Jan A. Hofmann

1.3k total citations
27 papers, 714 citations indexed

About

Jan A. Hofmann is a scholar working on Immunology, Hematology and Transplantation. According to data from OpenAlex, Jan A. Hofmann has authored 27 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Immunology, 13 papers in Hematology and 7 papers in Transplantation. Recurrent topics in Jan A. Hofmann's work include T-cell and B-cell Immunology (20 papers), Hematopoietic Stem Cell Transplantation (11 papers) and Immune Cell Function and Interaction (10 papers). Jan A. Hofmann is often cited by papers focused on T-cell and B-cell Immunology (20 papers), Hematopoietic Stem Cell Transplantation (11 papers) and Immune Cell Function and Interaction (10 papers). Jan A. Hofmann collaborates with scholars based in Germany, United States and United Kingdom. Jan A. Hofmann's co-authors include Alexander H. Schmidt, Vinzenz Lange, Jürgen Sauter, Julia Pingel, Kathrin Lang, Irina Böhme, Gerhard Ehninger, Daniel Baier, Bianca Schöne and Gerhard Schöfl and has published in prestigious journals such as PLoS ONE, Scientific Reports and Frontiers in Immunology.

In The Last Decade

Jan A. Hofmann

25 papers receiving 629 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan A. Hofmann Germany 15 443 244 144 120 61 27 714
Julia Pingel Germany 14 437 1.0× 291 1.2× 153 1.1× 117 1.0× 67 1.1× 27 715
Jürgen Sauter Germany 18 645 1.5× 287 1.2× 157 1.1× 153 1.3× 82 1.3× 61 1.1k
Irina Böhme Germany 7 285 0.6× 149 0.6× 91 0.6× 107 0.9× 59 1.0× 9 519
Bianca Schöne Germany 7 194 0.4× 103 0.4× 60 0.4× 74 0.6× 40 0.7× 12 360
Laëtitia Le Texier Australia 14 335 0.8× 75 0.3× 60 0.4× 95 0.8× 37 0.6× 30 586
Yana A. Wilson Australia 13 606 1.4× 364 1.5× 24 0.2× 103 0.9× 62 1.0× 19 978
Jacqueline D.H. Anholts Netherlands 17 542 1.2× 68 0.3× 139 1.0× 172 1.4× 71 1.2× 44 835
Zhuoer Lin United States 8 411 0.9× 178 0.7× 13 0.1× 71 0.6× 19 0.3× 11 532
José Luis Arroyo Spain 11 72 0.2× 124 0.5× 10 0.1× 34 0.3× 45 0.7× 33 362
Jason B. Williams United States 12 755 1.7× 24 0.1× 14 0.1× 262 2.2× 101 1.7× 14 998

Countries citing papers authored by Jan A. Hofmann

Since Specialization
Citations

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

Fields of papers citing papers by Jan A. Hofmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan A. Hofmann. 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 Jan A. Hofmann. The network helps show where Jan A. Hofmann may publish in the future.

Co-authorship network of co-authors of Jan A. Hofmann

This figure shows the co-authorship network connecting the top 25 collaborators of Jan A. Hofmann. A scholar is included among the top collaborators of Jan A. Hofmann 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 Jan A. Hofmann. Jan A. Hofmann 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.
Mack, Steven J., Martin Maiers, Jill A. Hollenbach, et al.. (2023). Genotype List String 1.1: Extending the Genotype List String grammar for describing HLA and Killer‐cell Immunoglobulin‐like Receptor genotypes. HLA. 102(2). 206–212. 3 indexed citations
2.
Behrens, Geoffrey A., Daniel Baier, Heike Fischer, et al.. (2022). Reanalysis of unclear CMV status results from buccal swab samples of potential stem cell donors is an efficient donor registry strategy. Transplant Immunology. 75. 101729–101729. 2 indexed citations
3.
Foss, Franziska, et al.. (2021). EphrinB2 and GRIP1 stabilize mushroom spines during denervation-induced homeostatic plasticity. Cell Reports. 34(13). 108923–108923. 11 indexed citations
4.
Marin, Wesley M., Ravi Dandekar, Danillo G. Augusto, et al.. (2021). High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING. PLoS Computational Biology. 17(8). e1008904–e1008904. 19 indexed citations
5.
Heidenreich, Falk, Vinzenz Lange, Jan A. Hofmann, et al.. (2021). CCR5Δ32 mutations do not determine COVID-19 disease course. International Journal of Infectious Diseases. 105. 653–655. 16 indexed citations
6.
Schmidt, Alexander H., et al.. (2020). Hap-E Search 2.0: Improving the Performance of a Probabilistic Donor-Recipient Matching Algorithm Based on Haplotype Frequencies. Frontiers in Medicine. 7. 32–32. 6 indexed citations
7.
Klußmeier, Anja, Jürgen Sauter, Jan A. Hofmann, et al.. (2020). High-Throughput MICA/B Genotyping of Over Two Million Samples: Workflow and Allele Frequencies. Frontiers in Immunology. 11. 314–314. 29 indexed citations
8.
Sauter, Jürgen, Ute V. Solloch, Anja Klußmeier, et al.. (2020). HLA-E typing of more than 2.5 million potential hematopoietic stem cell donors: Methods and population-specific allele frequencies. Human Immunology. 82(7). 541–547. 19 indexed citations
9.
Baier, Daniel, Jan A. Hofmann, Heike Fischer, et al.. (2018). Very low error rates of NGS-based HLA typing at stem cell donor recruitment question the need for a standard confirmatory typing step before donor work-up. Bone Marrow Transplantation. 54(6). 928–930. 15 indexed citations
10.
Schöfl, Gerhard, Bianca Schöne, Kathrin Lang, et al.. (2018). Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations. Frontiers in Immunology. 9. 2843–2843. 43 indexed citations
11.
Schöfl, Gerhard, Kathrin Lang, Irina Böhme, et al.. (2017). 2.7 million samples genotyped for HLA by next generation sequencing: lessons learned. BMC Genomics. 18(1). 161–161. 83 indexed citations
12.
Lang, Kathrin, Bianca Schöne, Gerhard Schöfl, et al.. (2016). ABO allele-level frequency estimation based on population-scale genotyping by next generation sequencing. BMC Genomics. 17(1). 374–374. 46 indexed citations
13.
Sauter, Jürgen, et al.. (2016). Simulation shows that HLA-matched stem cell donors can remain unidentified in donor searches. Scientific Reports. 6(1). 21149–21149. 17 indexed citations
14.
Lange, Vinzenz, Irina Böhme, Jan A. Hofmann, et al.. (2014). Cost-efficient high-throughput HLA typing by MiSeq amplicon sequencing. BMC Genomics. 15(1). 63–63. 199 indexed citations
15.
Maiers, Martin, Daniel Baier, Jan A. Hofmann, et al.. (2013). An update to the HLA Nomenclature Guidelines of the World Marrow Donor Association, 2012. Bone Marrow Transplantation. 48(11). 1387–1388. 9 indexed citations
16.
Lang, Kathrin, Irina Böhme, Vinzenz Lange, et al.. (2013). 8-OR. Human Immunology. 74. 8–8. 1 indexed citations
17.
Maiers, Martin, Loren Gragert, Abeer Madbouly, et al.. (2012). 16th IHIW: Global analysis of registry HLA haplotypes from 20 Million individuals: Report from the IHIW Registry Diversity Group. International Journal of Immunogenetics. 40(1). 66–71. 18 indexed citations
18.
Pingel, Julia, Ute V. Solloch, Jan A. Hofmann, et al.. (2012). High-resolution HLA haplotype frequencies of stem cell donors in Germany with foreign parentage: How can they be used to improve unrelated donor searches?. Human Immunology. 74(3). 330–340. 56 indexed citations
19.
Schmidt, Alexander H., Ute V. Solloch, Daniel Baier, et al.. (2011). Support of Unrelated Stem Cell Donor Searches by Donor Center-Initiated HLA Typing of Potentially Matching Donors. PLoS ONE. 6(5). e20268–e20268. 8 indexed citations
20.
Arora, Amit, et al.. (2011). Mechanistic Basis for RNA Aptamer‐Based Induction of TetR. ChemBioChem. 12(17). 2608–2614. 16 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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