Karin Leiderman

1.5k total citations
40 papers, 1.1k citations indexed

About

Karin Leiderman is a scholar working on Hematology, Pulmonary and Respiratory Medicine and Condensed Matter Physics. According to data from OpenAlex, Karin Leiderman has authored 40 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Hematology, 14 papers in Pulmonary and Respiratory Medicine and 9 papers in Condensed Matter Physics. Recurrent topics in Karin Leiderman's work include Platelet Disorders and Treatments (14 papers), Blood properties and coagulation (13 papers) and Blood Coagulation and Thrombosis Mechanisms (11 papers). Karin Leiderman is often cited by papers focused on Platelet Disorders and Treatments (14 papers), Blood properties and coagulation (13 papers) and Blood Coagulation and Thrombosis Mechanisms (11 papers). Karin Leiderman collaborates with scholars based in United States and Denmark. Karin Leiderman's co-authors include Aaron L. Fogelson, Alisa S. Wolberg, Kellie R. Machlus, Maria M. Aleman, Sarah D. Olson, Keith B. Neeves, Bridget S. Wilson, Janet M. Oliver, Jorge A. Di Paola and Stanly Steinberg and has published in prestigious journals such as Blood, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Karin Leiderman

38 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karin Leiderman United States 16 406 339 195 178 151 40 1.1k
Josie Carberry Australia 14 379 0.9× 366 1.1× 387 2.0× 222 1.2× 115 0.8× 36 1.4k
N Tatsumi Japan 22 226 0.6× 105 0.3× 38 0.2× 214 1.2× 18 0.1× 128 1.4k
Giles R. Cokelet United States 22 262 0.6× 1.1k 3.4× 230 1.2× 416 2.3× 27 0.2× 48 2.0k
Prosenjit Bagchi United States 32 422 1.0× 1.6k 4.7× 113 0.6× 567 3.2× 8 0.1× 62 2.9k
Toshihiko Sugiura Japan 19 17 0.0× 588 1.7× 339 1.7× 278 1.6× 157 1.0× 193 1.4k
R. H. Anderson United States 23 457 1.1× 409 1.2× 927 4.8× 100 0.6× 479 3.2× 64 2.0k
Brad Johnson United States 29 17 0.0× 1.2k 3.4× 277 1.4× 181 1.0× 165 1.1× 92 2.4k
Sandeep Saha United States 17 19 0.0× 191 0.6× 176 0.9× 78 0.4× 6 0.0× 56 1.2k
James Cooper United States 17 224 0.6× 117 0.3× 48 0.2× 57 0.3× 79 0.5× 80 961
R. T. Yen United States 17 21 0.1× 393 1.2× 267 1.4× 183 1.0× 25 0.2× 25 864

Countries citing papers authored by Karin Leiderman

Since Specialization
Citations

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

Fields of papers citing papers by Karin Leiderman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karin Leiderman

This figure shows the co-authorship network connecting the top 25 collaborators of Karin Leiderman. A scholar is included among the top collaborators of Karin Leiderman 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 Karin Leiderman. Karin Leiderman 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.
Monroe, Dougald M., et al.. (2025). Mathematical analysis of emicizumab: affinity-driven complex formation and lipid-surface reactions. Journal of Thrombosis and Haemostasis. 23(10). 3111–3123.
2.
Nicely, Nathan I., Ashutosh Tripathy, Ruian Ke, et al.. (2024). Stoichiometry for entry and binding properties of the Env protein of R5 T cell-tropic HIV-1 and its evolutionary variant of macrophage-tropic HIV-1. mBio. 15(4). e0032124–e0032124. 3 indexed citations
3.
Miyazawa, Kenji, Alan E. Mast, Adam R. Wufsus, et al.. (2024). Examining downstream effects of concizumab in hemophilia A with a mathematical modeling approach. Journal of Thrombosis and Haemostasis. 23(2). 480–491.
4.
Neeves, Keith B., et al.. (2024). Mathematical modeling identifies clotting factor combinations that modify thrombin generation in normal and factor VIII-, IX-, or XI-deficient blood. Research and Practice in Thrombosis and Haemostasis. 8(7). 102570–102570. 2 indexed citations
5.
Montgomery, David, et al.. (2023). clotFoam: An open-source framework to simulate blood clot formation under arterial flow. SoftwareX. 23. 101483–101483. 3 indexed citations
6.
Miyazawa, Kenji, Aaron L. Fogelson, & Karin Leiderman. (2022). Inhibition of platelet-surface-bound proteins during coagulation under flow I: TFPI. Biophysical Journal. 122(1). 99–113. 7 indexed citations
7.
Leiderman, Karin, et al.. (2022). Mathematical modeling to understand the role of bivalent thrombin-fibrin binding during polymerization. PLoS Computational Biology. 18(9). e1010414–e1010414. 3 indexed citations
8.
Leiderman, Karin, et al.. (2020). Minimal model of the hydrodynamical coupling of flagella on a spherical body with application toVolvox. Physical review. E. 102(3). 33114–33114. 7 indexed citations
9.
Monroe, Dougald M., et al.. (2019). Assessing the impact of product inhibition in a chromogenic assay. Analytical Biochemistry. 580. 62–71. 2 indexed citations
10.
Leiderman, Karin, et al.. (2019). A Mathematical Model of Bivalent Binding Suggests Physical Trapping of Thrombin within Fibrin Fibers. Biophysical Journal. 117(8). 1442–1455. 8 indexed citations
11.
Manco‐Johnson, Marilyn J., Jorge A. Di Paola, Suzanne Sindi, et al.. (2019). A mathematical model of coagulation under flow identifies factor V as a modifier of thrombin generation in hemophilia A. Journal of Thrombosis and Haemostasis. 18(2). 306–317. 23 indexed citations
12.
Paola, Jorge Di, et al.. (2018). A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow. PLoS ONE. 13(7). e0200917–e0200917. 52 indexed citations
13.
Fauci, Lisa, et al.. (2018). Mixing and pumping by pairs of helices in a viscous fluid. Physical review. E. 97(2). 23101–23101. 8 indexed citations
14.
Olson, Sarah D., et al.. (2016). Swimming speeds of filaments in viscous fluids with resistance. Physical review. E. 93(4). 43108–43108. 15 indexed citations
15.
Leiderman, Karin & Aaron L. Fogelson. (2014). An overview of mathematical modeling of thrombus formation under flow. Thrombosis Research. 133. S12–S14. 43 indexed citations
16.
Leiderman, Karin, Aaron L. Fogelson, Michael Wang, et al.. (2013). The Effect of Factor VIII Deficiencies and Replacement and Bypass Therapies on Thrombus Formation under Venous Flow Conditions in Microfluidic and Computational Models. PLoS ONE. 8(11). e78732–e78732. 47 indexed citations
17.
Wolberg, Alisa S., Maria M. Aleman, Karin Leiderman, & Kellie R. Machlus. (2011). Procoagulant Activity in Hemostasis and Thrombosis. Anesthesia & Analgesia. 114(2). 275–285. 230 indexed citations
18.
Leiderman, Karin & Aaron L. Fogelson. (2010). Grow with the flow: a spatial-temporal model of platelet deposition and blood coagulation under flow. Mathematical Medicine and Biology A Journal of the IMA. 28(1). 47–84. 183 indexed citations
19.
Leiderman, Karin, Laura Miller, & Aaron L. Fogelson. (2008). The effects of spatial inhomogeneities on flow through the endothelial surface layer. Journal of Theoretical Biology. 252(2). 313–325. 20 indexed citations
20.

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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