David F. Kiger

553 total citations
11 papers, 419 citations indexed

About

David F. Kiger is a scholar working on Transplantation, Surgery and Immunology. According to data from OpenAlex, David F. Kiger has authored 11 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Transplantation, 4 papers in Surgery and 4 papers in Immunology. Recurrent topics in David F. Kiger's work include Renal Transplantation Outcomes and Treatments (6 papers), T-cell and B-cell Immunology (4 papers) and Immune Cell Function and Interaction (4 papers). David F. Kiger is often cited by papers focused on Renal Transplantation Outcomes and Treatments (6 papers), T-cell and B-cell Immunology (4 papers) and Immune Cell Function and Interaction (4 papers). David F. Kiger collaborates with scholars based in United States and Netherlands. David F. Kiger's co-authors include Michael D. Gautreaux, Robert J. Stratta, P.L. Adams, Donald W. Bowden, Anthony J. Bleyer, Amber Reeves‐Daniel, Barry I. Freedman, Mariana Murea, Andrew A. Hicks and Carl D. Langefeld and has published in prestigious journals such as Annals of Surgery, Clinical Orthopaedics and Related Research and Transplantation.

In The Last Decade

David F. Kiger

10 papers receiving 414 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David F. Kiger United States	6	215	181	151	142	59	11	419
Suresh Raghavaiah United States	7	476 2.2×	183 1.0×	53 0.4×	245 1.7×	30 0.5×	10	605
Prince Mohan United States	10	98 0.5×	71 0.4×	57 0.4×	54 0.4×	6 0.1×	32	254
Robert J. Postlethwaite United Kingdom	8	48 0.2×	160 0.9×	45 0.3×	45 0.3×	20 0.3×	15	306
Günther F. Hillebrand Germany	6	462 2.1×	152 0.8×	59 0.4×	270 1.9×	7 0.1×	11	551
Marian D. Witvliet Netherlands	13	427 2.0×	85 0.5×	248 1.6×	283 2.0×	4 0.1×	18	680
N. Miyamoto Japan	11	270 1.3×	51 0.3×	162 1.1×	203 1.4×	17 0.3×	28	381
Emre Arpalı Türkiye	10	136 0.6×	34 0.2×	69 0.5×	159 1.1×	4 0.1×	34	320
Jakob Mühlbacher Austria	9	149 0.7×	38 0.2×	25 0.2×	120 0.8×	9 0.2×	27	294
P.G.P Machado Brazil	12	231 1.1×	70 0.4×	63 0.4×	133 0.9×	2 0.0×	29	343
Akihito Sannomiya Japan	9	250 1.2×	38 0.2×	136 0.9×	237 1.7×	3 0.1×	29	382

Countries citing papers authored by David F. Kiger

Since Specialization

Citations

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

Fields of papers citing papers by David F. Kiger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David F. Kiger. 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 David F. Kiger. The network helps show where David F. Kiger may publish in the future.

Co-authorship network of co-authors of David F. Kiger

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

All Works

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11 of 11 papers shown

1.

Gautreaux, Michael D., Socorro Mesa, David F. Kiger, & Cathi Murphey. (2025). Is it time to perform NGS HLA typing exclusively on deceased Donors?. Human Immunology. 86(2). 111253–111253.

2.

Gautreaux, Michael D., et al.. (2024). Identification of novel HLA alleles discovered in 2022–2023. Human Immunology. 85(3). 110772–110772. 2 indexed citations

3.

Kiger, David F., et al.. (2021). Identification of novel HLA alleles discovered in 2019–2021. Human Immunology. 82(12). 982–984. 3 indexed citations

4.

Kiger, David F., et al.. (2020). NGS and HLA: The long road ahead. Human Immunology. 81(6). 280–284. 14 indexed citations

5.

Kiger, David F., et al.. (2019). New HLA alleles discovered by next generation sequencing in routine histocompatibility lab work in a medium-volume laboratory. Human Immunology. 80(7). 465–467. 11 indexed citations

6.

Kucheryavaya, Anna Y., et al.. (2014). A Substantial Increase in Reporting of HLA-DPB Typing of Deceased Donors in US.. Transplantation. 98. 590–590. 3 indexed citations

7.

Reeves‐Daniel, Amber, Anthony J. Bleyer, Michael V. Rocco, et al.. (2011). The APOL1 Gene and Allograft Survival after Kidney Transplantation. American Journal of Transplantation. 11(5). 1025–1030. 235 indexed citations

8.

Stratta, Robert J., Aimee K. Sundberg, Michael S. Rohr, et al.. (2006). Optimal use of older donors and recipients in kidney transplantation. Surgery. 139(3). 324–333. 38 indexed citations

9.

Stratta, Robert J., Michael S. Rohr, Aimee K. Sundberg, et al.. (2006). Intermediate-Term Outcomes With Expanded Criteria Deceased Donors in Kidney Transplantation. Annals of Surgery. 243(5). 594–603. 95 indexed citations

10.

Ward, William G., Eugene R. Heise, Carol A. Boles, et al.. (2005). Human Leukocyte Antigen Sensitization after Structural Cortical Allograft Implantations. Clinical Orthopaedics and Related Research. &NA;(435). 31–35. 14 indexed citations

11.

Stratta, Robert J., Michael S. Rohr, Patricia L. Adams, et al.. (2003). Kidney and pancreas transplantation at Wake Forest University Baptist Medical Center.. PubMed. 229–45. 4 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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