S D Hauschka
- Molecular Biology top 10%
- Surgery top 10%
- Genetics top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Biomaterials top 10%
- Co-authors
- Charles E. MurryRobert W. WisemanStephen M. SchwartzBradley B. OlwinJeffrey S. ChamberlainJean N. BuskinJames B. JaynesRobert W. Lim
- Topics
- Muscle Physiology and Disorders (7 papers)Ion channel regulation and function (3 papers)Tissue Engineering and Regenerative Medicine (3 papers)
- Partner nations
- United StatesAustraliaCanada
In The Last Decade
S D Hauschka
15 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 68
- Molecular Biology 802
- Surgery 452
- Genetics 219
- Cardiology and Cardiovascular Medicine 202
- Biomaterials 175
Countries citing papers authored by S D Hauschka
This map shows the geographic impact of S D Hauschka'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 S D Hauschka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S D Hauschka more than expected).
Fields of papers citing papers by S D Hauschka
This network shows the impact of papers produced by S D Hauschka. 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 S D Hauschka. The network helps show where S D Hauschka may publish in the future.
Co-authorship network of co-authors of S D Hauschka
This figure shows the co-authorship network connecting the top 25 collaborators of S D Hauschka. A scholar is included among the top collaborators of S D Hauschka 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 S D Hauschka. S D Hauschka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Li, S, Kimura, E, Fall, BM, Reyes, M, Angello, JC, Welikson, R et al.. Stable transduction of myogenic cells with lentiviral vectors expressing a minidystrophin. Gene Ther 12: 1099-1108 | 18 |
| 2 | 1 | |
| 3 | 70 | |
| 4 | Floyd, S.S. Jr. et al. Ex vivo gene transfer using adenovirus-mediated full-length dystrophin delivery to dystrophic muscles. Gene Ther. 5, 19-30 | 9 |
| 5 | 447 | |
| 6 | p53-dependent activation of the mouse MCK gene promoter: identification of a novel p53-responsive sequence and evidence for cooperation between distinct p53 binding sites. | 7 |
| 7 | 55 | |
| 8 | Gene complementation using myoblast transfer into fetal muscle. | 6 |
| 9 | 4 | |
| 10 | 15 | |
| 11 | 177 | |
| 12 | 26 | |
| 13 | 161 | |
| 14 | 48 | |
| 15 | 74 |
About S D Hauschka
S D Hauschka is a scholar working on Molecular Biology, Biomaterials and Cancer Research, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (7 papers), Ion channel regulation and function (3 papers) and Tissue Engineering and Regenerative Medicine (3 papers). The work is most often cited by research in Genetics (219 citations), Biomaterials (175 citations) and Molecular Biology (802 citations). S D Hauschka has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Charles E. Murry, Robert W. Wiseman, Stephen M. Schwartz, Bradley B. Olwin, Jeffrey S. Chamberlain, Jean N. Buskin, James B. Jaynes, Robert W. Lim, Jane E. Johnson and Todd Scheuer. Their work appears in journals such as Journal of Clinical Investigation, Journal of Neuroscience and The Journal of Cell Biology.
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.