Lukas Mueller

4.0k total citations · 1 hit paper
19 papers, 3.1k citations indexed

About

Lukas Mueller is a scholar working on Molecular Biology, Spectroscopy and Strategy and Management. According to data from OpenAlex, Lukas Mueller has authored 19 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Spectroscopy and 2 papers in Strategy and Management. Recurrent topics in Lukas Mueller's work include Advanced Proteomics Techniques and Applications (12 papers), Mass Spectrometry Techniques and Applications (8 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). Lukas Mueller is often cited by papers focused on Advanced Proteomics Techniques and Applications (12 papers), Mass Spectrometry Techniques and Applications (8 papers) and Metabolomics and Mass Spectrometry Studies (6 papers). Lukas Mueller collaborates with scholars based in Switzerland, United States and Portugal. Lukas Mueller's co-authors include Ruedi Aebersold, Bernd Bodenmiller, Bruno Domon, Markus Mueller, Paola Picotti, Mi‐Youn Brusniak, Oliver Rinner, Alexander Schmidt, D.R. Mani and Markus Müller and has published in prestigious journals such as Cell, Nature Biotechnology and Nature Methods.

In The Last Decade

Lukas Mueller

18 papers receiving 3.1k citations

Hit Papers

Full Dynamic Range Proteome Analysis of S. cerevisiae by ... 2009 2026 2014 2020 2009 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lukas Mueller Switzerland 15 2.4k 1.8k 234 148 136 19 3.1k
Ute Distler Germany 25 2.0k 0.8× 875 0.5× 161 0.7× 95 0.6× 79 0.6× 66 3.1k
Jeffrey C. Silva United States 23 3.2k 1.3× 1.4k 0.7× 308 1.3× 87 0.6× 69 0.5× 32 4.5k
Gerhard Mayer Germany 12 2.4k 1.0× 835 0.5× 291 1.2× 67 0.5× 56 0.4× 15 3.5k
Toshitaka Sato Japan 13 1.6k 0.7× 878 0.5× 232 1.0× 68 0.5× 23 0.2× 21 2.5k
Nadin Neuhauser Germany 6 3.4k 1.4× 1.3k 0.7× 521 2.2× 111 0.8× 46 0.3× 6 4.7k
Hélian Boucherie France 23 2.7k 1.1× 731 0.4× 368 1.6× 172 1.2× 36 0.3× 49 3.5k
Wilfred H. Tang United States 12 1.5k 0.6× 780 0.4× 125 0.5× 110 0.7× 20 0.1× 16 2.3k
Sylvie Luche France 21 1.7k 0.7× 516 0.3× 234 1.0× 130 0.9× 25 0.2× 38 2.5k
Timo Glatter Germany 30 2.7k 1.1× 491 0.3× 485 2.1× 110 0.7× 282 2.1× 105 3.8k
Emanuele Alpi United Kingdom 11 1.6k 0.7× 493 0.3× 144 0.6× 62 0.4× 33 0.2× 14 2.3k

Countries citing papers authored by Lukas Mueller

Since Specialization
Citations

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

Fields of papers citing papers by Lukas Mueller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Mueller

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

All Works

19 of 19 papers shown
1.
Kohli, Bernhard M., Delphine Pflieger, Lukas Mueller, et al.. (2012). Interactome of the Amyloid Precursor Protein APP in Brain Reveals a Protein Network Involved in Synaptic Vesicle Turnover and a Close Association with Synaptotagmin-1. Journal of Proteome Research. 11(8). 4075–4090. 55 indexed citations
3.
Picotti, Paola, Bernd Bodenmiller, Lukas Mueller, Bruno Domon, & Ruedi Aebersold. (2009). Full Dynamic Range Proteome Analysis of S. cerevisiae by Targeted Proteomics. Cell. 138(4). 795–806. 608 indexed citations breakdown →
4.
Mirzaei, Hamid, et al.. (2009). Halogenated Peptides as Internal Standards (H-PINS). Molecular & Cellular Proteomics. 8(8). 1934–1946. 22 indexed citations
5.
Schoen, Wolfgang, et al.. (2009). Debt and Equity: What's the Difference? A Comparative View. SSRN Electronic Journal. 2 indexed citations
6.
Schiess, Ralph, Lukas Mueller, Alexander Schmidt, et al.. (2008). Analysis of Cell Surface Proteome Changes via Label-free, Quantitative Mass Spectrometry. Molecular & Cellular Proteomics. 8(4). 624–638. 75 indexed citations
7.
Letarte, Simon, David Campbell, James S. Eddes, et al.. (2008). Differential Plasma Glycoproteome of p19ARF Skin Cancer Mouse Model Using the Corra Label-Free LC-MS Proteomics Platform. Clinical Proteomics. 4(3-4). 105–116. 11 indexed citations
8.
Urwyler, Simon, Curdin Ragaz, Hookeun Lee, et al.. (2008). Proteome Analysis of Legionella Vacuoles Purified by Magnetic Immunoseparation Reveals Secretory and Endosomal GTPases. Traffic. 10(1). 76–87. 140 indexed citations
9.
Rinner, Oliver, Jan Seebacher, Thomas Walzthoeni, et al.. (2008). Identification of cross-linked peptides from large sequence databases. Nature Methods. 5(4). 315–318. 356 indexed citations
10.
Brusniak, Mi‐Youn, Bernd Bodenmiller, David Campbell, et al.. (2008). Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics. BMC Bioinformatics. 9(1). 542–542. 56 indexed citations
11.
Schmidt, Alexander, Nils Gehlenborg, Bernd Bodenmiller, et al.. (2008). An Integrated, Directed Mass Spectrometric Approach for In-depth Characterization of Complex Peptide Mixtures. Molecular & Cellular Proteomics. 7(11). 2138–2150. 114 indexed citations
12.
Mueller, Lukas, Mi‐Youn Brusniak, D.R. Mani, & Ruedi Aebersold. (2008). An Assessment of Software Solutions for the Analysis of Mass Spectrometry Based Quantitative Proteomics Data. Journal of Proteome Research. 7(1). 51–61. 352 indexed citations
13.
Bodenmiller, Bernd, Lukas Mueller, Patrick G. A. Pedrioli, et al.. (2007). An integrated chemical, mass spectrometric and computational strategy for (quantitative) phosphoproteomics: application to Drosophila melanogaster Kc167 cells. Molecular BioSystems. 3(4). 275–286. 68 indexed citations
14.
Mueller, Lukas, Oliver Rinner, Alexander Schmidt, et al.. (2007). SuperHirn – a novel tool for high resolution LC‐MS‐based peptide/protein profiling. PROTEOMICS. 7(19). 3470–3480. 262 indexed citations
15.
Bodenmiller, Bernd, Lukas Mueller, Markus Mueller, Bruno Domon, & Ruedi Aebersold. (2007). Reproducible isolation of distinct, overlapping segments of the phosphoproteome. Nature Methods. 4(3). 231–237. 484 indexed citations
16.
Bodenmiller, Bernd, Johan Malmström, Bertran Gerrits, et al.. (2007). PhosphoPep—a phosphoproteome resource for systems biology research in Drosophila Kc167 cells. Molecular Systems Biology. 3(1). 139–139. 161 indexed citations
17.
Rinner, Oliver, Lukas Mueller, Martin Hubálek, et al.. (2007). An integrated mass spectrometric and computational framework for the analysis of protein interaction networks. Nature Biotechnology. 25(3). 345–352. 137 indexed citations
18.
19.
Hendrickx, Larissa, et al.. (2005). Effect of nucleic acid stain Syto9 on nascent biofilm architecture of Acinetobacter sp. BD413. Water Science & Technology. 52(7). 195–202. 6 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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