Sarah E. Sweterlitsch

559 total citations
7 papers, 445 citations indexed

About

Sarah E. Sweterlitsch is a scholar working on Cardiology and Cardiovascular Medicine, Oncology and Surgery. According to data from OpenAlex, Sarah E. Sweterlitsch has authored 7 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cardiology and Cardiovascular Medicine, 4 papers in Oncology and 3 papers in Surgery. Recurrent topics in Sarah E. Sweterlitsch's work include Cardiac Fibrosis and Remodeling (5 papers), Peptidase Inhibition and Analysis (4 papers) and Protease and Inhibitor Mechanisms (3 papers). Sarah E. Sweterlitsch is often cited by papers focused on Cardiac Fibrosis and Remodeling (5 papers), Peptidase Inhibition and Analysis (4 papers) and Protease and Inhibitor Mechanisms (3 papers). Sarah E. Sweterlitsch collaborates with scholars based in United States and United Kingdom. Sarah E. Sweterlitsch's co-authors include Francis G. Spinale, Joseph T. Mingoia, Rupak Mukherjee, Christina E. Squires, Gustavo Escobar, J.C. Hendrick, Merry L. Lindsey, William C. Gibson, John S. Ikonomidis and Robert P. Thompson and has published in prestigious journals such as Circulation, Cardiovascular Research and American Journal of Physiology-Heart and Circulatory Physiology.

In The Last Decade

Sarah E. Sweterlitsch

7 papers receiving 440 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sarah E. Sweterlitsch United States 6 206 143 123 113 104 7 445
Hiroyuki Kurogane Japan 10 231 1.1× 280 2.0× 147 1.2× 73 0.6× 110 1.1× 24 543
Els Busser Netherlands 7 195 0.9× 131 0.9× 258 2.1× 113 1.0× 104 1.0× 8 533
Takehisa Shimizu Japan 14 112 0.5× 130 0.9× 90 0.7× 221 2.0× 45 0.4× 23 575
Moira McCann United Kingdom 11 160 0.8× 222 1.6× 370 3.0× 213 1.9× 47 0.5× 19 732
Alexandre C. Zago Brazil 8 155 0.8× 123 0.9× 77 0.6× 188 1.7× 92 0.9× 12 591
David M. McClister United States 6 196 1.0× 103 0.7× 104 0.8× 160 1.4× 164 1.6× 6 410
Hideyuki Fujikawa Japan 11 325 1.6× 187 1.3× 94 0.8× 160 1.4× 64 0.6× 24 527
Takanori Kusuyama Japan 11 109 0.5× 109 0.8× 55 0.4× 140 1.2× 93 0.9× 20 405
Brijesh Bhambi United States 8 346 1.7× 147 1.0× 40 0.3× 169 1.5× 64 0.6× 12 497
Simone Mangan Australia 5 82 0.4× 85 0.6× 99 0.8× 200 1.8× 46 0.4× 7 451

Countries citing papers authored by Sarah E. Sweterlitsch

Since Specialization
Citations

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

Fields of papers citing papers by Sarah E. Sweterlitsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sarah E. Sweterlitsch. 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 Sarah E. Sweterlitsch. The network helps show where Sarah E. Sweterlitsch may publish in the future.

Co-authorship network of co-authors of Sarah E. Sweterlitsch

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

All Works

7 of 7 papers shown
1.
Mukherjee, Rick, et al.. (2005). Time-dependent changes in myocardial structure following discrete injury in mice deficient of matrix metalloproteinase-3. Journal of Molecular and Cellular Cardiology. 39(2). 259–268. 19 indexed citations
2.
Su, Haili, Francis G. Spinale, Lawrence W. Dobrucki, et al.. (2005). Noninvasive Targeted Imaging of Matrix Metalloproteinase Activation in a Murine Model of Postinfarction Remodeling. Circulation. 112(20). 3157–3167. 156 indexed citations
3.
Lindsey, Merry L., Christina E. Squires, Gustavo Escobar, et al.. (2004). Age-dependent changes in myocardial matrix metalloproteinase/tissue inhibitor of metalloproteinase profiles and fibroblast function. Cardiovascular Research. 66(2). 410–419. 135 indexed citations
4.
Mukherjee, Rupak, Joseph T. Mingoia, Sarah E. Sweterlitsch, et al.. (2004). Myocardial remodeling after discrete radiofrequency injury: effects of tissue inhibitor of matrix metalloproteinase-1 gene deletion. American Journal of Physiology-Heart and Circulatory Physiology. 286(4). H1242–H1247. 20 indexed citations
5.
Ikonomidis, John S., William C. Gibson, Jessica Butler, et al.. (2004). Effects of Deletion of the Tissue Inhibitor of Matrix Metalloproteinases-1 Gene on the Progression of Murine Thoracic Aortic Aneurysms. Circulation. 110(11_suppl_1). II268–73. 49 indexed citations
6.
Spinale, Francis G., Lawrence W. Dobrucki, Conroy Chow, et al.. (2004). Evaluation of myocardial matrix metalloproteinase (MMP) mediated post-MI remodeling with a novel radiolabeled MMP inhibitor. Journal of Nuclear Cardiology. 11(4). S20–S20. 4 indexed citations
7.
Ikonomidis, John S., William C. Gibson, JONATHAN GARDNER, et al.. (2003). A murine model of thoracic aortic aneurysms. Journal of Surgical Research. 115(1). 157–163. 62 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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2026