DDW Cornelison

4.1k total citations · 1 hit paper
38 papers, 3.0k citations indexed

About

DDW Cornelison is a scholar working on Molecular Biology, Surgery and Genetics. According to data from OpenAlex, DDW Cornelison has authored 38 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 19 papers in Surgery and 11 papers in Genetics. Recurrent topics in DDW Cornelison's work include Muscle Physiology and Disorders (23 papers), Tissue Engineering and Regenerative Medicine (17 papers) and Mesenchymal stem cell research (7 papers). DDW Cornelison is often cited by papers focused on Muscle Physiology and Disorders (23 papers), Tissue Engineering and Regenerative Medicine (17 papers) and Mesenchymal stem cell research (7 papers). DDW Cornelison collaborates with scholars based in United States, Canada and China. DDW Cornelison's co-authors include B Wold, Bradley B. Olwin, Alan C. Rapraeger, Michael A. Rudnicki, Ashley L. Siegel, Mark S. Filla, Sarah A. Wilcox‐Adelman, Heikki Rauvala, Paul F. Goetinck and Danny A. Stark and has published in prestigious journals such as Genes & Development, The Journal of Cell Biology and Development.

In The Last Decade

DDW Cornelison

36 papers receiving 3.0k citations

Hit Papers

Single-Cell Analysis of Regulatory Gene Expression in Qui... 1997 2026 2006 2016 1997 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
DDW Cornelison United States 22 2.6k 1.1k 703 502 487 38 3.0k
Julia von Maltzahn Germany 25 2.9k 1.1× 746 0.7× 515 0.7× 364 0.7× 772 1.6× 48 3.4k
Sophie Chargé Canada 13 2.3k 0.9× 804 0.8× 447 0.6× 405 0.8× 672 1.4× 26 2.9k
Ramkumar Sambasivan India 20 2.4k 0.9× 734 0.7× 618 0.9× 248 0.5× 441 0.9× 29 2.7k
Atsushi Asakura United States 31 3.9k 1.5× 1.4k 1.3× 1.3k 1.8× 420 0.8× 750 1.5× 73 4.8k
Feodor D. Price Canada 11 2.0k 0.8× 585 0.6× 489 0.7× 266 0.5× 514 1.1× 16 2.4k
Nicolas A. Dumont Canada 23 2.6k 1.0× 690 0.7× 512 0.7× 380 0.8× 829 1.7× 49 3.2k
Christoph Lepper United States 16 2.0k 0.8× 584 0.6× 468 0.7× 264 0.5× 626 1.3× 26 2.4k
Jonathan R. Beauchamp United Kingdom 20 3.3k 1.3× 1.6k 1.5× 1.2k 1.7× 342 0.7× 582 1.2× 26 3.9k
Yuko Miyagoe‐Suzuki Japan 36 3.6k 1.4× 1.1k 1.0× 929 1.3× 509 1.0× 885 1.8× 70 4.4k
C. Florian Bentzinger Canada 22 4.1k 1.6× 967 0.9× 664 0.9× 659 1.3× 1.2k 2.5× 31 4.9k

Countries citing papers authored by DDW Cornelison

Since Specialization
Citations

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

Fields of papers citing papers by DDW Cornelison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of DDW Cornelison

This figure shows the co-authorship network connecting the top 25 collaborators of DDW Cornelison. A scholar is included among the top collaborators of DDW Cornelison 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 DDW Cornelison. DDW Cornelison 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.
Nguyen, Michael, et al.. (2025). Satellite Cell Ablation Limits Myofiber Regeneration but Not Angiogenesis Following Skeletal Muscle Injury. Microcirculation. 32(7). e70024–e70024.
2.
Morton, Aaron B., et al.. (2024). Inducible deletion of endothelial cell Efnb2 delays capillary regeneration and attenuates myofibre reinnervation following myotoxin injury in mice. The Journal of Physiology. 602(19). 4907–4927. 3 indexed citations
3.
Cornelison, DDW, et al.. (2022). EphA1 receptor tyrosine kinase is localized to the nucleus in rhabdomyosarcoma from multiple species. Biology Open. 11(10). 1 indexed citations
4.
Cornelison, DDW, et al.. (2022). Eph/Ephrin-Based Protein Complexes: The Importance of cis Interactions in Guiding Cellular Processes. Frontiers in Molecular Biosciences. 8. 809364–809364. 9 indexed citations
5.
Schüler, Svenja C., Yuguo Liu, Michel Grandbois, et al.. (2022). Extracellular matrix: Brick and mortar in the skeletal muscle stem cell niche. Frontiers in Cell and Developmental Biology. 10. 1056523–1056523. 34 indexed citations
6.
Stark, Danny A., et al.. (2020). EphA7 promotes myogenic differentiation via cell-cell contact. eLife. 9. 14 indexed citations
7.
Morton, Aaron B., et al.. (2019). Barium chloride injures myofibers through calcium-induced proteolysis with fragmentation of motor nerves and microvessels. Skeletal Muscle. 9(1). 27–27. 55 indexed citations
8.
Siegel, Ashley L., et al.. (2017). Methods for Observing and Quantifying Muscle Satellite Cell Motility and Invasion In Vitro. Methods in molecular biology. 1556. 303–315. 2 indexed citations
9.
Cornelison, DDW & Eusebio Perdiguero. (2017). Muscle Stem Cells: A Model System for Adult Stem Cell Biology. Methods in molecular biology. 1556. 3–19. 6 indexed citations
10.
Villalón, Eric, et al.. (2017). Plastin-3 extends survival and reduces severity in mouse models of spinal muscular atrophy. JCI Insight. 2(5). e89970–e89970. 56 indexed citations
11.
Wang, Jingxin, Jennifer M. Peterson, Jonathan Shintaku, et al.. (2016). An NF-κB - EphrinA5-Dependent Communication between NG2+ Interstitial Cells and Myoblasts Promotes Muscle Growth in Neonates. Developmental Cell. 36(2). 215–224. 28 indexed citations
12.
Stark, Danny A., Nathan J. Coffey, Joanne Vallée, et al.. (2015). Ephrin-A3 promotes and maintains slow muscle fiber identity during postnatal development and reinnervation. The Journal of Cell Biology. 211(5). 1077–1091. 24 indexed citations
13.
Farina, Nicholas H., Melissa Hausburg, Nicole Dalla Betta, et al.. (2012). A role for RNA post-transcriptional regulation in satellite cell activation. Skeletal Muscle. 2(1). 21–21. 38 indexed citations
14.
Siegel, Ashley L., et al.. (2011). Muscle satellite cell proliferation and association: new insights from myofiber time-lapse imaging. Skeletal Muscle. 1(1). 7–7. 51 indexed citations
15.
Cook, Daniel P., et al.. (2011). Muscle satellite cells from GRMD dystrophic dogs are not phenotypically distinguishable from wild type satellite cells in ex vivo culture. Neuromuscular Disorders. 21(4). 282–290. 9 indexed citations
16.
Kelly, Kathleen, et al.. (2009). Syndecan-4-Expressing Muscle Progenitor Cells in the SP Engraft as Satellite Cells during Muscle Regeneration. Cell stem cell. 4(3). 217–225. 180 indexed citations
17.
Stevenson, Severin E., et al.. (2008). Neural cell adhesion molecule (NCAM) marks adult myogenic cells committed to differentiation. Experimental Cell Research. 314(7). 1553–1565. 76 indexed citations
18.
19.
Cornelison, DDW, Bradley B. Olwin, Michael A. Rudnicki, & B Wold. (2000). MyoD−/− Satellite Cells in Single-Fiber Culture Are Differentiation Defective and MRF4 Deficient. Developmental Biology. 224(2). 122–137. 224 indexed citations
20.
Cornelison, DDW & B Wold. (1997). Single-Cell Analysis of Regulatory Gene Expression in Quiescent and Activated Mouse Skeletal Muscle Satellite Cells. Developmental Biology. 191(2). 270–283. 731 indexed citations breakdown →

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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