S. Takemoto

1.4k total citations
32 papers, 1.1k citations indexed

About

S. Takemoto is a scholar working on Transplantation, Surgery and Public Health, Environmental and Occupational Health. According to data from OpenAlex, S. Takemoto has authored 32 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Transplantation, 18 papers in Surgery and 8 papers in Public Health, Environmental and Occupational Health. Recurrent topics in S. Takemoto's work include Renal Transplantation Outcomes and Treatments (27 papers), Organ Transplantation Techniques and Outcomes (15 papers) and Transplantation: Methods and Outcomes (6 papers). S. Takemoto is often cited by papers focused on Renal Transplantation Outcomes and Treatments (27 papers), Organ Transplantation Techniques and Outcomes (15 papers) and Transplantation: Methods and Outcomes (6 papers). S. Takemoto collaborates with scholars based in United States, Canada and Belgium. S. Takemoto's co-authors include Krista L. Lentine, Mark A. Schnitzler, Brett Pinsky, Thomas E. Burroughs, Paolo R. Salvalaggio, Ralph C. Marcove, John H. Healey, Suphamai Bunnapradist, L Willoughby and P I Terasaki and has published in prestigious journals such as American Journal of Transplantation, Transfusion and The Journal of Heart and Lung Transplantation.

In The Last Decade

S. Takemoto

32 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
S. Takemoto United States 13 652 385 236 210 189 32 1.1k
Laetitia Albano France 17 546 0.8× 313 0.8× 154 0.7× 137 0.7× 158 0.8× 51 926
Alihan Gürkan Türkiye 17 218 0.3× 368 1.0× 205 0.9× 205 1.0× 56 0.3× 72 780
Jolanta Karpinski Canada 12 249 0.4× 150 0.4× 346 1.5× 123 0.6× 48 0.3× 30 635
Mary McGraw United Kingdom 14 223 0.3× 134 0.3× 168 0.7× 95 0.5× 54 0.3× 27 644
Yang‐Jen Chiang Taiwan 14 165 0.3× 178 0.5× 214 0.9× 122 0.6× 71 0.4× 83 713
J. Foutz United States 9 674 1.0× 940 2.4× 373 1.6× 186 0.9× 66 0.3× 15 1.6k
Syed Adibul Hasan Rizvi Pakistan 19 214 0.3× 363 0.9× 446 1.9× 518 2.5× 18 0.1× 59 1.2k
Edward M. Falta United States 11 191 0.3× 128 0.3× 137 0.6× 134 0.6× 51 0.3× 19 455
Cheri Hunter United States 11 222 0.3× 182 0.5× 224 0.9× 121 0.6× 25 0.1× 19 839
Jessica M. Ruck United States 15 232 0.4× 335 0.9× 241 1.0× 138 0.7× 46 0.2× 93 738

Countries citing papers authored by S. Takemoto

Since Specialization
Citations

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

Fields of papers citing papers by S. Takemoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Takemoto

This figure shows the co-authorship network connecting the top 25 collaborators of S. Takemoto. A scholar is included among the top collaborators of S. Takemoto 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. Takemoto. S. Takemoto 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.
Gill, Jagbir, et al.. (2009). Outcomes of Simultaneous Heart–Kidney Transplant in the US: A Retrospective Analysis Using OPTN/UNOS Data. American Journal of Transplantation. 9(4). 844–852. 76 indexed citations
2.
Pinsky, Brett, S. Takemoto, Krista L. Lentine, et al.. (2009). Transplant Outcomes and Economic Costs Associated with Patient Noncompliance to Immunosuppression. American Journal of Transplantation. 9(11). 2597–2606. 277 indexed citations
3.
Machnicki, Gerardo, Brett Pinsky, S. Takemoto, et al.. (2008). Predictive Ability of Pretransplant Comorbidities to Predict Long-Term Graft Loss and Death. American Journal of Transplantation. 9(3). 494–505. 47 indexed citations
4.
Salvalaggio, Paolo R., Mark A. Schnitzler, Kevin C. Abbott, et al.. (2007). Patient and Graft Survival Implications of Simultaneous Pancreas Kidney Transplantation From Old Donors. American Journal of Transplantation. 7(6). 1561–1571. 60 indexed citations
5.
Takemoto, S., Brett Pinsky, Mark A. Schnitzler, et al.. (2007). A Retrospective Analysis of Immunosuppression Compliance, Dose Reduction and Discontinuation in Kidney Transplant Recipients. American Journal of Transplantation. 7(12). 2704–2711. 162 indexed citations
6.
Kobashigawa, Jon, J. Patel, Hiroshi Furukawa, et al.. (2006). Five-Year Results of a Randomized, Single-Center Study of Tacrolimus vs Microemulsion Cyclosporine in Heart Transplant Patients. The Journal of Heart and Lung Transplantation. 25(4). 434–439. 71 indexed citations
7.
Bunnapradist, Suphamai & S. Takemoto. (2003). Controlling treatment allocation bias in a registry analysis when comparing calcineurin inhibitors. Transplantation Proceedings. 35(7). 2407–2408. 1 indexed citations
8.
Bradley, Benjamin, S. Takemoto, David Gjertson, Elaine F. Reed, & Michael Cecka. (2001). Elderly transplant recipients may require less immunosuppression. Transplantation Proceedings. 33(1-2). 1115–1116. 9 indexed citations
9.
Lee, Po‐Huang, et al.. (1998). HLA epitopes for kidney allocation. Transplantation Proceedings. 30(7). 3496–3497. 4 indexed citations
10.
Thompson, J. S., Leroy R. Thacker, & S. Takemoto. (1997). CREG matching for first kidney transplants performed by SEOPF centers between October 1987 and September 1995: An analysis of outcome and prospective benefit. Transplantation Proceedings. 29(1-2). 1435–1438. 10 indexed citations
11.
Terasaki, P I, et al.. (1997). Should excessive height and weight differences between the kidney donor and recipient be avoided?. Transplantation Proceedings. 29(1-2). 104–105. 13 indexed citations
12.
Takemoto, S.. (1996). HLA amino acid residue matching.. PubMed. 397–425. 12 indexed citations
13.
Terasaki, P I, et al.. (1995). Advances in kidney transplantation: 1985-1995.. PubMed. 487–501. 13 indexed citations
14.
Marcove, Ralph C., et al.. (1995). The treatment of aneurysmal bone cyst.. PubMed. 157–63. 177 indexed citations
15.
Takemoto, S., J. Michael Cecka, & Paul I. Terasaki. (1994). Permissible class I mismatches identified from 7-year kidney transplant successes with 4 AB mismatches. Human Immunology. 40. 17–17. 3 indexed citations
16.
Takemoto, S., et al.. (1993). Molecular matching for clinical kidney transplantation.. PubMed. 25(1 Pt 1). 206–206. 2 indexed citations
17.
Terasaki, Paul I., et al.. (1992). Landsteiner Award. HLA epitope matching. Transfusion. 32(8). 775–786. 14 indexed citations
18.
Takemoto, S., et al.. (1992). Effect of mismatching serologically defined residues on kidney transplant survival.. PubMed. 24(4). 1266–8. 4 indexed citations
19.
Terasaki, P I, et al.. (1991). Molecular HLA matching.. PubMed. 23(1 Pt 1). 365–7. 3 indexed citations
20.
Takemoto, S. & Terasaki Pi. (1990). HLA peptide matching.. PubMed. 23(4). 2039–42. 6 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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