Sebastian Boegel

3.6k total citations · 2 hit papers
24 papers, 2.5k citations indexed

About

Sebastian Boegel is a scholar working on Immunology, Molecular Biology and Cancer Research. According to data from OpenAlex, Sebastian Boegel has authored 24 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Immunology, 13 papers in Molecular Biology and 9 papers in Cancer Research. Recurrent topics in Sebastian Boegel's work include Immunotherapy and Immune Responses (11 papers), vaccines and immunoinformatics approaches (8 papers) and Cancer Genomics and Diagnostics (6 papers). Sebastian Boegel is often cited by papers focused on Immunotherapy and Immune Responses (11 papers), vaccines and immunoinformatics approaches (8 papers) and Cancer Genomics and Diagnostics (6 papers). Sebastian Boegel collaborates with scholars based in Germany, United States and Croatia. Sebastian Boegel's co-authors include Uğur Şahin, Martin Löwer, Mustafa Diken, Özlem Türeci, John C. Castle, Sebastian Kreiter, Niels van de Roemer, Jan Diekmann, Christoph Huber and Arbel D. Tadmor and has published in prestigious journals such as Nature, PLoS ONE and Cancer Research.

In The Last Decade

Sebastian Boegel

24 papers receiving 2.5k citations

Hit Papers

Mutant MHC class II epitopes drive therapeutic immune res... 2012 2026 2016 2021 2015 2012 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sebastian Boegel Germany 13 1.8k 1.5k 1.1k 282 219 24 2.5k
Timothy N. J. Bullock United States 31 2.1k 1.1× 1.4k 0.9× 798 0.8× 181 0.6× 299 1.4× 84 3.1k
Gregory Lizée United States 32 2.2k 1.2× 1.8k 1.2× 1.2k 1.2× 160 0.6× 157 0.7× 86 3.4k
Mathias Vormehr Germany 13 1.2k 0.7× 990 0.7× 850 0.8× 143 0.5× 136 0.6× 23 1.8k
Barbara Schrörs Germany 12 1.2k 0.7× 1.0k 0.7× 783 0.7× 175 0.6× 141 0.6× 23 1.7k
Fernando Aranda Spain 28 1.5k 0.8× 1.3k 0.9× 644 0.6× 116 0.4× 149 0.7× 76 2.5k
M. Ángela Aznar Spain 18 1.5k 0.8× 1.5k 1.0× 715 0.7× 103 0.4× 201 0.9× 23 2.5k
Rajasekharan Somasundaram United States 26 1.1k 0.6× 878 0.6× 869 0.8× 315 1.1× 181 0.8× 76 1.9k
Iñaki Etxeberría Spain 17 1.1k 0.6× 1.1k 0.7× 616 0.6× 106 0.4× 171 0.8× 25 1.9k
Deepak Mittal Australia 21 1.7k 0.9× 1.7k 1.1× 807 0.8× 107 0.4× 310 1.4× 28 3.1k
Leopoldo Luistro United States 15 1.1k 0.6× 1.0k 0.7× 777 0.7× 281 1.0× 114 0.5× 28 2.2k

Countries citing papers authored by Sebastian Boegel

Since Specialization
Citations

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

Fields of papers citing papers by Sebastian Boegel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sebastian Boegel

This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Boegel. A scholar is included among the top collaborators of Sebastian Boegel 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 Sebastian Boegel. Sebastian Boegel 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.
2.
Boegel, Sebastian, et al.. (2023). Transcriptome analysis of renal ischemia/reperfusion (I/R) injury in BAFF and BAFF-R deficient mice. PLoS ONE. 18(9). e0291619–e0291619. 1 indexed citations
3.
Boegel, Sebastian, John C. Castle, & Andreas Schwarting. (2021). Current status of use of high throughput nucleotide sequencing in rheumatology. RMD Open. 7(1). e001324–e001324. 5 indexed citations
4.
Schrörs, Barbara, Sebastian Boegel, Christian Albrecht, et al.. (2020). Multi-Omics Characterization of the 4T1 Murine Mammary Gland Tumor Model. Frontiers in Oncology. 10. 1195–1195. 141 indexed citations
5.
Boegel, Sebastian. (2020). Bioinformatics for Cancer Immunotherapy. Methods in molecular biology. 5 indexed citations
6.
Boegel, Sebastian, John C. Castle, Julia Kodysh, Timothy J. O’Donnell, & Alex Rubinsteyn. (2019). Bioinformatic methods for cancer neoantigen prediction. Progress in molecular biology and translational science. 164. 25–60. 29 indexed citations
7.
Boegel, Sebastian & John C. Castle. (2019). Human Leukocyte Antigen Typing Using High-Throughput DNA and RNA Sequencing and Application for Cell Line Identification. 2(1). 187–199. 1 indexed citations
8.
Boegel, Sebastian, Thomas Bukur, John C. Castle, & Uğur Şahin. (2018). In Silico Typing of Classical and Non-classical HLA Alleles from Standard RNA-Seq Reads. Methods in molecular biology. 1802. 177–191. 7 indexed citations
9.
Boegel, Sebastian, Martin Löwer, Thomas Bukur, et al.. (2018). HLA and proteasome expression body map. BMC Medical Genomics. 11(1). 36–36. 73 indexed citations
10.
Foerster, Friedrich, Sebastian Boegel, Rosario Heck, et al.. (2017). Enhanced protection of C57 BL/6 vs Balb/c mice to melanoma liver metastasis is mediated by NK cells. OncoImmunology. 7(4). e1409929–e1409929. 24 indexed citations
11.
Vormehr, Mathias, Sebastian Kreiter, Niels van de Roemer, et al.. (2016). Abstract A110: Mutant MHC class II epitopes drive therapeutic immune responses to cancer. Cancer Immunology Research. 4(1_Supplement). A110–A110. 1 indexed citations
12.
Vormehr, Mathias, et al.. (2015). Mutanome directed cancer immunotherapy. Current Opinion in Immunology. 39. 14–22. 48 indexed citations
13.
Kreiter, Sebastian, Mathias Vormehr, Niels van de Roemer, et al.. (2015). Mutant MHC class II epitopes drive therapeutic immune responses to cancer. Nature. 520(7549). 692–696. 915 indexed citations breakdown →
14.
Boegel, Sebastian, Jelle Scholtalbers, Martin Löwer, Uğur Şahin, & John C. Castle. (2015). In Silico HLA Typing Using Standard RNA-Seq Sequence Reads. Methods in molecular biology. 1310. 247–258. 11 indexed citations
15.
Scholtalbers, Jelle, Sebastian Boegel, Thomas Bukur, et al.. (2015). TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression. Genome Medicine. 7(1). 118–118. 57 indexed citations
16.
Castle, John C., Martin Löewer, Sebastian Boegel, et al.. (2014). Mutated tumor alleles are expressed according to their DNA frequency. Scientific Reports. 4(1). 4743–4743. 33 indexed citations
17.
Boegel, Sebastian, Martin Löwer, Thomas Bukur, Uğur Şahin, & John C. Castle. (2014). A catalog of HLA type, HLA expression, and neo-epitope candidates in human cancer cell lines. OncoImmunology. 3(8). e954893–e954893. 79 indexed citations
18.
Castle, John C., Martin Löewer, Sebastian Boegel, et al.. (2014). Immunomic, genomic and transcriptomic characterization of CT26 colorectal carcinoma. BMC Genomics. 15(1). 190–190. 280 indexed citations
19.
Castle, John C., Sebastian Kreiter, Jan Diekmann, et al.. (2012). Exploiting the Mutanome for Tumor Vaccination. Cancer Research. 72(5). 1081–1091. 617 indexed citations breakdown →
20.
Boegel, Sebastian, Martin Löwer, Michael K. E. Schäfer, et al.. (2012). HLA typing from RNA-Seq sequence reads. Genome Medicine. 4(12). 102–102. 170 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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