Megan Robinson

620 total citations
10 papers, 301 citations indexed

About

Megan Robinson is a scholar working on Molecular Biology, Oncology and Biomedical Engineering. According to data from OpenAlex, Megan Robinson has authored 10 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Oncology and 3 papers in Biomedical Engineering. Recurrent topics in Megan Robinson's work include Pluripotent Stem Cells Research (6 papers), CRISPR and Genetic Engineering (5 papers) and CAR-T cell therapy research (5 papers). Megan Robinson is often cited by papers focused on Pluripotent Stem Cells Research (6 papers), CRISPR and Genetic Engineering (5 papers) and CAR-T cell therapy research (5 papers). Megan Robinson collaborates with scholars based in United States, Sweden and Germany. Megan Robinson's co-authors include Bahram Valamehr, Ramzey Abujarour, Peter Flynn, Thuy Le, David Robbins, Tom Tong Lee, M Salmon, M Bofill, G Jánossy and Kevin Lai and has published in prestigious journals such as Blood, The Journal of Immunology and Cancer Research.

In The Last Decade

Megan Robinson

10 papers receiving 297 citations

Peers

Megan Robinson

MB

IMMUN

ONCOL

BE

SURGE

Ryan Huang United States

Kathrin Haake Germany

Sebastian Brennig Germany

William L. Corwin United States

Immanuel Andrä Germany

Monalisa Ghosh United States

Haelee Ahn United States

Anita van den Heuvel Netherlands

Atsutaka Minagawa Japan

Martin Tibudan United States

Ryan Huang United States

Megan Robinson

140 ×0.8

MB

87 ×0.9

IMMUN

35 ×0.5

ONCOL

43 ×0.8

BE

36 ×0.7

SURGE

Citations per year, relative to Megan Robinson Megan Robinson (= 1×) peers Ryan Huang

Countries citing papers authored by Megan Robinson

Since Specialization

Citations

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

Fields of papers citing papers by Megan Robinson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megan Robinson

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

All Works

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10 of 10 papers shown

1.

Bjordahl, Ryan, Svetlana Gaidarova, Karrune Woan, et al.. (2019). FT538: Preclinical Development of an Off-the-Shelf Adoptive NK Cell Immunotherapy with Targeted Disruption of CD38 to Prevent Anti-CD38 Antibody-Mediated Fratricide and Enhance ADCC in Multiple Myeloma When Combined with Daratumumab. Blood. 134(Supplement_1). 133–133. 13 indexed citations

2.

Bjordahl, Ryan, Svetlana Gaidarova, Jode Goodridge, et al.. (2019). FT576: A Novel Multiplexed Engineered Off-the-Shelf Natural Killer Cell Immunotherapy for the Dual-Targeting of CD38 and Bcma for the Treatment of Multiple Myeloma. Blood. 134(Supplement_1). 3214–3214. 26 indexed citations

3.

Bjordahl, Ryan, Sajid Mahmood, Svetlana Gaidarova, et al.. (2018). Abstract 3576: FT500, an off-the-shelf NK cell cancer immunotherapy derived from a master pluripotent cell line, enhances T-cell activation and recruitment to overcome checkpoint blockade resistance. Cancer Research. 78(13_Supplement). 3576–3576. 7 indexed citations

4.

Bjordahl, Ryan, Raedun Clarke, Svetlana Gaidarova, et al.. (2017). Multi-Functional Genetic Engineering of Pluripotent Cell Lines for Universal Off-the-Shelf Natural Killer Cell Cancer Immunotherapy. Blood. 130. 3187–3187. 1 indexed citations

5.

Clarke, Raedun, Brian Groff, Tom Tong Lee, et al.. (2016). Genetically Enhanced Pluripotent Stem Cell-Derived T Lymphocytes for Off-the-Shelf Cellular Immunotherapy. Blood. 128(22). 2164–2164. 1 indexed citations

6.

Sánchez, José Carlos Gómez, et al.. (2014). Combining protein-based biomaterials with stem cells for spinal cord injury repair. UVic’s Research and Learning Repository (University of Victoria). 1 indexed citations

7.

Abujarour, Ramzey, Bahram Valamehr, Tom Tong Lee, et al.. (2014). Myogenic Differentiation of Muscular Dystrophy-Specific Induced Pluripotent Stem Cells for Use in Drug Discovery. Stem Cells Translational Medicine. 3(2). 149–160. 91 indexed citations

8.

Abujarour, Ramzey, et al.. (2013). Optimized Surface Markers for the Prospective Isolation of High-Quality hiPSCs using Flow Cytometry Selection. Scientific Reports. 3(1). 1179–1179. 36 indexed citations

9.

Valamehr, Bahram, Ramzey Abujarour, Megan Robinson, et al.. (2012). A novel platform to enable the high-throughput derivation and characterization of feeder-free human iPSCs. Scientific Reports. 2(1). 213–213. 62 indexed citations

10.

Bofill, M, et al.. (1994). Immature CD45RA(low)RO(low) T cells in the human cord blood. I. Antecedents of CD45RA+ unprimed T cells.. The Journal of Immunology. 152(12). 5613–5623. 63 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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