Matt Tector

1.5k total citations
19 papers, 833 citations indexed

About

Matt Tector is a scholar working on Surgery, Genetics and Molecular Biology. According to data from OpenAlex, Matt Tector has authored 19 papers receiving a total of 833 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Surgery, 9 papers in Genetics and 7 papers in Molecular Biology. Recurrent topics in Matt Tector's work include Xenotransplantation and immune response (15 papers), T-cell and B-cell Immunology (5 papers) and Virus-based gene therapy research (4 papers). Matt Tector is often cited by papers focused on Xenotransplantation and immune response (15 papers), T-cell and B-cell Immunology (5 papers) and Virus-based gene therapy research (4 papers). Matt Tector collaborates with scholars based in United States, Sweden and Germany. Matt Tector's co-authors include José L. Estrada, James Butler, A. Joseph Tector, Andrew Adams, Richard A. Sidner, Gregory R. Martens, Joseph M. Ladowski, Luz M. Reyes, Mandy L. Ford and Devin E. Eckhoff and has published in prestigious journals such as The Journal of Immunology, Annals of Surgery and Transplantation.

In The Last Decade

Matt Tector

18 papers receiving 821 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matt Tector United States 10 669 479 281 130 37 19 833
Leela L. Paris United States 16 672 1.0× 458 1.0× 380 1.4× 78 0.6× 24 0.6× 20 926
Gregory R. Martens United States 13 567 0.8× 398 0.8× 216 0.8× 44 0.3× 29 0.8× 17 635
Gilda Chavez United Kingdom 12 772 1.2× 449 0.9× 160 0.6× 69 0.5× 67 1.8× 25 822
Hua Qian China 9 293 0.4× 179 0.4× 114 0.4× 41 0.3× 15 0.4× 16 422
Julia Greenstein United States 3 453 0.7× 270 0.6× 130 0.5× 84 0.6× 28 0.8× 3 512
Denis Lambrigts United States 7 408 0.6× 237 0.5× 88 0.3× 78 0.6× 47 1.3× 9 478
Peter L. Wigley Australia 10 285 0.4× 228 0.5× 271 1.0× 57 0.4× 9 0.2× 15 515
Ross L. Blankenship United States 9 440 0.7× 374 0.8× 290 1.0× 32 0.2× 14 0.4× 13 592
Wiebke Baars Germany 14 352 0.5× 251 0.5× 177 0.6× 117 0.9× 13 0.4× 20 484
Y. Ye United States 8 564 0.8× 297 0.6× 100 0.4× 45 0.3× 38 1.0× 9 601

Countries citing papers authored by Matt Tector

Since Specialization
Citations

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

Fields of papers citing papers by Matt Tector

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matt Tector

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

All Works

19 of 19 papers shown
1.
Estrada, Jose L., et al.. (2025). Generation of SLA-DQ Knockout Pigs and Screening for Anti-SLA-DQ Antibodies in Sera From Naïve and HLA Class II-sensitized Patients. Transplantation. 109(8). 1357–1366. 1 indexed citations
2.
Tector, A. Joseph, Matt Tector, Sabrina Copsel, et al.. (2025). Humoral Barrier to Preclinical and Clinical Xenotransplantation. Xenotransplantation. 32(3). e70056–e70056.
3.
Reyes, Luz M., et al.. (2024). Non‐Classical Swine Leukocyte Antigens SLA‐6, ‐7, and ‐8, Are Xenoantigens for Some Waitlisted Patients. Xenotransplantation. 31(3). e12872–e12872. 1 indexed citations
4.
Ladowski, Joseph M., Matt Tector, Zheng‐Yu Wang, et al.. (2024). Late graft failure of pig‐to‐rhesus renal xenografts has features of glomerulopathy and recipients have anti‐swine leukocyte antigen class I and class II antibodies. Xenotransplantation. 31(3). e12862–e12862. 5 indexed citations
5.
Adams, Andrew, Brendan P. Lovasik, Steven C. Kim, et al.. (2024). Iscalimab Combined With Transient Tesidolumab Prolongs Survival in Pig‐to‐Rhesus Monkey Renal Xenografts. Xenotransplantation. 31(4). e12880–e12880. 4 indexed citations
6.
Burlak, Christopher, Zheng‐Yu Wang, Greg Martens, et al.. (2023). Xenoreactive antibodies in α‐granules of human platelets bind pig liver endothelial cells. Xenotransplantation. 30(6). e12834–e12834. 2 indexed citations
7.
Wang, Zheng‐Yu, et al.. (2023). Patients on the Transplant Waiting List Have Anti-Swine Leukocyte Antigen Class I Antibodies. ImmunoHorizons. 7(9). 619–625. 13 indexed citations
8.
Tector, A. Joseph, Andrew Adams, & Matt Tector. (2022). Current Status of Renal Xenotransplantation and Next Steps. Kidney360. 4(2). 278–284. 14 indexed citations
9.
Ladowski, Joseph M., Gregory R. Martens, Luz M. Reyes, et al.. (2018). Examining the Biosynthesis and Xenoantigenicity of Class II Swine Leukocyte Antigen Proteins. The Journal of Immunology. 200(8). 2957–2964. 28 indexed citations
10.
Adams, Andrew, Steven C. Kim, Gregory R. Martens, et al.. (2018). Xenoantigen Deletion and Chemical Immunosuppression Can Prolong Renal Xenograft Survival. Annals of Surgery. 268(4). 564–573. 116 indexed citations
11.
Martens, Gregory R., Luz M. Reyes, James Butler, et al.. (2017). Humoral Reactivity of Renal Transplant-Waitlisted Patients to Cells From GGTA1/CMAH/B4GalNT2, and SLA Class I Knockout Pigs. Transplantation. 101(4). e86–e92. 161 indexed citations
12.
Estrada, José L., Andrew Adams, Kenneth A. Newell, et al.. (2015). Evaluation of human and non-human primate antibody binding to pig cells lacking GGTA1/CMAH/β4GalNT2 genes. PMC. 18 indexed citations
13.
Butler, James, Gregory R. Martens, Ping Li, et al.. (2015). The fate of human platelets exposed to porcine renal endothelium: a single-pass model of platelet uptake in domestic and genetically modified porcine organs. Journal of Surgical Research. 200(2). 698–706. 6 indexed citations
14.
Estrada, José L., Greg Martens, Ping Li, et al.. (2015). Evaluation of human and non‐human primate antibody binding to pig cells lacking GGTA1/CMAH/β4GalNT2 genes. Xenotransplantation. 22(3). 194–202. 305 indexed citations
15.
Paris, Leela L., Andrew J. Lutz, R.A. Sidner, et al.. (2014). Reduced Binding of Human Antibodies to Cells From GGTA1/CMAH KO Pigs. American Journal of Transplantation. 14(8). 1895–1900. 65 indexed citations
16.
Tector, Matt, et al.. (2009). Biochemical analysis of CTLA-4 immunoreactive material from human blood. BMC Immunology. 10(1). 51–51. 8 indexed citations
17.
Berry, Andrew, Matt Tector, & Martin K. Oaks. (2008). Lack of association between sCTLA-4 levels in human plasma and common CTLA-4 polymorphisms. Journal of Negative Results in BioMedicine. 7(1). 8–8. 16 indexed citations
18.
Chinnasamy, Dhanalakshmi, et al.. (2006). A mechanistic study of immune system activation by fusion of antigens with the ligand-binding domain of CTLA4. Cancer Immunology Immunotherapy. 55(12). 1504–1514. 5 indexed citations
19.
Zeh, Herbert J., Gerhard Leder, Michael T. Lotze, et al.. (1994). Flow-cytometric determination of peptide-class I complex formation identification of p53 peptides that bind to HLA-A2. Human Immunology. 39(2). 79–86. 65 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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