Jane Owens

812 total citations
26 papers, 583 citations indexed

About

Jane Owens is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jane Owens has authored 26 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 6 papers in Cardiology and Cardiovascular Medicine and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jane Owens's work include Muscle Physiology and Disorders (13 papers), Cardiomyopathy and Myosin Studies (5 papers) and Virus-based gene therapy research (3 papers). Jane Owens is often cited by papers focused on Muscle Physiology and Disorders (13 papers), Cardiomyopathy and Myosin Studies (5 papers) and Virus-based gene therapy research (3 papers). Jane Owens collaborates with scholars based in United States, United Kingdom and France. Jane Owens's co-authors include Carl Morris, Peter Bialek, Nicolas Christoforou, Charles P. Emerson, Todd J. Martı́nez, Christopher M. Brennan, Chutintorn Punwong, Gerard Bain, Andrew Robertson and Prashant Bansal and has published in prestigious journals such as PLoS ONE, The Journal of Physical Chemistry B and The Journal of Physiology.

In The Last Decade

Jane Owens

25 papers receiving 574 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jane Owens United States 15 382 100 71 69 63 26 583
Anthony R. Soltis United States 12 418 1.1× 62 0.6× 130 1.8× 47 0.7× 54 0.9× 28 699
Åke Sidén Sweden 17 391 1.0× 71 0.7× 41 0.6× 65 0.9× 38 0.6× 41 832
Susanne E. Swalley United States 12 785 2.1× 194 1.9× 37 0.5× 49 0.7× 29 0.5× 14 961
Chen Fu China 16 426 1.1× 54 0.5× 124 1.7× 29 0.4× 29 0.5× 45 860
Margaret Cunningham United Kingdom 15 220 0.6× 36 0.4× 76 1.1× 46 0.7× 74 1.2× 38 561
Joanna Bielańska Spain 16 545 1.4× 45 0.5× 221 3.1× 48 0.7× 108 1.7× 19 777
Tory Schaaf United States 10 338 0.9× 38 0.4× 103 1.5× 36 0.5× 93 1.5× 16 487
M. I. Shakhparonov Russia 16 652 1.7× 50 0.5× 36 0.5× 51 0.7× 31 0.5× 71 938
Sophie Duban‐Deweer France 12 471 1.2× 47 0.5× 25 0.4× 36 0.5× 26 0.4× 23 740
Valeria Tomati Italy 20 449 1.2× 119 1.2× 20 0.3× 64 0.9× 34 0.5× 42 1.1k

Countries citing papers authored by Jane Owens

Since Specialization
Citations

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

Fields of papers citing papers by Jane Owens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jane Owens

This figure shows the co-authorship network connecting the top 25 collaborators of Jane Owens. A scholar is included among the top collaborators of Jane Owens 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 Jane Owens. Jane Owens 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.
Brimble, Mark A., Jane Owens, Laurence O. Whiteley, et al.. (2024). Single cell and TCR analysis of immune cells from AAV gene therapy-dosed Duchenne muscular dystrophy patients. Molecular Therapy — Methods & Clinical Development. 32(4). 101349–101349. 4 indexed citations
2.
Guiner, Caroline Le, Xiao Xiao, Thibaut Larcher, et al.. (2023). Evaluation of an AAV9-mini-dystrophin gene therapy candidate in a rat model of Duchenne muscular dystrophy. Molecular Therapy — Methods & Clinical Development. 30. 30–47. 12 indexed citations
3.
Gluscevic, Martina, David J. Tester, Nicolas Christoforou, et al.. (2023). BS-452758-3 SUPPRESSION-REPLACEMENT GENE THERAPY FOR -MEDIATED CARDIOMYOPATHIES. Heart Rhythm. 20(5). S42–S43.
4.
Kim, Jihee, Muriel Nobles, Denis Rybin, et al.. (2022). CRISPR-mediated correction of skeletal muscle Ca2+ handling in a novel DMD patient-derived pluripotent stem cell model. Neuromuscular Disorders. 32(11-12). 908–922. 3 indexed citations
5.
Brennan, Christopher M., Xianfeng Li, Liang Xue, et al.. (2022). DUX4 expression activates JNK and p38 MAP kinases in myoblasts. Disease Models & Mechanisms. 15(11). 12 indexed citations
6.
Farrokhi, Vahid, Jason Walsh, Joe Palandra, et al.. (2021). Dystrophin and mini-dystrophin quantification by mass spectrometry in skeletal muscle for gene therapy development in Duchenne muscular dystrophy. Gene Therapy. 29(10-11). 608–615. 17 indexed citations
7.
Brennan, Christopher M., Charles P. Emerson, Jane Owens, & Nicolas Christoforou. (2021). p38 MAPKs — roles in skeletal muscle physiology, disease mechanisms, and as potential therapeutic targets. JCI Insight. 6(12). 58 indexed citations
8.
Spinazzola, Janelle M., et al.. (2020). PDE10A Inhibition Reduces the Manifestation of Pathology in DMD Zebrafish and Represses the Genetic Modifier PITPNA. Molecular Therapy. 29(3). 1086–1101. 13 indexed citations
9.
Schomaker, Shelli, David M. Potter, Roscoe L. Warner, et al.. (2020). Serum glutamate dehydrogenase activity enables early detection of liver injury in subjects with underlying muscle impairments. PLoS ONE. 15(5). e0229753–e0229753. 44 indexed citations
10.
11.
Aartsma‐Rus, Annemieke, Jennifer E. Morgan, Hendrik Neubert, et al.. (2019). Report of a TREAT-NMD/World Duchenne Organisation Meeting on Dystrophin Quantification Methodology. Journal of Neuromuscular Diseases. 6(1). 147–159. 44 indexed citations
12.
Zhang, Xiaoyu, Jane Owens, Henrik S. Olsen, et al.. (2019). A recombinant human IgG1 Fc multimer designed to mimic the active fraction of IVIG in autoimmunity. JCI Insight. 4(2). 24 indexed citations
13.
Zhou, Hua, Henrik S. Olsen, Edward So, et al.. (2017). A fully recombinant human IgG1 Fc multimer (GL-2045) inhibits complement-mediated cytotoxicity and induces iC3b. Blood Advances. 1(8). 504–515. 25 indexed citations
14.
Beatka, Margaret, Hui Meng, Lin Yang, et al.. (2017). Myostatin inhibition using mRK35 produces skeletal muscle growth and tubular aggregate formation in wild type and TgACTA1D286G nemaline myopathy mice. Human Molecular Genetics. 27(4). 638–648. 26 indexed citations
15.
16.
Wang, Mengmeng, Yutian Zhan, Jianqing Chen, et al.. (2016). Understanding Lung Deposition of Alpha-1 Antitrypsin in Acute Experimental Mouse Lung Injury Model Using Fluorescence Microscopy. PubMed. 2016. 1–11. 1 indexed citations
17.
Owens, Jane, et al.. (2013). Characterization of primary human skeletal muscle cells from multiple commercial sources. In Vitro Cellular & Developmental Biology - Animal. 49(9). 695–705. 27 indexed citations
18.
Sastry, Kumara, D. D. Johnson, Alexis L. Thompson, et al.. (2007). Optimization of Semiempirical Quantum Chemistry Methods via Multiobjective Genetic Algorithms: Accurate Photodynamics for Larger Molecules and Longer Time Scales. Materials and Manufacturing Processes. 22(5). 553–561. 18 indexed citations
19.
Sastry, Kumara, D. D. Johnson, Alexis L. Thompson, et al.. (2006). Multiobjective genetic algorithms for multiscaling excited state direct dynamics in photochemistry. 1745–1752. 5 indexed citations
20.
Owens, Jane, Bryan K. S. Yeung, Daniel C. Hill, & Peter A. Petillo. (2001). Facile C1 Epimerization of α-1-Sulfonamidyl-2-deoxy-2-iodo- glycopyranosides. The Journal of Organic Chemistry. 66(4). 1484–1486. 17 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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