Olga Vitek

10.5k total citations · 2 hit papers
99 papers, 6.4k citations indexed

About

Olga Vitek is a scholar working on Molecular Biology, Spectroscopy and Biomedical Engineering. According to data from OpenAlex, Olga Vitek has authored 99 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Molecular Biology, 65 papers in Spectroscopy and 5 papers in Biomedical Engineering. Recurrent topics in Olga Vitek's work include Advanced Proteomics Techniques and Applications (53 papers), Mass Spectrometry Techniques and Applications (51 papers) and Metabolomics and Mass Spectrometry Studies (49 papers). Olga Vitek is often cited by papers focused on Advanced Proteomics Techniques and Applications (53 papers), Mass Spectrometry Techniques and Applications (51 papers) and Metabolomics and Mass Spectrometry Studies (49 papers). Olga Vitek collaborates with scholars based in United States, Switzerland and Germany. Olga Vitek's co-authors include Ruedi Aebersold, Alexey I. Nesvizhskii, Ching-Yun Chang, Meena Choi, Timothy Clough, Brendan MacLean, Lukas Reiter, Ann L. Oberg, Lin‐Yang Cheng and Oliver Rinner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and PLoS ONE.

In The Last Decade

Olga Vitek

97 papers receiving 6.3k 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 Lin‐Yang Cheng, Olga Vitek et al. Molecular & Cellular Proteomics profile →
MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments

2014 667 citations Meena Choi, Ching-Yun Chang et al. Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Olga Vitek United States	40	4.2k	3.0k	599	320	287	99	6.4k
Matthew Chambers United States	22	4.3k 1.0×	2.7k 0.9×	250 0.4×	250 0.8×	326 1.1×	46	5.9k
Ludovic Gillet Switzerland	28	4.7k 1.1×	3.0k 1.0×	202 0.3×	310 1.0×	395 1.4×	39	6.3k
Hannes Röst United States	30	4.8k 1.1×	3.2k 1.1×	181 0.3×	315 1.0×	319 1.1×	66	6.7k
Brendan MacLean United States	35	6.5k 1.6×	4.3k 1.4×	368 0.6×	399 1.2×	533 1.9×	59	9.4k
Johannes Griss Austria	25	4.1k 1.0×	1.4k 0.5×	520 0.9×	438 1.4×	592 2.1×	61	6.5k
Parag Mallick United States	35	4.8k 1.2×	2.8k 0.9×	217 0.4×	274 0.9×	601 2.1×	98	7.3k
Xiaowen Liu China	48	3.4k 0.8×	1.7k 0.6×	226 0.4×	453 1.4×	276 1.0×	403	7.6k
Hyungwon Choi Singapore	40	4.7k 1.1×	1.5k 0.5×	310 0.5×	354 1.1×	335 1.2×	125	6.7k
Timothy J. Griffin United States	45	4.9k 1.2×	2.2k 0.7×	228 0.4×	334 1.0×	420 1.5×	158	7.8k
Florian Reisinger United Kingdom	26	5.2k 1.2×	1.9k 0.6×	553 0.9×	477 1.5×	669 2.3×	44	8.0k

Countries citing papers authored by Olga Vitek

Since Specialization

Citations

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

Fields of papers citing papers by Olga Vitek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olga Vitek

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

Gyori, Benjamin M. & Olga Vitek. (2024). Beyond protein lists: AI-assisted interpretation of proteomic investigations in the context of evolving scientific knowledge. Nature Methods. 21(8). 1387–1389. 5 indexed citations

Bronsert, Peter, et al.. (2024). MSIreg: an R package for unsupervised coregistration of mass spectrometry and H&E images. Bioinformatics. 40(11). 2 indexed citations

Föll, Melanie Christine, et al.. (2023). Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis. Nature Methods. 20(12). 1883–1886. 28 indexed citations

Saffo, David, et al.. (2022). Effective Use of Likert Scales in Visualization Evaluations: A Systematic Review. OSF Preprints (OSF Preprints). 10 indexed citations

Saffo, David, et al.. (2022). Effective Use of Likert Scales in Visualization Evaluations: A Systematic Review. Computer Graphics Forum. 41(3). 43–55. 69 indexed citations

Tsai, Tsung‐Heng, Erik Verschueren, Ting Huang, et al.. (2022). MSstatsPTM: Statistical Relative Quantification of Posttranslational Modifications in Bottom-Up Mass Spectrometry-Based Proteomics. Molecular & Cellular Proteomics. 22(1). 100477–100477. 17 indexed citations

Zucker, Jeremy, et al.. (2021). Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis. PubMed Central. 11 indexed citations

Tsai, Tsung‐Heng, Meena Choi, Balázs Bánfai, et al.. (2020). Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments. Molecular & Cellular Proteomics. 19(6). 944–959. 21 indexed citations

Huang, Ting, Meena Choi, Manuel Tzouros, et al.. (2020). MSstatsTMT: Statistical Detection of Differentially Abundant Proteins in Experiments with Isobaric Labeling and Multiple Mixtures. Molecular & Cellular Proteomics. 19(10). 1706–1723. 92 indexed citations

10.

Egertson, Jarrett D., Susan E. Abbatiello, Clark M. Henderson, et al.. (2018). Nonlinear Regression Improves Accuracy of Characterization of Multiplexed Mass Spectrometric Assays. Molecular & Cellular Proteomics. 17(5). 913–924. 20 indexed citations

11.

Tsai, Tsung‐Heng, Zhiqi Hao, Qiuting Hong, et al.. (2017). Statistical characterization of therapeutic protein modifications. Scientific Reports. 7(1). 7896–7896. 3 indexed citations

12.

Liu, Yansheng, Alfonso Buil, Ben C. Collins, et al.. (2015). Quantitative variability of 342 plasma proteins in a human twin population. Molecular Systems Biology. 11(2). 786–786. 236 indexed citations

13.

Rardin, Matthew J., Birgit Schilling, Brendan MacLean, et al.. (2015). MS1 Peptide Ion Intensity Chromatograms in MS2 (SWATH) Data Independent Acquisitions. Improving Post Acquisition Analysis of Proteomic Experiments. Molecular & Cellular Proteomics. 14(9). 2405–2419. 51 indexed citations

14.

Cerciello, Ferdinando, Meena Choi, Annalisa Nicastri, et al.. (2013). Identification of a seven glycopeptide signature for malignant pleural mesothelioma in human serum by selected reaction monitoring. Clinical Proteomics. 10(1). 16–16. 36 indexed citations

15.

Sabidó, Eduard, Oswald Quehenberger, Qin Shen, et al.. (2012). Targeted Proteomics of the Eicosanoid Biosynthetic Pathway Completes an Integrated Genomics-Proteomics-Metabolomics Picture of Cellular Metabolism. Molecular & Cellular Proteomics. 11(7). M111.014746–1. 36 indexed citations

16.

Chang, Ching-Yun, Paola Picotti, Ruth Hüttenhain, et al.. (2011). Protein Significance Analysis in Selected Reaction Monitoring (SRM) Measurements. Molecular & Cellular Proteomics. 11(4). M111.014662–M111.014662. 115 indexed citations

17.

Baxter, Ivan, Olga Vitek, Brett Lahner, et al.. (2008). The leaf ionome as a multivariable system to detect a plant's physiological status. Proceedings of the National Academy of Sciences. 105(33). 12081–12086. 235 indexed citations

18.

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

19.

Vitek, Olga, Chris Bailey‐Kellogg, Bruce Α. Craig, & Jan Vítek. (2006). Inferential backbone assignment for sparse data. Journal of Biomolecular NMR. 35(3). 187–208. 11 indexed citations

20.

Vitek, Olga, Jan Vítek, Bruce Α. Craig, & Chris Bailey‐Kellogg. (2004). Model-Based Assignment and Inference of Protein Backbone Nuclear Magnetic Resonances. Statistical Applications in Genetics and Molecular Biology. 3(1). 1–33. 9 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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