Mathias Walzer

18.1k total citations · 2 hit papers
20 papers, 4.9k citations indexed

About

Mathias Walzer is a scholar working on Molecular Biology, Spectroscopy and Information Systems and Management. According to data from OpenAlex, Mathias Walzer has authored 20 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 14 papers in Spectroscopy and 4 papers in Information Systems and Management. Recurrent topics in Mathias Walzer's work include Advanced Proteomics Techniques and Applications (14 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Mathias Walzer is often cited by papers focused on Advanced Proteomics Techniques and Applications (14 papers), Mass Spectrometry Techniques and Applications (12 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Mathias Walzer collaborates with scholars based in Germany, United Kingdom and United States. Mathias Walzer's co-authors include Yasset Pérez‐Riverol, Juan Antonio Vizcaíno, Ananth Prakash, Suresh Hewapathirana, Shengbo Wang, Selvakumar Kamatchinathan, Jingwen Bai, Chakradhar Bandla, Deepti J Kundu and Martin Eisenacher and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Mathias Walzer

19 papers receiving 4.9k 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.

The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences

2021 3.9k citations Yasset Pérez‐Riverol, Jingwen Bai et al. Nucleic Acids Research profile →
The PRIDE database at 20 years: 2025 update

2024 375 citations Yasset Pérez‐Riverol, Chakradhar Bandla et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mathias Walzer Germany	13	3.2k	796	518	467	395	20	4.9k
José A. Dianes United Kingdom	8	3.2k 1.0×	1000 1.3×	475 0.9×	429 0.9×	369 0.9×	11	5.0k
Ananth Prakash United Kingdom	11	3.2k 1.0×	477 0.6×	495 1.0×	480 1.0×	371 0.9×	18	4.9k
Tobias Ternent United Kingdom	8	2.6k 0.8×	731 0.9×	369 0.7×	359 0.8×	270 0.7×	9	3.9k
Dorothea Busse Germany	6	3.6k 1.2×	624 0.8×	662 1.3×	444 1.0×	387 1.0×	7	5.1k
Nadin Neuhauser Germany	6	3.4k 1.1×	1.3k 1.6×	448 0.9×	521 1.1×	379 1.0×	6	4.7k
Deepti J Kundu United Kingdom	6	2.7k 0.9×	452 0.6×	473 0.9×	456 1.0×	362 0.9×	9	4.4k
David García‐Seisdedos Spain	10	2.6k 0.8×	431 0.5×	441 0.9×	439 0.9×	379 1.0×	16	4.2k
Jingwen Bai China	5	2.7k 0.9×	416 0.5×	472 0.9×	451 1.0×	358 0.9×	6	4.4k
Shengbo Wang United Kingdom	5	2.7k 0.8×	430 0.5×	472 0.9×	454 1.0×	358 0.9×	6	4.3k
Christian A. Luber Germany	10	3.2k 1.0×	1.1k 1.3×	808 1.6×	529 1.1×	407 1.0×	10	5.2k

Countries citing papers authored by Mathias Walzer

Since Specialization

Citations

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

Fields of papers citing papers by Mathias Walzer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mathias Walzer

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

Pérez‐Riverol, Yasset, Chakradhar Bandla, Deepti J Kundu, et al.. (2024). The PRIDE database at 20 years: 2025 update. Nucleic Acids Research. 53(D1). D543–D553. 375 indexed citations breakdown →

Bielow, Chris, Nils Hoffmann, Tim Van Den Bossche, et al.. (2024). Communicating Mass Spectrometry Quality Information in mzQC with Python, R, and Java. Journal of the American Society for Mass Spectrometry. 35(8). 1875–1882. 4 indexed citations

Walzer, Mathias, Kyowon Jeong, David L. Tabb, & Juan Antonio Vizcaíno. (2023). TopDownApp: An open and modular platform for analysis and visualisation of top‐down proteomics data. PROTEOMICS. 24(3-4). e2200403–e2200403. 4 indexed citations

Walzer, Mathias, David García‐Seisdedos, Ananth Prakash, et al.. (2022). Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas. Scientific Data. 9(1). 335–335. 16 indexed citations

Pérez‐Riverol, Yasset, Jingwen Bai, Chakradhar Bandla, et al.. (2021). The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Research. 50(D1). D543–D552. 3918 indexed citations breakdown →

Dijkstra, Tjeerd M. H., Timo Sachsenberg, Lukas Zimmermann, et al.. (2020). OpenPepXL: An Open-Source Tool for Sensitive Identification of Cross-Linked Peptides in XL-MS. Molecular & Cellular Proteomics. 19(12). 2157–2168. 9 indexed citations

Hulstaert, Niels, Jim Shofstahl, Timo Sachsenberg, et al.. (2019). ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. Journal of Proteome Research. 19(1). 537–542. 141 indexed citations

Walzer, Mathias & Juan Antonio Vizcaíno. (2019). Review of Issues and Solutions to Data Analysis Reproducibility and Data Quality in Clinical Proteomics. Methods in molecular biology. 2051. 345–371. 5 indexed citations

Bittremieux, Wout, Mathias Walzer, Stefan Tenzer, et al.. (2017). The Human Proteome Organization–Proteomics Standards Initiative Quality Control Working Group: Making Quality Control More Accessible for Biological Mass Spectrometry. Analytical Chemistry. 89(8). 4474–4479. 17 indexed citations

10.

Vizcaíno, Juan Antonio, Gerhard Mayer, Simon Perkins, et al.. (2017). The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics. Molecular & Cellular Proteomics. 16(7). 1275–1285. 42 indexed citations

11.

Pfeuffer, Julianus, Timo Sachsenberg, Oliver Alka, et al.. (2017). OpenMS – A platform for reproducible analysis of mass spectrometry data. Journal of Biotechnology. 261. 142–148. 67 indexed citations

12.

Schubert, Benjamin, et al.. (2017). ImmunoNodes – graphical development of complex immunoinformatics workflows. BMC Bioinformatics. 18(1). 242–242. 8 indexed citations

13.

Deutsch, Eric W., Sandra Orchard, Pierre‐Alain Binz, et al.. (2017). Proteomics Standards Initiative: Fifteen Years of Progress and Future Work. Journal of Proteome Research. 16(12). 4288–4298. 56 indexed citations

14.

Kyzirakos, Christina, Christopher Mohr, Sorin Armeanu–Ebinger, et al.. (2016). Optimized neoantigen selection based on tumor exome data. Annals of Oncology. 27. vi375–vi375.

15.

Griss, Johannes, Yasset Pérez‐Riverol, David L. Tabb, et al.. (2016). Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nature Methods. 13(8). 651–656. 118 indexed citations

16.

Schubert, Benjamin, et al.. (2016). FRED 2: an immunoinformatics framework for Python. Bioinformatics. 32(13). 2044–2046. 29 indexed citations

17.

Aiche, Stephan, Timo Sachsenberg, Erhan Kenar, et al.. (2015). Workflows for automated downstream data analysis and visualization in large‐scale computational mass spectrometry. PROTEOMICS. 15(8). 1443–1447. 23 indexed citations

18.

Kohlbacher, Oliver, Rupert Handgretinger, Hans‐Georg Rammensee, et al.. (2013). iVacALL: utilizing next-generation sequencing for the establishment of an individual peptide vaccination approach for paediatric acute lymphoblastic leukaemia. Bone Marrow Transplantation. 48(3). 2 indexed citations

19.

Sturm, Theo, Trese Leinders‐Zufall, Boris Maček, et al.. (2013). Mouse urinary peptides provide a molecular basis for genotype discrimination by nasal sensory neurons. Nature Communications. 4(1). 1616–1616. 63 indexed citations

20.

Walzer, Mathias, Da Qi, Gerhard Mayer, et al.. (2013). The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics. Molecular & Cellular Proteomics. 12(8). 2332–2340. 47 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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