell. 24(11). e70221–e70221. 1 indexed citations

Jönsson, Vanessa D., et al.. (2025). Protocol for deep-learning-driven cell type label transfer in single-cell RNA sequencing data. STAR Protocols. 6(2). 103768–103768.

Worthington, Atesh, Stephanie Smith‐Berdan, M Rommel, et al.. (2024). An age-progressive platelet differentiation path from hematopoietic stem cells causes exacerbated thrombosis. Cell. 187(12). 3090–3107.e21. 49 indexed citations breakdown →

Paten, Benedict, et al.. (2024). SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis. Cell Genomics. 4(6). 100581–100581. 6 indexed citations

Yamaguchi, Yukiko, Raymond T. Ng, Neena A. Leggett, et al.. (2022). PD-L1 blockade restores CAR T cell activity through IFN-γ-regulation of CD163+ M2 macrophages. Journal for ImmunoTherapy of Cancer. 10(6). e004400–e004400. 74 indexed citations

Bucktrout, Samantha, Nicholas E. Banovich, Lisa H. Butterfield, et al.. (2022). Advancing T cell–based cancer therapy with single-cell technologies. Nature Medicine. 28(9). 1761–1764. 2 indexed citations

Brown, Christine E., Darya Alizadeh, Vanessa D. Jönsson, et al.. (2021). Abstract 59: CAR T cell therapy reshapes the tumor microenvironment to promote host antitumor immune repsonses in glioblastoma. Cancer Research. 81(13_Supplement). 59–59. 2 indexed citations

Stern, Lawrence A., Vanessa D. Jönsson, & Saul J. Priceman. (2020). CAR T Cell Therapy Progress and Challenges for Solid Tumors. Cancer treatment and research. 180. 297–326. 29 indexed citations

Dullerud, Natalie & Vanessa D. Jönsson. (2020). Cellular Immunotherapy Treatment Scheduling to Address Antigen Escape. 34. 4634–4639. 1 indexed citations

10.

Barish, Michael E., Lihong Weng, Massimo D’Apuzzo, et al.. (2020). P855 High-resolution maps of heterogeneous antigen expression in glioblastoma and implications for immunotherapy. Poster presentations. A6.1–A6. 1 indexed citations

11.

Jönsson, Vanessa D., Luping Lin, Saurabh Asthana, et al.. (2017). Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution. Scientific Reports. 7(1). 44206–44206. 28 indexed citations

12.

Giordano, Giulia, Anders Rantzer, & Vanessa D. Jönsson. (2016). A convex optimization approach to cancer treatment to address tumor heterogeneity and imperfect drug penetration in physiological compartments. Institutional Research Information System (Università degli Studi di Trento). 2494–2500. 8 indexed citations

13.

Jönsson, Vanessa D., Anders Rantzer, & Richard M. Murray. (2014). A scalable formulation for engineering combination therapies for evolutionary dynamics of disease. 2771–2778. 25 indexed citations

14.

Jönsson, Vanessa D., Nikolai Matni, & Richard M. Murray. (2014). Synthesizing combination therapies for evolutionary dynamics of disease for nonlinear pharmacodynamics. 271. 2352–2358. 2 indexed citations

15.

Jönsson, Vanessa D., Nikolai Matni, & Richard M. Murray. (2013). Reverse engineering combination therapies for evolutionary dynamics of disease: An ℌ<inf>∞</inf> approach. 2060–2065. 14 indexed citations

16.

Chaudhuri, Aadel A., Alex Yick‐Lun So, Arnav Mehta, et al.. (2012). Oncomir miR-125b regulates hematopoiesis by targeting the gene Lin28A. Proceedings of the National Academy of Sciences. 109(11). 4233–4238. 117 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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