Yasset Pérez‐Riverol

30.5k total citations · 5 hit papers
86 papers, 12.0k citations indexed

About

Yasset Pérez‐Riverol is a scholar working on Molecular Biology, Spectroscopy and Information Systems and Management. According to data from OpenAlex, Yasset Pérez‐Riverol has authored 86 papers receiving a total of 12.0k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Molecular Biology, 67 papers in Spectroscopy and 11 papers in Information Systems and Management. Recurrent topics in Yasset Pérez‐Riverol's work include Advanced Proteomics Techniques and Applications (66 papers), Mass Spectrometry Techniques and Applications (37 papers) and Metabolomics and Mass Spectrometry Studies (36 papers). Yasset Pérez‐Riverol is often cited by papers focused on Advanced Proteomics Techniques and Applications (66 papers), Mass Spectrometry Techniques and Applications (37 papers) and Metabolomics and Mass Spectrometry Studies (36 papers). Yasset Pérez‐Riverol collaborates with scholars based in United Kingdom, Germany and United States. Yasset Pérez‐Riverol's co-authors include Juan Antonio Vizcaíno, Henning Hermjakob, Attila Csordás, Johannes Griss, Rui Wang, Mathias Walzer, José A. Dianes, Florian Reisinger, Deepti J Kundu and Chakradhar Bandla and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Biotechnology.

In The Last Decade

Yasset Pérez‐Riverol

84 papers receiving 12.0k citations

Hit Papers

5 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 →
2016 update of the PRIDE database and its related tools

2015 3.0k citations Juan Antonio Vizcaíno, Attila Csordás et al. Nucleic Acids Research profile →
The Proteomics Identifications (PRIDE) database and associated tools: status in 2013

2012 1.6k citations Juan Antonio Vizcaíno, Attila Csordás et al. Nucleic Acids Research profile →
The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition

2016 654 citations Eric W. Deutsch, Attila Csordás 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
Yasset Pérez‐Riverol United Kingdom	29	8.0k	2.8k	1.0k	987	887	86	12.0k
Stefka Tyanova Germany	17	7.7k 1.0×	2.2k 0.8×	1.1k 1.1×	1.5k 1.5×	798 0.9×	25	11.8k
Martin R. Larsen Denmark	59	8.4k 1.0×	4.0k 1.5×	882 0.9×	1.2k 1.2×	773 0.9×	260	13.0k
Juan Antonio Vizcaíno United Kingdom	42	9.8k 1.2×	3.5k 1.3×	1.1k 1.1×	1.3k 1.3×	1.4k 1.6×	127	14.4k
Alexandre Zougman United Kingdom	24	6.2k 0.8×	2.1k 0.8×	763 0.7×	827 0.8×	767 0.9×	36	9.3k
Andrew Keller United States	30	7.9k 1.0×	4.2k 1.5×	1.1k 1.0×	1.0k 1.0×	544 0.6×	65	11.5k
Henning Hermjakob United Kingdom	54	12.8k 1.6×	4.3k 1.6×	1.1k 1.1×	1.0k 1.0×	945 1.1×	213	17.4k
Jüergen Cox Germany	31	8.2k 1.0×	4.3k 1.6×	716 0.7×	990 1.0×	495 0.6×	37	11.2k
Tamar Geiger Israel	43	8.9k 1.1×	2.7k 1.0×	1.1k 1.1×	1.6k 1.6×	544 0.6×	100	12.8k
Eugene Kolker United States	29	7.5k 0.9×	3.6k 1.3×	701 0.7×	826 0.8×	546 0.6×	94	10.8k
Marc R. Wilkins Australia	51	10.4k 1.3×	3.0k 1.1×	1.1k 1.1×	779 0.8×	1.8k 2.1×	232	15.3k

Countries citing papers authored by Yasset Pérez‐Riverol

Since Specialization

Citations

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

Fields of papers citing papers by Yasset Pérez‐Riverol

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yasset Pérez‐Riverol. 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 Yasset Pérez‐Riverol. The network helps show where Yasset Pérez‐Riverol may publish in the future.

Co-authorship network of co-authors of Yasset Pérez‐Riverol

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Kamatchinathan, Selvakumar, et al.. (2025). pridepy: A Python package to download and search data from PRIDE database. The Journal of Open Source Software. 10(107). 7563–7563.

Zheng, Ping, Enrique Audain, Henry Webel, et al.. (2025). Ibaqpy: A scalable Python package for baseline quantification in proteomics leveraging SDRF metadata. Journal of Proteomics. 317. 105440–105440. 2 indexed citations

Pérez‐Riverol, Yasset, Wout Bittremieux, William Stafford Noble, et al.. (2025). Open-Source and FAIR Research Software for Proteomics. Journal of Proteome Research. 24(5). 2222–2234. 6 indexed citations

Deutsch, Eric W., Nuno Bandeira, Yasset Pérez‐Riverol, et al.. (2025). The ProteomeXchange consortium in 2026: making proteomics data FAIR. Nucleic Acids Research. 54(D1). D459–D469.

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 →

Pfeuffer, Julianus, Hong Wang, Ping Zheng, et al.. (2024). quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data. Nature Methods. 21(9). 1603–1607. 26 indexed citations

Webel, Henry, Yasset Pérez‐Riverol, Annelaura Bach Nielsen, & Simon Rasmussen. (2024). Mass spectrometry-based proteomics data from thousands of HeLa control samples. Scientific Data. 11(1). 112–112. 6 indexed citations

Neely, Benjamin A., Yasset Pérez‐Riverol, & Magnus Palmblad. (2024). Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer. PubMed. 35(3). 1 indexed citations

Bossche, Tim Van Den, et al.. (2023). lesSDRF is more: maximizing the value of proteomics data through streamlined metadata annotation. Nature Communications. 14(1). 6743–6743. 23 indexed citations

10.

Gabriels, Ralf, Robbin Bouwmeester, Siegfried Gessulat, et al.. (2023). ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics. Journal of Proteome Research. 22(2). 632–636. 14 indexed citations

11.

Wang, Hong, Julianus Pfeuffer, Timo Sachsenberg, et al.. (2023). Tissue‐based absolute quantification using large‐scale TMT and LFQ experiments. PROTEOMICS. 23(20). e2300188–e2300188. 4 indexed citations

12.

Puyvelde, Bart Van, Simon Daled, Sander Willems, et al.. (2022). A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics. Scientific Data. 9(1). 126–126. 32 indexed citations

13.

Umer, Husen M., Enrique Audain, Yafeng Zhu, et al.. (2021). Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides. Bioinformatics. 38(5). 1470–1472. 15 indexed citations

14.

Sinitcyn, Pavel, Hamid Hamzeiy, Daniel N. Itzhak, et al.. (2021). MaxDIA enables library-based and library-free data-independent acquisition proteomics. Nature Biotechnology. 39(12). 1563–1573. 156 indexed citations

15.

Schmidt, Tobias, Patroklos Samaras, Viktoria Dorfer, et al.. (2021). Universal Spectrum Explorer: A Standalone (Web-)Application for Cross-Resource Spectrum Comparison. Journal of Proteome Research. 20(6). 3388–3394. 21 indexed citations

16.

Murillo, Jimmy Rodriguez, Indira Plá, Yasset Pérez‐Riverol, et al.. (2021). Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database. Cancers. 13(24). 6224–6224. 4 indexed citations

17.

Xu, Pan, Enrique Audain, Marc‐Phillip Hitz, et al.. (2020). The omics discovery REST interface. Nucleic Acids Research. 48(W1). W380–W384. 3 indexed citations

18.

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

19.

Deutsch, Eric W., Attila Csordás, Zhi Sun, et al.. (2016). The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition. Nucleic Acids Research. 45(D1). D1100–D1106. 654 indexed citations breakdown →

20.

Leprevost, Felipe da Veiga, et al.. (2014). On best practices in the development of bioinformatics software. Frontiers in Genetics. 5. 199–199. 39 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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