Oliver M. Bernhardt

3.7k total citations · 2 hit papers
18 papers, 2.2k citations indexed

About

Oliver M. Bernhardt is a scholar working on Molecular Biology, Spectroscopy and Oncology. According to data from OpenAlex, Oliver M. Bernhardt has authored 18 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 15 papers in Spectroscopy and 2 papers in Oncology. Recurrent topics in Oliver M. Bernhardt's work include Advanced Proteomics Techniques and Applications (15 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (11 papers). Oliver M. Bernhardt is often cited by papers focused on Advanced Proteomics Techniques and Applications (15 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (11 papers). Oliver M. Bernhardt collaborates with scholars based in United States, Germany and Switzerland. Oliver M. Bernhardt's co-authors include Lukas Reiter, Tejas Gandhi, Roland Bruderer, Olga Vitek, Lin‐Yang Cheng, Oliver Rinner, Yulia Butscheid, Saša M. Miladinović, Simon Messner and Tobias Ehrenberger and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Analytical Chemistry.

In The Last Decade

Oliver M. Bernhardt

15 papers receiving 2.2k 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.

Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues

2015 755 citations Roland Bruderer, Oliver M. Bernhardt et al. Molecular & Cellular Proteomics profile →
Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries

2020 257 citations Dorte B. Bekker‐Jensen, Oliver M. Bernhardt et al. Nature Communications profile →

Peers

Oliver M. Bernhardt

SPECT

ONCOL

PHYSI

Tejas Gandhi United States

Christoph Stingl Netherlands

Hasmik Keshishian United States

Isabell Bludau Germany

Tujin Shi United States

Daniel P. Zolg Germany

Josef Schwarz United Kingdom

Andreas‐David Brunner Germany

Vadim Demichev Germany

Marc Vaudel Norway

Tejas Gandhi United States

Oliver M. Bernhardt

1.3k ×0.8

951 ×0.8

SPECT

122 ×0.9

ONCOL

136 ×1.1

112 ×0.9

PHYSI

Citations per year, relative to Oliver M. Bernhardt Oliver M. Bernhardt (= 1×) peers Tejas Gandhi

Countries citing papers authored by Oliver M. Bernhardt

Since Specialization

Citations

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

Fields of papers citing papers by Oliver M. Bernhardt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oliver M. Bernhardt. 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 Oliver M. Bernhardt. The network helps show where Oliver M. Bernhardt may publish in the future.

Co-authorship network of co-authors of Oliver M. Bernhardt

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

All Works

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18 of 18 papers shown

Deng, Liulin, Brian Adamson, Kyle L. Fort, et al.. (2025). Enhancing Sensitivity in Low-Load Proteomics Orbitrap Workflows via SLIM Integration. Analytical Chemistry. 97(24). 12613–12622.

Bernhardt, Oliver M., Sander Willems, Ino D. Karemaker, et al.. (2025). Enhanced Identifications and Quantification Through Retention Time Down-Sampling in Fast-Cycling Diagonal-PASEF Methods. Molecular & Cellular Proteomics. 25(1). 101480–101480.

Šalovská, Barbora, Oliver M. Bernhardt, Pierre‐Luc Germain, et al.. (2025). A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy. Nature Communications. 16(1). 5034–5034. 2 indexed citations

Bons, Joanna, Jacob Rose, Tejas Gandhi, et al.. (2023). Substantial downregulation of mitochondrial and peroxisomal proteins during acute kidney injury revealed by data‐independent acquisition proteomics. PROTEOMICS. 24(5). e2300162–e2300162. 11 indexed citations

Tsai, Tsung‐Heng, Ting Huang, Nicholas Shulman, et al.. (2023). MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale. Journal of Proteome Research. 22(5). 1466–1482. 46 indexed citations

Bekker‐Jensen, Dorte B., Oliver M. Bernhardt, Alexander Hogrebe, et al.. (2020). Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries. Nature Communications. 11(1). 787–787. 257 indexed citations breakdown →

Baeza, Josue, Jing Fan, Michael J. Smallegan, et al.. (2020). Revealing Dynamic Protein Acetylation across Subcellular Compartments. Journal of Proteome Research. 19(6). 2404–2418. 25 indexed citations

Muntel, Jan, et al.. (2019). Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy. Molecular Omics. 15(5). 348–360. 115 indexed citations

Bruderer, Roland, Jan Muntel, Sebastian Müller, et al.. (2019). Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance. Molecular & Cellular Proteomics. 18(6). 1242–1254. 118 indexed citations

10.

Kolbowski, Lars, et al.. (2019). Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry. Molecular & Cellular Proteomics. 18(4). 786–795. 36 indexed citations

11.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics. Molecular & Cellular Proteomics. mcp.M116.065730–mcp.M116.065730. 4 indexed citations

12.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results. Molecular & Cellular Proteomics. 16(12). 2296–2309. 305 indexed citations

13.

Navarro, Pedro, Jörg Kuharev, Ludovic Gillet, et al.. (2016). A multicenter study benchmarks software tools for label-free proteome quantification. Nature Biotechnology. 34(11). 1130–1136. 244 indexed citations

14.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, & Lukas Reiter. (2016). High‐precision iRT prediction in the targeted analysis of data‐independent acquisition and its impact on identification and quantitation. PROTEOMICS. 16(15-16). 2246–2256. 96 indexed citations

15.

Selevsek, Nathalie, Ching-Yun Chang, Ludovic Gillet, et al.. (2015). Reproducible and Consistent Quantification of the Saccharomyces cerevisiae Proteome by SWATH-mass spectrometry *. Molecular & Cellular Proteomics. 14(3). 739–749. 139 indexed citations

16.

Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2015). Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues. Molecular & Cellular Proteomics. 14(5). 1400–1410. 755 indexed citations breakdown →

17.

Bernhardt, Oliver M., Roland Bruderer, Tejas Gandhi, et al.. (2015). General guidelines for validation of decoy models for HRM/DIA/SWATH as exemplified using spectronaut. 6.

18.

Bernhardt, Oliver M., Nathalie Selevsek, Ludovic Gillet, et al.. (2012). Spectronaut A fast and efficient algorithm for MRM-like processing of data independent acquisition (SWATH-MS) data. 5. 32 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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