George Rosenberger

8.6k total citations · 2 hit papers
36 papers, 3.8k citations indexed

About

George Rosenberger is a scholar working on Molecular Biology, Spectroscopy and Materials Chemistry. According to data from OpenAlex, George Rosenberger has authored 36 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 26 papers in Spectroscopy and 5 papers in Materials Chemistry. Recurrent topics in George Rosenberger's work include Advanced Proteomics Techniques and Applications (26 papers), Mass Spectrometry Techniques and Applications (18 papers) and Metabolomics and Mass Spectrometry Studies (17 papers). George Rosenberger is often cited by papers focused on Advanced Proteomics Techniques and Applications (26 papers), Mass Spectrometry Techniques and Applications (18 papers) and Metabolomics and Mass Spectrometry Studies (17 papers). George Rosenberger collaborates with scholars based in Switzerland, United States and Germany. George Rosenberger's co-authors include Ruedi Aebersold, Ben C. Collins, Ludovic Gillet, Hannes Röst, Christina Ludwig, Sabine Amon, Lars Malmström, Olga T. Schubert, Matthias Gstaiger and Yansheng Liu and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Nature Communications.

In The Last Decade

George Rosenberger

36 papers receiving 3.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Data‐independent acquisition‐based SWATH ‐ MS for quantitative proteomics: a tutorial

2018 719 citations Christina Ludwig, Ludovic Gillet et al. Molecular Systems Biology profile →
dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts

2022 202 citations Vadim Demichev, Łukasz Szyrwiel et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
George Rosenberger Switzerland	27	2.8k	2.1k	272	241	220	36	3.8k
Ben C. Collins Switzerland	28	3.0k 1.1×	2.2k 1.0×	290 1.1×	236 1.0×	249 1.1×	54	4.3k
Zhi Sun United States	24	3.0k 1.1×	1.8k 0.9×	262 1.0×	209 0.9×	228 1.0×	52	4.1k
Pedro Navarro Spain	17	3.0k 1.1×	2.2k 1.1×	202 0.7×	114 0.5×	188 0.9×	26	4.3k
Subhakar Dey United States	9	2.7k 1.0×	2.1k 1.0×	245 0.9×	84 0.3×	123 0.6×	15	3.8k
William M. Old United States	30	2.9k 1.0×	1.4k 0.7×	517 1.9×	93 0.4×	169 0.8×	56	3.8k
Hannes Hahne Germany	25	2.5k 0.9×	842 0.4×	178 0.7×	212 0.9×	176 0.8×	48	3.5k
Nicholas Shulman United States	14	3.1k 1.1×	1.5k 0.7×	316 1.2×	103 0.4×	452 2.1×	21	4.6k
Gregory L. Finney United States	7	2.7k 1.0×	1.4k 0.7×	245 0.9×	97 0.4×	188 0.9×	7	3.9k
Christina Ludwig Germany	27	2.4k 0.8×	953 0.5×	176 0.6×	331 1.4×	215 1.0×	94	3.4k

Countries citing papers authored by George Rosenberger

Since Specialization

Citations

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

Fields of papers citing papers by George Rosenberger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of George Rosenberger

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

All Works

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20 of 20 papers shown

Rosenberger, George, Mikko Turunen, Jing He, et al.. (2024). Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nature Communications. 15(1). 3909–3909. 6 indexed citations

Demichev, Vadim, Łukasz Szyrwiel, Fengchao Yu, et al.. (2022). dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. Nature Communications. 13(1). 3944–3944. 202 indexed citations breakdown →

Bludau, Isabell, Max Frank, Christian Dörig, et al.. (2021). Systematic detection of functional proteoform groups from bottom-up proteomic datasets. Nature Communications. 12(1). 3810–3810. 45 indexed citations

Chen, Qian, Mairene Coto‐Llerena, Aleksei Suslov, et al.. (2021). Interferon lambda 4 impairs hepatitis C viral antigen presentation and attenuates T cell responses. Nature Communications. 12(1). 4882–4882. 13 indexed citations

Bludau, Isabell, Moritz Heusel, Max Frank, et al.. (2020). Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes. Nature Protocols. 15(8). 2341–2386. 44 indexed citations

Robinson, Aaron, Aleksandra Binek, Vidya Venkatraman, et al.. (2020). Lysine and Arginine Protein Post-translational Modifications by Enhanced DIA Libraries: Quantification in Murine Liver Disease. Journal of Proteome Research. 19(10). 4163–4178. 14 indexed citations

Heusel, Moritz, Max Frank, Sabine Amon, et al.. (2020). A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Systems. 10(2). 133–155.e6. 51 indexed citations

Rosenberger, George, Moritz Heusel, Isabell Bludau, et al.. (2020). SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles. Cell Systems. 11(6). 589–607.e8. 29 indexed citations

Heusel, Moritz, Isabell Bludau, George Rosenberger, et al.. (2019). Complex‐centric proteome profiling by SEC ‐ SWATH ‐ MS. Molecular Systems Biology. 15(1). e8438–e8438. 92 indexed citations

10.

Ludwig, Christina, Ludovic Gillet, George Rosenberger, et al.. (2018). Data‐independent acquisition‐based SWATH ‐ MS for quantitative proteomics: a tutorial. Molecular Systems Biology. 14(8). e8126–e8126. 719 indexed citations breakdown →

11.

Schubert, Olga T., Hannes Röst, Ben C. Collins, George Rosenberger, & Ruedi Aebersold. (2017). Quantitative proteomics: challenges and opportunities in basic and applied research. Nature Protocols. 12(7). 1289–1294. 189 indexed citations

12.

Rosenberger, George, Yansheng Liu, Hannes Röst, et al.. (2017). Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nature Biotechnology. 35(8). 781–788. 96 indexed citations

13.

Guo, Tiannan, Petri Kouvonen, Ching Chiek Koh, et al.. (2015). Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nature Medicine. 21(4). 407–413. 272 indexed citations

14.

Walzthoeni, Thomas, Łukasz A. Joachimiak, George Rosenberger, et al.. (2015). xTract: software for characterizing conformational changes of protein complexes by quantitative cross-linking mass spectrometry. Nature Methods. 12(12). 1185–1190. 73 indexed citations

15.

Rosenberger, George, Christina Ludwig, Hannes Röst, Ruedi Aebersold, & Lars Malmström. (2014). aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data. Bioinformatics. 30(17). 2511–2513. 44 indexed citations

16.

Teleman, Johan, Hannes Röst, George Rosenberger, et al.. (2014). DIANA—algorithmic improvements for analysis of data-independent acquisition MS data. Bioinformatics. 31(4). 555–562. 69 indexed citations

17.

Wisniewska, M., Lotta Happonen, Fredrik Kahn, et al.. (2014). Functional and Structural Properties of a Novel Protein and Virulence Factor (Protein sHIP) in Streptococcus pyogenes. Journal of Biological Chemistry. 289(26). 18175–18188. 6 indexed citations

18.

Hüttenhain, Ruth, Silvia Šurinová, Reto Ossola, et al.. (2013). N-Glycoprotein SRMAtlas. Molecular & Cellular Proteomics. 12(4). 1005–1016. 39 indexed citations

19.

Kahraman, Abdullah, Franz Herzog, Alexander Leitner, et al.. (2013). Cross-Link Guided Molecular Modeling with ROSETTA. PLoS ONE. 8(9). e73411–e73411. 141 indexed citations

20.

Schubert, Olga T., Jeppe Mouritsen, Christina Ludwig, et al.. (2013). The Mtb Proteome Library: A Resource of Assays to Quantify the Complete Proteome of Mycobacterium tuberculosis. Cell Host & Microbe. 13(5). 602–612. 139 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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