Christian Panse

2.9k total citations
57 papers, 1.9k citations indexed

About

Christian Panse is a scholar working on Molecular Biology, Spectroscopy and Computer Vision and Pattern Recognition. According to data from OpenAlex, Christian Panse has authored 57 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 20 papers in Spectroscopy and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Christian Panse's work include Advanced Proteomics Techniques and Applications (17 papers), Data Visualization and Analytics (15 papers) and Metabolomics and Mass Spectrometry Studies (13 papers). Christian Panse is often cited by papers focused on Advanced Proteomics Techniques and Applications (17 papers), Data Visualization and Analytics (15 papers) and Metabolomics and Mass Spectrometry Studies (13 papers). Christian Panse collaborates with scholars based in Switzerland, Germany and United States. Christian Panse's co-authors include Daniel A. Keim, Ralph Schlapbach, Stephen C. North, F. Bechstedt, Jonas Grossmann, Mike Sips, Bertran Gerrits, Paolo Nanni, Abderrezak Belabbes and J. Furthmüller and has published in prestigious journals such as Nano Letters, Bioinformatics and PLoS ONE.

In The Last Decade

Christian Panse

55 papers receiving 1.8k citations

Peers

Countries citing papers authored by Christian Panse

Since Specialization

Citations

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

Fields of papers citing papers by Christian Panse

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christian Panse

This figure shows the co-authorship network connecting the top 25 collaborators of Christian Panse. A scholar is included among the top collaborators of Christian Panse 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 Christian Panse. Christian Panse 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

#	Work	Indexed citations
1	A combination of phenotypic responses and genetic adaptations enables Staphylococcus aureus to withstand inhibitory molecules secreted by Pseudomonas aeruginosa 2025 ·mSystems ·(unknown), (unknown), (unknown), Lucy Poveda, Witold Wolski, Christian Panse, Ralph Schlapbach, Rolf Kümmerli, Jonas Grossmann	0
2	prolfquapp ─ A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics 2025 ·Journal of Proteome Research ·Witold Wolski, Jonas Grossmann, (unknown), Peter Leary, Can Türker, Paolo Nanni, Ralph Schlapbach, Christian Panse	1
3	A Multiyear Longitudinal Harmonization Study of Quality Controls in Mass Spectrometry Proteomics Core Facilities 2025 ·Journal of Proteome Research ·Cristina Chiva, Roger Olivella, An Staes, Teresa Mendes Maia, Christian Panse, Karel Stejskal, Thibaut Douché, Bérangère Lombard, (unknown), Damarys Loew, Karl Mechtler, Mariette Matondo, Mandy Rettel, Dominic Helm, Francis Impens, Simon Devos, Anna Shevchenko, Paolo Nanni, Eduard Sabidó	2
4	prolfqua : A Comprehensive R -Package for Proteomics Differential Expression Analysis 2023 ·Journal of Proteome Research ·Witold Wolski, Paolo Nanni, Jonas Grossmann, Maria d’Errico, Ralph Schlapbach, Christian Panse	33
5	Developmental stage-specific proteome analysis of the legume pod borer Maruca vitrata provides insights on relevant proteins 2023 ·International Journal of Biological Macromolecules ·(unknown), Bernd Roschitzki, Jonas Grossmann, Maniraj Rathinam, Laura Kunz, Witold Wolski, Christian Panse, (unknown), Ralph Schlapbach, Uma Rao, Rohini Sreevathsa	2
6	The rawrr R Package: Direct Access to Orbitrap Data and Beyond 2021 ·Journal of Proteome Research ·Tobias Kockmann, Christian Panse	21
7	Universal Spectrum Explorer: A Standalone (Web-)Application for Cross-Resource Spectrum Comparison 2021 ·Journal of Proteome Research ·Tobias Schmidt, Patroklos Samaras, Viktoria Dorfer, Christian Panse, Tobias Kockmann, Leon Bichmann, Bart Van Puyvelde, Yasset Pérez‐Riverol, Eric W. Deutsch, Bernhard Küster, Mathias Wilhelm	21
8	Unraveling the proteomic changes involved in the resistance response of Cajanus platycarpus to herbivory by Helicoverpa armigera 2020 ·Applied Microbiology and Biotechnology ·Maniraj Rathinam, Bernd Roschitzki, Jonas Grossmann, Pragya Mishra, Laura Kunz, Witold Wolski, Christian Panse, (unknown), Uma Rao, Ralph Schlapbach, Rohini Sreevathsa	13
9	Engineered peptide barcodes for in-depth analyses of binding protein libraries 2019 ·Nature Methods ·Pascal Egloff, Iwan Zimmermann, Fabian Arnold, Cedric A. J. Hutter, Damien Morger, Lennart Opitz, Lucy Poveda, (unknown), Christian Panse, Bernd Roschitzki, Markus A. Seeger	42
10	rawDiag: An R Package Supporting Rational LC–MS Method Optimization for Bottom-up Proteomics 2018 ·Journal of Proteome Research ·Christian Trachsel, Christian Panse, Tobias Kockmann, Witold Wolski, Jonas Grossmann, Ralph Schlapbach	25
11	specL - Prepare Peptide Spectrum Matches for Use in Targeted Proteomics 2014 ·Zurich Open Repository and Archive (University of Zurich) ·Christian Trachsel, Christian Panse, Jonas Grossmann	1
12	cosmiq - COmbining Single Masses Into Quantities 2014 ·Zurich Open Repository and Archive (University of Zurich) ·David Fischer, Christian Panse, Endre Laczkó	2
13	FCC – An automated rule-based processing tool for life science data 2013 ·PubMed ·Simon Barkow‐Oesterreicher, Can Türker, Christian Panse	18
14	Identification of Combinatorial Patterns of Post-Translational Modifications on Individual Histones in the Mouse Brain 2012 ·PLoS ONE ·Ry Y. Tweedie‐Cullen, Andrea M. Brunner, Jonas Grossmann, (unknown), (unknown), Paolo Nanni, Christian Panse, Isabelle M. Mansuy	124
15	Qualitative and Quantitative Analyses of Protein Phosphorylation in Naive and Stimulated Mouse Synaptosomal Preparations 2006 ·Molecular & Cellular Proteomics ·(unknown), Ry Y. Tweedie‐Cullen, Magdalena Livingstone-Zatchej, (unknown), (unknown), (unknown), Peter Gehrig, Frańk Potthast, Dorothea Rutishauser, Bertran Gerrits, Christian Panse, Ralph Schlapbach, Isabelle M. Mansuy	187
16	Medial-Axis-Based Cartograms 2005 ·IEEE Computer Graphics and Applications ·Daniel A. Keim, Christian Panse, Stephen C. North	28
17	Exploring and Visualizing the History of InfoVis 2004 ·Daniel A. Keim, (unknown), Christian Panse, (unknown), Mike Sips	9
18	Geo-Spatial Data Viewer: From Familiar Land-covering to Arbitrary Distorted Geo-Spatial Quadtree Maps 2004 ·KOPS (University of Konstanz) ·Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips	4
19	Visual Data Mining in Large Geospatial Point Sets 2004 ·IEEE Computer Graphics and Applications ·Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North	47
20	HistoScale: An Efficient Approach for Computing Pseudo-Cartograms 2003 ·IEEE Visualization ·Daniel A. Keim, Christian Panse, Mathias Schäfer, Mike Sips, Stephen C. North	10

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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