Daniel P. Reay

901 total citations
19 papers, 727 citations indexed

About

Daniel P. Reay is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Daniel P. Reay has authored 19 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 10 papers in Genetics and 4 papers in Oncology. Recurrent topics in Daniel P. Reay's work include Virus-based gene therapy research (10 papers), Muscle Physiology and Disorders (9 papers) and CAR-T cell therapy research (3 papers). Daniel P. Reay is often cited by papers focused on Virus-based gene therapy research (10 papers), Muscle Physiology and Disorders (9 papers) and CAR-T cell therapy research (3 papers). Daniel P. Reay collaborates with scholars based in United States, Germany and Greece. Daniel P. Reay's co-authors include Paula R. Clemens, Paul D. Robbins, Denis C. Guttridge, Laura J. Niedernhofer, Simon C. Watkins, Donna B. Stolz, Siobhán Q. Gregg, George A. Garinis, Jin Wang and Andria R. Robinson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Neuroscience.

In The Last Decade

Daniel P. Reay

19 papers receiving 714 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel P. Reay United States 12 449 203 145 124 97 19 727
Ana Vujić United States 16 654 1.5× 177 0.9× 110 0.8× 61 0.5× 99 1.0× 28 1.0k
Jennifer L Onken United States 4 469 1.0× 437 2.2× 66 0.5× 178 1.4× 150 1.5× 4 931
Sarmistha Mukherjee United States 19 501 1.1× 129 0.6× 151 1.0× 50 0.4× 90 0.9× 27 923
Joonseok Cho United States 10 426 0.9× 176 0.9× 35 0.2× 127 1.0× 98 1.0× 16 706
Lior Roitman Israel 7 213 0.5× 224 1.1× 51 0.4× 135 1.1× 47 0.5× 8 482
Gabriela Desdín-Micó Spain 7 412 0.9× 177 0.9× 66 0.5× 325 2.6× 134 1.4× 11 931
Misako Kawahara United States 9 258 0.6× 270 1.3× 64 0.4× 200 1.6× 67 0.7× 9 583
Tillman Vollbrandt Germany 13 258 0.6× 314 1.5× 187 1.3× 252 2.0× 108 1.1× 18 878
Nora Yucel United States 9 418 0.9× 158 0.8× 67 0.5× 36 0.3× 41 0.4× 11 578
Nadine Wiper‐Bergeron Canada 14 489 1.1× 207 1.0× 67 0.5× 33 0.3× 63 0.6× 25 662

Countries citing papers authored by Daniel P. Reay

Since Specialization
Citations

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

Fields of papers citing papers by Daniel P. Reay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel P. Reay. 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 Daniel P. Reay. The network helps show where Daniel P. Reay may publish in the future.

Co-authorship network of co-authors of Daniel P. Reay

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

All Works

19 of 19 papers shown
1.
Yamaguchi, Koichi, Qi Tang, Paul A. Poland, et al.. (2024). Clinical features associated with the presence of anti-Ro52 and anti-Ro60 antibodies in Jo-1 antibody-positive anti-synthetase syndrome. Frontiers in Immunology. 15. 1399451–1399451. 1 indexed citations
2.
Reay, Daniel P., Tracy Tabib, Ying Wang, et al.. (2023). Antigen-driven T cell-macrophage interactions mediate the interface between innate and adaptive immunity in histidyl-tRNA synthetase-induced myositis. Frontiers in Immunology. 14. 1238221–1238221. 2 indexed citations
4.
Mi, Zhiping, Hao Liu, Marie E. Rose, et al.. (2020). Abolishing UCHL1's hydrolase activity exacerbates TBI-induced axonal injury and neuronal death in mice. Experimental Neurology. 336. 113524–113524. 18 indexed citations
5.
Liu, Hao, Nadya Povysheva, Marie E. Rose, et al.. (2019). Role of UCHL1 in axonal injury and functional recovery after cerebral ischemia. Proceedings of the National Academy of Sciences. 116(10). 4643–4650. 61 indexed citations
6.
Zhao, Jing, Lei Zhang, Xiaodong Mu, et al.. (2018). Development of novel NEMO-binding domain mimetics for inhibiting IKK/NF-κB activation. PLoS Biology. 16(6). e2004663–e2004663. 31 indexed citations
7.
Reay, Daniel P., Sheldon Bastacky, Kathryn E. Wack, et al.. (2015). d-Amino Acid Substitution of Peptide-Mediated NF-κB Suppression in mdx Mice Preserves Therapeutic Benefit in Skeletal Muscle, but Causes Kidney Toxicity. Molecular Medicine. 21(1). 442–452. 5 indexed citations
8.
Tilstra, Jeremy S., Andria R. Robinson, Jin Wang, et al.. (2012). NF-κB inhibition delays DNA damage–induced senescence and aging in mice. Journal of Clinical Investigation. 122(7). 2601–2612. 367 indexed citations
9.
Reay, Daniel P., et al.. (2012). Effect of Nuclear Factor κB Inhibition on Serotype 9 Adeno-Associated Viral (AAV9) Minidystrophin Gene Transfer to the mdx Mouse. Molecular Medicine. 18(3). 466–476. 4 indexed citations
10.
Reay, Daniel P., Michele Yang, Jon F. Watchko, et al.. (2011). Systemic delivery of NEMO binding domain/IKKγ inhibitory peptide to young mdx mice improves dystrophic skeletal muscle histopathology. Neurobiology of Disease. 43(3). 598–608. 39 indexed citations
11.
Tang, Ying, Daniel P. Reay, Denis C. Guttridge, et al.. (2010). Inhibition of the IKK/NF-κB pathway by AAV gene transfer improves muscle regeneration in older mdx mice. Gene Therapy. 17(12). 1476–1483. 43 indexed citations
12.
Li, J, Daniel P. Reay, Biao Wang, et al.. (2010). Improvement of the mdx mouse dystrophic phenotype by systemic in utero AAV8 delivery of a minidystrophin gene. Gene Therapy. 17(11). 1355–1362. 27 indexed citations
13.
Reay, Daniel P., Roberto Bilbao, Liquan Cai, et al.. (2008). Full-length dystrophin gene transfer to the mdx mouse in utero. Gene Therapy. 15(7). 531–536. 26 indexed citations
14.
Bilbao, Roberto, Daniel P. Reay, Juan Li, Xiao Xiao, & Paula R. Clemens. (2005). Patterns of Gene Expression from In Utero Delivery of Adenoviral-Associated Vector Serotype 1. Human Gene Therapy. 16(6). 678–684. 16 indexed citations
15.
Bilbao, Roberto, et al.. (2004). Comparison of high-capacity and first-generation adenoviral vector gene delivery to murine muscle in utero. Gene Therapy. 12(1). 39–47. 19 indexed citations
16.
Bilbao, Roberto, et al.. (2004). Biocompatibility of adenoviral vectors in poly(vinyl chloride) tubing catheters with presence or absence of plasticizer di‐2‐ethylhexyl phthalate. Journal of Biomedical Materials Research Part A. 69A(1). 91–96. 1 indexed citations
17.
Bilbao, Roberto, Daniel P. Reay, Christoph Volpers, et al.. (2003). Fetal muscle gene transfer is not enhanced by an RGD capsid modification to high-capacity adenoviral vectors. Gene Therapy. 10(21). 1821–1829. 21 indexed citations
18.
Bilbao, Roberto, Daniel P. Reay, Laura Goldberg, et al.. (2003). Binding of Adenoviral Fiber Knob to the Coxsackievirus–Adenovirus Receptor Is Crucial for Transduction of Fetal Muscle. Human Gene Therapy. 14(7). 645–649. 9 indexed citations
19.
Jiang, Zhilong, Daniel P. Reay, Florian Kreppel, et al.. (2001). Local High-Capacity Adenovirus-Mediated mCTLA4Ig and mCD40Ig Expression Prolongs Recombinant Gene Expression in Skeletal Muscle. Molecular Therapy. 3(6). 892–900. 34 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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