Daniel Brändle

572 total citations
7 papers, 492 citations indexed

About

Daniel Brändle is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Pathology and Forensic Medicine. According to data from OpenAlex, Daniel Brändle has authored 7 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 2 papers in Radiology, Nuclear Medicine and Imaging and 1 paper in Pathology and Forensic Medicine. Recurrent topics in Daniel Brändle's work include T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (5 papers) and Immunotherapy and Immune Responses (5 papers). Daniel Brändle is often cited by papers focused on T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (5 papers) and Immunotherapy and Immune Responses (5 papers). Daniel Brändle collaborates with scholars based in Switzerland, United Kingdom and Belgium. Daniel Brändle's co-authors include Hans Hengartner, Christoph Müller, Hanspeter Pircher, Thomas Rülicke, Thierry Boon, B. Van den Eynde, F. Brasseur, P. Weynants, Hanspeter Pircher and Stefan Müller and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and European Journal of Immunology.

In The Last Decade

Daniel Brändle

7 papers receiving 486 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Brändle Switzerland 7 442 154 96 50 36 7 492
C. Huber Germany 6 305 0.7× 160 1.0× 148 1.5× 23 0.5× 28 0.8× 10 397
Giuseppe Consogno Italy 10 295 0.7× 149 1.0× 108 1.1× 33 0.7× 18 0.5× 14 373
Masaru Taniguchi Japan 7 424 1.0× 103 0.7× 110 1.1× 30 0.6× 24 0.7× 8 524
Saral N. Amarnani United States 8 477 1.1× 331 2.1× 201 2.1× 33 0.7× 60 1.7× 8 600
Moustapha El-Amine United States 8 209 0.5× 97 0.6× 101 1.1× 63 1.3× 84 2.3× 13 361
Theo Nicholaou Australia 5 357 0.8× 259 1.7× 107 1.1× 23 0.5× 19 0.5× 6 431
Kathleen C. Barracchini United States 9 544 1.2× 233 1.5× 206 2.1× 44 0.9× 52 1.4× 11 618
C M D'Urso Italy 6 241 0.5× 123 0.8× 103 1.1× 36 0.7× 15 0.4× 7 355
Olivier Peeters Belgium 5 467 1.1× 171 1.1× 312 3.3× 57 1.1× 27 0.8× 6 535
Christine Stemmer France 8 226 0.5× 108 0.7× 102 1.1× 44 0.9× 28 0.8× 10 352

Countries citing papers authored by Daniel Brändle

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Brändle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Brändle

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

All Works

7 of 7 papers shown
1.
Brändle, Daniel, Janine Bilsborough, Thomas Rülicke, et al.. (1998). The shared tumor-specific antigen encoded by mouse geneP1A is a target not only for cytolytic T lymphocytes but also for tumor rejection. European Journal of Immunology. 28(12). 4010–4019. 54 indexed citations
2.
Brändle, Daniel, F. Brasseur, P. Weynants, Thierry Boon, & B. Van den Eynde. (1996). A mutated HLA-A2 molecule recognized by autologous cytotoxic T lymphocytes on a human renal cell carcinoma.. The Journal of Experimental Medicine. 183(6). 2501–2508. 121 indexed citations
3.
Brändle, Daniel, Karin Brduscha‐Riem, Adrian Hayday, et al.. (1995). T cell development and repertoire of mice expressing a single T cell receptor α chain. European Journal of Immunology. 25(9). 2650–2655. 21 indexed citations
4.
Brändle, Daniel, Stefan Müller, Christoph Müller, Hans Hengartner, & Hanspeter Pircher. (1994). Regulation of RAG‐1 and CD69 expression in the thymus during positive and negative selection. European Journal of Immunology. 24(1). 145–151. 100 indexed citations
5.
Simpson, Elizabeth, Phillip J. Robinson, Phillip Chandler, et al.. (1994). Separation of thymic education from antigen presenting functions of major histocompatibility complex class I molecules.. PubMed. 81(1). 132–6. 13 indexed citations
6.
Brändle, Daniel, Christoph Müller, Thomas Rülicke, Hans Hengartner, & Hanspeter Pircher. (1992). Engagement of the T-cell receptor during positive selection in the thymus down-regulates RAG-1 expression.. Proceedings of the National Academy of Sciences. 89(20). 9529–9533. 120 indexed citations
7.
Brändle, Daniel, Kurt Bürki, Valerie A. Wallace, et al.. (1991). Involvement of both T cell receptor Vα and Vβ variable region domains and α chain junctional region in viral antigen recognition. European Journal of Immunology. 21(9). 2195–2202. 63 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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