Oliver M. Crook

1.4k total citations · 2 hit papers
26 papers, 720 citations indexed

About

Oliver M. Crook is a scholar working on Molecular Biology, Spectroscopy and Epidemiology. According to data from OpenAlex, Oliver M. Crook has authored 26 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 12 papers in Spectroscopy and 3 papers in Epidemiology. Recurrent topics in Oliver M. Crook's work include Advanced Proteomics Techniques and Applications (9 papers), Mass Spectrometry Techniques and Applications (8 papers) and Protein Structure and Dynamics (3 papers). Oliver M. Crook is often cited by papers focused on Advanced Proteomics Techniques and Applications (9 papers), Mass Spectrometry Techniques and Applications (8 papers) and Protein Structure and Dynamics (3 papers). Oliver M. Crook collaborates with scholars based in United Kingdom, Belgium and United States. Oliver M. Crook's co-authors include Kathryn S. Lilley, Lisa M. Breckels, Laurent Gatto, Claire M. Mulvey, Tom Smith, Konstantin Barylyuk, Ross F. Waller, Aikaterini Geladaki, Nina Kočevar Britovšek and Eelco C. Tromer and has published in prestigious journals such as Science, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Oliver M. Crook

25 papers receiving 716 citations

Hit Papers

align trajectories sort by overperformance

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.

A Comprehensive Subcellular Atlas of the Toxoplasma Proteome via hyperLOPIT Provides Spatial Context for Protein Functions

2020 205 citations Konstantin Barylyuk, Luděk Kořený et al. Cell Host & Microbe profile →
Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

2024 56 citations Oliver M. Crook et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Oliver M. Crook United Kingdom	13	400	209	202	145	136	26	720
Carlos Madrid-Aliste United States	13	368 0.9×	131 0.6×	44 0.2×	21 0.1×	97 0.7×	19	607
Kristian E. Swearingen United States	14	426 1.1×	94 0.4×	263 1.3×	25 0.2×	120 0.9×	26	941
P. Bieri Switzerland	10	1.1k 2.8×	26 0.1×	105 0.5×	38 0.3×	77 0.6×	10	1.2k
Hayley M. Bennett United Kingdom	10	310 0.8×	137 0.7×	42 0.2×	17 0.1×	38 0.3×	15	656
Srinivasan Ramakrishnan United States	8	275 0.7×	249 1.2×	15 0.1×	55 0.4×	218 1.6×	10	553
Ian T. Foe United States	12	300 0.8×	79 0.4×	11 0.1×	90 0.6×	95 0.7×	15	517
Todd Minning United States	14	612 1.5×	163 0.8×	92 0.5×	22 0.2×	767 5.6×	18	1.2k
Karen M. Grant United Kingdom	16	529 1.3×	59 0.3×	41 0.2×	60 0.4×	366 2.7×	31	1.1k
Eva Růčková Czechia	10	347 0.9×	41 0.2×	16 0.1×	76 0.5×	191 1.4×	12	694
Martín Graña Uruguay	17	552 1.4×	69 0.3×	18 0.1×	92 0.6×	70 0.5×	36	799

Countries citing papers authored by Oliver M. Crook

Since Specialization

Citations

This map shows the geographic impact of Oliver M. Crook'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. Crook 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. Crook more than expected).

Fields of papers citing papers by Oliver M. Crook

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

This figure shows the co-authorship network connecting the top 25 collaborators of Oliver M. Crook. A scholar is included among the top collaborators of Oliver M. Crook 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. Crook. Oliver M. Crook 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

Crook, Oliver M., et al.. (2026). Biological data governance in an age of AI. Science. 391(6785). 558–561.

Vanderaa, Christophe, et al.. (2025). msqrob2TMT: Robust Linear Mixed Models for Inferring Differential Abundant Proteins in Labeled Experiments With Arbitrarily Complex Design. Molecular & Cellular Proteomics. 24(7). 101002–101002. 1 indexed citations

Breckels, Lisa M., et al.. (2024). Global Proteomics Indicates Subcellular-Specific Anti-Ferroptotic Responses to Ionizing Radiation. Molecular & Cellular Proteomics. 24(1). 100888–100888. 4 indexed citations

Barylyuk, Konstantin, Eelco C. Tromer, Oliver M. Crook, et al.. (2023). Mapping diversity in African trypanosomes using high resolution spatial proteomics. Nature Communications. 14(1). 4401–4401. 13 indexed citations

Guérin, Amandine, Konstantin Barylyuk, Laurence Berry, et al.. (2023). Cryptosporidium uses multiple distinct secretory organelles to interact with and modify its host cell. Cell Host & Microbe. 31(4). 650–664.e6. 46 indexed citations

Villanueva, Eneko, Tom Smith, Mariavittoria Pizzinga, et al.. (2023). System-wide analysis of RNA and protein subcellular localization dynamics. Nature Methods. 21(1). 60–71. 29 indexed citations

Crook, Oliver M., et al.. (2023). A Functional Bayesian Model for Hydrogen–Deuterium Exchange Mass Spectrometry. Journal of Proteome Research. 22(9). 2959–2972. 3 indexed citations

Crook, Oliver M., et al.. (2022). Improving lab-of-origin prediction of genetically engineered plasmids via deep metric learning. Nature Computational Science. 2(4). 253–264. 4 indexed citations

Crook, Oliver M., Colin Davies, Lisa M. Breckels, et al.. (2022). Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE. Nature Communications. 13(1). 5948–5948. 12 indexed citations

10.

Crook, Oliver M., Chun‐wa Chung, & Charlotte M. Deane. (2022). Empirical Bayes functional models for hydrogen deuterium exchange mass spectrometry. Communications Biology. 5(1). 588–588. 5 indexed citations

11.

Crook, Oliver M., Christine H. Chung, Christopher W. Bakerlee, et al.. (2022). Analysis of the first genetic engineering attribution challenge. Nature Communications. 13(1). 7374–7374. 6 indexed citations

12.

Braccia, Clarissa, Oliver M. Crook, Lisa M. Breckels, et al.. (2022). CFTR Rescue by Lumacaftor (VX-809) Induces an Extensive Reorganization of Mitochondria in the Cystic Fibrosis Bronchial Epithelium. Cells. 11(12). 1938–1938. 8 indexed citations

13.

Mulvey, Claire M., Lisa M. Breckels, Oliver M. Crook, et al.. (2021). Spatiotemporal proteomic profiling of the pro-inflammatory response to lipopolysaccharide in the THP-1 human leukaemia cell line. Nature Communications. 12(1). 5773–5773. 36 indexed citations

14.

Fang, Siqi, Paul Kirk, Marcus Bantscheff, Kathryn S. Lilley, & Oliver M. Crook. (2021). A Bayesian semi-parametric model for thermal proteome profiling. Communications Biology. 4(1). 810–810. 12 indexed citations

15.

Shin, John J. H., Oliver M. Crook, Jérôme Cattin‐Ortolá, et al.. (2020). Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers. Nature Communications. 11(1). 5987–5987. 49 indexed citations

16.

Crook, Oliver M., et al.. (2020). A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection. PLoS Computational Biology. 16(11). e1008288–e1008288. 14 indexed citations

17.

Barylyuk, Konstantin, Luděk Kořený, Huiling Ke, et al.. (2020). A Comprehensive Subcellular Atlas of the Toxoplasma Proteome via hyperLOPIT Provides Spatial Context for Protein Functions. Cell Host & Microbe. 28(5). 752–766.e9. 205 indexed citations breakdown →

18.

Crook, Oliver M., et al.. (2020). Moving Profiling Spatial Proteomics Beyond Discrete Classification. PROTEOMICS. 20(23). e1900392–e1900392. 17 indexed citations

19.

Geladaki, Aikaterini, Nina Kočevar Britovšek, Lisa M. Breckels, et al.. (2019). Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics. Nature Communications. 10(1). 331–331. 133 indexed citations

20.

Crook, Oliver M., Claire M. Mulvey, Paul Kirk, Kathryn S. Lilley, & Laurent Gatto. (2018). A Bayesian mixture modelling approach for spatial proteomics. PLoS Computational Biology. 14(11). e1006516–e1006516. 41 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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