Jade Samulski

1.4k total citations
8 papers, 1.0k citations indexed

About

Jade Samulski is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Jade Samulski has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Genetics and 5 papers in Oncology. Recurrent topics in Jade Samulski's work include Virus-based gene therapy research (6 papers), CAR-T cell therapy research (5 papers) and Muscle Physiology and Disorders (3 papers). Jade Samulski is often cited by papers focused on Virus-based gene therapy research (6 papers), CAR-T cell therapy research (5 papers) and Muscle Physiology and Disorders (3 papers). Jade Samulski collaborates with scholars based in United States and China. Jade Samulski's co-authors include Scott McPhee, Chengwen Li, Steven J. Gray, Dawn E. Bowles, R. Jude Samulski, R. Jude Samulski, Paul E. Monahan, Joshua C. Grieger, Vinod Malik and K. Reed Clark and has published in prestigious journals such as New England Journal of Medicine, The Journal of Immunology and Biomaterials.

In The Last Decade

Jade Samulski

8 papers receiving 1000 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jade Samulski United States	7	800	610	192	180	90	8	1.0k
Marie Montus France	8	837 1.0×	662 1.1×	189 1.0×	212 1.2×	86 1.0×	10	1.1k
Helena Costa Verdera France	7	917 1.1×	535 0.9×	104 0.5×	219 1.2×	53 0.6×	10	1.2k
Joel R. Chamberlain United States	15	1.4k 1.7×	562 0.9×	152 0.8×	94 0.5×	187 2.1×	23	1.6k
Lisa M. Petek United States	12	1.0k 1.3×	472 0.8×	135 0.7×	71 0.4×	139 1.5×	12	1.1k
Christel Rivière France	11	520 0.7×	454 0.7×	101 0.5×	144 0.8×	182 2.0×	13	967
Amy Poirier United States	11	590 0.7×	587 1.0×	112 0.6×	151 0.8×	55 0.6×	13	910
Hollie A. Harper United States	7	895 1.1×	422 0.7×	186 1.0×	63 0.3×	63 0.7×	10	1.0k
Sruthi Mantri United States	6	1.4k 1.8×	593 1.0×	104 0.5×	262 1.5×	167 1.9×	9	1.6k
Yi-Li Min United States	11	1.3k 1.6×	368 0.6×	187 1.0×	66 0.4×	53 0.6×	11	1.4k
Scott Loiler United States	13	722 0.9×	781 1.3×	135 0.7×	140 0.8×	40 0.4×	20	1.2k

Countries citing papers authored by Jade Samulski

Since Specialization

Citations

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

Fields of papers citing papers by Jade Samulski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jade Samulski

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

All Works

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8 of 8 papers shown

Wang, Mian, et al.. (2015). Prediction of adeno-associated virus neutralizing antibody activity for clinical application. Gene Therapy. 22(12). 984–992. 42 indexed citations

Monahan, Paul E., Junjiang Sun, Tong Gui, et al.. (2014). Employing a Gain-of-Function Factor IX Variant R338L to Advance the Efficacy and Safety of Hemophilia B Human Gene Therapy: Preclinical Evaluation Supporting an Ongoing Adeno-Associated Virus Clinical Trial. Human Gene Therapy. 26(2). 69–81. 86 indexed citations

Ishikawa, Kiyotake, Kenneth Fish, Lisa Tilemann, et al.. (2014). Cardiac I-1c Overexpression With Reengineered AAV Improves Cardiac Function in Swine Ischemic Heart Failure. Molecular Therapy. 22(12). 2038–2045. 59 indexed citations

Bowles, Dawn E., Scott McPhee, Chengwen Li, et al.. (2011). Phase 1 Gene Therapy for Duchenne Muscular Dystrophy Using a Translational Optimized AAV Vector. Molecular Therapy. 20(2). 443–455. 306 indexed citations

Yazıcı, Cemal, Masahiko Takahata, David G. Reynolds, et al.. (2011). Self-complementary AAV2.5-BMP2-coated Femoral Allografts Mediated Superior Bone Healing Versus Live Autografts in Mice With Equivalent Biomechanics to Unfractured Femur. Molecular Therapy. 19(8). 1416–1425. 53 indexed citations

Campbell, Katherine, Louise R. Rodino‐Klapac, Zarife Sahenk, et al.. (2010). Revertant muscle fibers expressing dystrophin do not tolerize the immune system in Duchenne muscular dystrophy: lessons learned from a Phase I clinical trial (96.9). The Journal of Immunology. 184(Supplement_1). 96.9–96.9. 1 indexed citations

Mendell, Jerry R., Katherine Campbell, Louise R. Rodino‐Klapac, et al.. (2010). Dystrophin Immunity in Duchenne's Muscular Dystrophy. New England Journal of Medicine. 363(15). 1429–1437. 455 indexed citations

Yazıcı, Cemal, Chao Xie, David G. Reynolds, et al.. (2008). The effect of surface demineralization of cortical bone allograft on the properties of recombinant adeno-associated virus coatings. Biomaterials. 29(28). 3882–3887. 14 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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