Maximiliane Hilger

2.0k citations
11 papers · 1.6k indexed · 1 hit paper · h-index 11
Topics
Advanced Proteomics Techniques and Applications (4 papers)Monoclonal and Polyclonal Antibodies Research (4 papers)Glycosylation and Glycoproteins Research (3 papers)

In The Last Decade

Maximiliane Hilger

11 papers receiving 1.6k citations

Hit Papers

A practical guide to the MaxQuant computational platform ...20092026201420202009200400600

Peers

Maximiliane Hilger
Comparison fields: 5 of 101
  • Molecular Biology 1.2k
  • Biochemistry 441
  • Spectroscopy 337
  • Cell Biology 257
  • Radiology, Nuclear Medicine and Imaging 196
Replace Horst Ahorn with:
Horst Ahorn Austria
Sandra L. Harper United States
Eric S. Witze United States
Jonathan Rameseder United States
Chunshui Zhou United States
Gregory J. Mize United States
Douglas H. Phanstiel United States
Rochelle C. J. D’Souza Germany
Dominic P. Byrne United Kingdom
Niklaas Colaert Belgium
Maximiliane Hilger relative to Horst Ahorn Austria Horst Ahorn's profile →
Citations per field
00.5×4.5×
Horst Ahorn · 1×
Citations per year

Countries citing papers authored by Maximiliane Hilger

Since Specialization
Citations

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

Fields of papers citing papers by Maximiliane Hilger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maximiliane Hilger

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 21
2 39
3 118
4 83
5 13
6 140
7 401
8 59
9
A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomicsbreakdown →
641
10 89
11 36

About Maximiliane Hilger

Maximiliane Hilger is a scholar working on Biochemistry, Spectroscopy and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and Glycosylation and Glycoproteins Research (3 papers). The work is most often cited by research in Biochemistry (441 citations), Spectroscopy (337 citations) and Molecular Biology (1.2k citations). Maximiliane Hilger has collaborated with scholars based in Germany, Switzerland and Denmark. Frequent co-authors include Matthias Mann, Ivan Matić, Jürgen Cox, Nagarjuna Nagaraj, Jesper V. Olsen, Matthias Selbach, Tobias C. Walther, Florian Wilfling, Robert V. Farese and Natalie Krahmer. Their work appears in journals such as PLoS ONE, Cell Metabolism and Nature Protocols.

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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