Robert L. Judson

3.2k total citations · 2 hit papers
20 papers, 2.2k citations indexed

About

Robert L. Judson is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Robert L. Judson has authored 20 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 8 papers in Cancer Research and 5 papers in Oncology. Recurrent topics in Robert L. Judson's work include CRISPR and Genetic Engineering (8 papers), Pluripotent Stem Cells Research (7 papers) and MicroRNA in disease regulation (6 papers). Robert L. Judson is often cited by papers focused on CRISPR and Genetic Engineering (8 papers), Pluripotent Stem Cells Research (7 papers) and MicroRNA in disease regulation (6 papers). Robert L. Judson collaborates with scholars based in United States, Australia and France. Robert L. Judson's co-authors include Robert Blelloch, Collin Melton, Joshua Babiarz, Monica Venere, Rik Derynck, Samy Lamouille, Deepa Subramanyam, Jason Y. Liu, Nathan Bucay and A. Hunter Shain and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Robert L. Judson

20 papers receiving 2.2k citations

Hit Papers

Opposing microRNA families regulate self-renewal in mouse... 2009 2026 2014 2020 2010 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert L. Judson United States 13 1.9k 962 323 174 131 20 2.2k
Lucas Dennis United States 12 1.8k 0.9× 1.3k 1.3× 470 1.5× 119 0.7× 50 0.4× 25 2.5k
Sebastian Hoersch United States 16 1.6k 0.8× 503 0.5× 672 2.1× 239 1.4× 144 1.1× 23 2.6k
Benjamin T. Spike United States 23 1.6k 0.9× 563 0.6× 1.0k 3.1× 219 1.3× 81 0.6× 44 2.4k
Timour Baslan United States 20 1.5k 0.8× 932 1.0× 761 2.4× 77 0.4× 133 1.0× 37 2.3k
Christopher Rodman United States 6 1.3k 0.7× 788 0.8× 891 2.8× 91 0.5× 142 1.1× 11 2.1k
Rik G.H. Lindeboom Netherlands 19 1.5k 0.8× 365 0.4× 285 0.9× 79 0.5× 95 0.7× 26 1.9k
Aldo Massimi United States 9 1.1k 0.6× 312 0.3× 238 0.7× 87 0.5× 78 0.6× 15 1.6k
Kate Lawrenson United States 27 1.0k 0.5× 530 0.6× 486 1.5× 84 0.5× 207 1.6× 62 1.9k
Dong‐Joo Cheon United States 17 806 0.4× 430 0.4× 615 1.9× 108 0.6× 203 1.5× 30 1.6k
Céline Vallot France 19 1.3k 0.7× 494 0.5× 267 0.8× 112 0.6× 64 0.5× 35 1.7k

Countries citing papers authored by Robert L. Judson

Since Specialization
Citations

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

Fields of papers citing papers by Robert L. Judson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert L. Judson. 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 Robert L. Judson. The network helps show where Robert L. Judson may publish in the future.

Co-authorship network of co-authors of Robert L. Judson

This figure shows the co-authorship network connecting the top 25 collaborators of Robert L. Judson. A scholar is included among the top collaborators of Robert L. Judson 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 Robert L. Judson. Robert L. Judson 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.
Botton, Thomas, Eric Talevich, Vivek Kumar Mishra, et al.. (2019). Genetic Heterogeneity of BRAF Fusion Kinases in Melanoma Affects Drug Responses. Cell Reports. 29(3). 573–588.e7. 72 indexed citations
2.
Shain, A. Hunter, Nancy M. Joseph, Richard Yu, et al.. (2018). Genomic and Transcriptomic Analysis Reveals Incremental Disruption of Key Signaling Pathways during Melanoma Evolution. Cancer Cell. 34(1). 45–55.e4. 129 indexed citations
3.
Zeng, Hanlin, Aparna Jorapur, A. Hunter Shain, et al.. (2018). Bi-allelic Loss of CDKN2A Initiates Melanoma Invasion via BRN2 Activation. Cancer Cell. 34(1). 56–68.e9. 86 indexed citations
4.
Shain, A. Hunter, Nancy M. Joseph, Richard Yu, et al.. (2018). Abstract NG07: Genomic and transcriptomic analysis reveals incremental disruption of key signaling pathways during melanoma evolution. Cancer Research. 78(13_Supplement). NG07–NG07. 1 indexed citations
5.
Judson, Robert L., et al.. (2018). Evaluation of holographic imaging cytometer holomonitor M4® motility applications. Cytometry Part A. 93(11). 1125–1131. 13 indexed citations
6.
Judson, Robert L., Miroslav Hejna, Aparna Jorapur, Jun S. Song, & Yuntian Zhang. (2018). Quantification of mammalian tumor cell state plasticity with digital holographic cytometry. 4. 36–36. 2 indexed citations
7.
Lang, U., Aparna Jorapur, A. Hunter Shain, et al.. (2017). 148 Combined activation of MAP kinase and beta-catenin signaling define deep penetrating nevi. Journal of Investigative Dermatology. 137(5). S25–S25. 5 indexed citations
8.
Hejna, Miroslav, Aparna Jorapur, Jun S. Song, & Robert L. Judson. (2017). High accuracy label-free classification of single-cell kinetic states from holographic cytometry of human melanoma cells. Scientific Reports. 7(1). 11943–11943. 48 indexed citations
9.
Yeh, Iwei, Ursula E. Lang, Meng Kian Tee, et al.. (2017). Combined activation of MAP kinase pathway and β-catenin signaling cause deep penetrating nevi. Nature Communications. 8(1). 644–644. 87 indexed citations
10.
Shain, A. Hunter, Richard Yu, Iwei Yeh, et al.. (2016). Abstract 2372: The genetic evolution of melanoma. Cancer Research. 76(14_Supplement). 2372–2372. 3 indexed citations
11.
Huskey, Noelle E., Tingxia Guo, Kimberley Evason, et al.. (2015). CDK1 Inhibition Targets the p53-NOXA-MCL1 Axis, Selectively Kills Embryonic Stem Cells, and Prevents Teratoma Formation. Stem Cell Reports. 4(3). 374–389. 54 indexed citations
12.
Parchem, Ronald J., et al.. (2014). Two miRNA Clusters Reveal Alternative Paths in Late-Stage Reprogramming. Cell stem cell. 14(5). 617–631. 67 indexed citations
13.
Judson, Robert L., et al.. (2013). MicroRNA-based discovery of barriers to dedifferentiation of fibroblasts to pluripotent stem cells. Nature Structural & Molecular Biology. 20(10). 1227–1235. 47 indexed citations
14.
Judson, Robert L., et al.. (2013). microRNA Control of Mouse and Human Pluripotent Stem Cell Behavior. Annual Review of Cell and Developmental Biology. 29(1). 213–239. 65 indexed citations
16.
Subramanyam, Deepa, Samy Lamouille, Robert L. Judson, et al.. (2011). Multiple targets of miR-302 and miR-372 promote reprogramming of human fibroblasts to induced pluripotent stem cells. Nature Biotechnology. 29(5). 443–448. 461 indexed citations
17.
Melton, Collin, Robert L. Judson, & Robert Blelloch. (2010). Opposing microRNA families regulate self-renewal in mouse embryonic stem cells. Nature. 463(7281). 621–626. 542 indexed citations breakdown →
18.
Judson, Robert L., Joshua Babiarz, Monica Venere, & Robert Blelloch. (2009). Embryonic stem cell–specific microRNAs promote induced pluripotency. Nature Biotechnology. 27(5). 459–461. 519 indexed citations breakdown →
19.
Ebina, Hirotaka, et al.. (2008). The GP(Y/F) Domain of TF1 Integrase Multimerizes when Present in a Fragment, and Substitutions in This Domain Reduce Enzymatic Activity of the Full-length Protein. Journal of Biological Chemistry. 283(23). 15965–15974. 6 indexed citations
20.
Judson, Robert L., et al.. (2006). The Self Primer of the Long Terminal Repeat Retrotransposon Tf1 Is Not Removed during Reverse Transcription. Journal of Virology. 80(16). 8267–8270. 10 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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