Michael J. Deery

4.2k total citations
65 papers, 2.7k citations indexed

About

Michael J. Deery is a scholar working on Molecular Biology, Spectroscopy and Plant Science. According to data from OpenAlex, Michael J. Deery has authored 65 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 14 papers in Spectroscopy and 7 papers in Plant Science. Recurrent topics in Michael J. Deery's work include Advanced Proteomics Techniques and Applications (10 papers), Mass Spectrometry Techniques and Applications (9 papers) and Ubiquitin and proteasome pathways (9 papers). Michael J. Deery is often cited by papers focused on Advanced Proteomics Techniques and Applications (10 papers), Mass Spectrometry Techniques and Applications (9 papers) and Ubiquitin and proteasome pathways (9 papers). Michael J. Deery collaborates with scholars based in United Kingdom, United States and Spain. Michael J. Deery's co-authors include Kathryn S. Lilley, Keith R. Jennings, Julie A. Howard, Elizabeth S. Maywood, Charalambos P. Kyriacou, Akhilesh B. Reddy, Natasha A. Karp, Michael H. Hastings, Gonçalo J. L. Bernardes and Paul Dupree and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Angewandte Chemie International Edition.

In The Last Decade

Michael J. Deery

63 papers receiving 2.7k citations

Peers

Michael J. Deery
Meng C. Wang United States
Mayumi Yoshida Japan
Gilles Ferry France
Javier Sastre Toraño Netherlands
Motoyuki Hattori China
Shigeki Kiyonaka Japan
László Prókai United States
Tomáš Obšil Czechia
Zbigniew Grzonka Poland
Mark J. Wall United Kingdom
Meng C. Wang United States
Michael J. Deery
Citations per year, relative to Michael J. Deery Michael J. Deery (= 1×) peers Meng C. Wang

Countries citing papers authored by Michael J. Deery

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Deery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael J. Deery. 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 Michael J. Deery. The network helps show where Michael J. Deery may publish in the future.

Co-authorship network of co-authors of Michael J. Deery

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

All Works

20 of 20 papers shown
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Breckels, Lisa M., et al.. (2025). Localization of Organelle Proteins Using Data-Independent Acquisition (DIA-LOP). Molecular & Cellular Proteomics. 24(9). 101047–101047.
3.
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Smith, Daniel P., Michael J. Deery, Richard Bayliss, et al.. (2023). A point mutation in the kinase domain of CRK10 leads to xylem vessel collapse and activation of defence responses in Arabidopsis. Journal of Experimental Botany. 74(10). 3104–3121. 7 indexed citations
5.
Geeson, Michael B., Claudio D. Navo, Marta C. Marques, et al.. (2022). Platform for Orthogonal N-Cysteine-Specific Protein Modification Enabled by Cyclopropenone Reagents. Journal of the American Chemical Society. 144(23). 10396–10406. 44 indexed citations
6.
Fabre, Bertrand, Carole Pichereaux, Michael J. Deery, et al.. (2022). In Depth Exploration of the Alternative Proteome of Drosophila melanogaster. Frontiers in Cell and Developmental Biology. 10. 901351–901351. 7 indexed citations
7.
Giachello, Carlo NG, Rayner M. L. Queiroz, Rebeka Popovic, et al.. (2022). Drosophila nicotinic acetylcholine receptor subunits and their native interactions with insecticidal peptide toxins. eLife. 11. 15 indexed citations
8.
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
9.
Winton, Valerie J., Rafael D. Melani, Lissa C. Anderson, et al.. (2020). Development of novel methods for non-canonical myeloma protein analysis with an innovative adaptation of immunofixation electrophoresis, native top-down mass spectrometry, and middle-down de novo sequencing. Clinical Chemistry and Laboratory Medicine (CCLM). 59(4). 653–661. 5 indexed citations
10.
Vantourout, Julien C., Srinivasa Rao Adusumalli, Kyle W. Knouse, et al.. (2020). Serine-Selective Bioconjugation. Journal of the American Chemical Society. 142(41). 17236–17242. 68 indexed citations
11.
Chung, Betty, Adrián Vallí, Michael J. Deery, et al.. (2019). Distinct roles of Argonaute in the green alga Chlamydomonas reveal evolutionary conserved mode of miRNA-mediated gene expression. Scientific Reports. 9(1). 11091–11091. 13 indexed citations
12.
Breckels, Lisa M., Laurent Gatto, Michael J. Deery, et al.. (2019). Proteome Mapping of a Cyanobacterium Reveals Distinct Compartment Organization and Cell-Dispersed Metabolism. PLANT PHYSIOLOGY. 181(4). 1721–1738. 48 indexed citations
13.
Chung, Betty, Michael J. Deery, Arnoud Groen, Julie A. Howard, & David C. Baulcombe. (2017). Endogenous miRNA in the green alga Chlamydomonas regulates gene expression through CDS-targeting. Nature Plants. 3(10). 787–794. 33 indexed citations
14.
Fabre, Bertrand, Harriet T. Parsons, Michael J. Deery, et al.. (2017). Spectral Libraries for SWATH‐MS Assays for Drosophila melanogaster and Solanum lycopersicum. PROTEOMICS. 17(21). 18 indexed citations
15.
James, Rory Hennell, Eva Caceres, Julie A. Howard, et al.. (2017). Functional reconstruction of a eukaryotic-like E1/E2/(RING) E3 ubiquitylation cascade from an uncultured archaeon. Nature Communications. 8(1). 1120–1120. 22 indexed citations
16.
Prevosto, Claudia, Sarah McDonald, Tim Key, et al.. (2016). Allele-Independent Turnover of Human Leukocyte Antigen (HLA) Class Ia Molecules. PLoS ONE. 11(8). e0161011–e0161011. 10 indexed citations
17.
Lilley, Kathryn S., Michael J. Deery, & Laurent Gatto. (2011). Challenges for proteomics core facilities. PROTEOMICS. 11(6). 1017–1025. 9 indexed citations
18.
Riva, Alessandra, Michael J. Deery, Sarah McDonald, Torben Lund, & Robert Busch. (2010). Measurement of protein synthesis using heavy water labeling and peptide mass spectrometry: Discrimination between major histocompatibility complex allotypes. Analytical Biochemistry. 403(1-2). 1–12. 34 indexed citations
19.
Reddy, Akhilesh B., Natasha A. Karp, Elizabeth S. Maywood, et al.. (2006). Circadian Orchestration of the Hepatic Proteome. Current Biology. 16(11). 1107–1115. 437 indexed citations
20.
Grant, Melissa M., et al.. (2003). Purification of an Arabinofuranosidase and Two β-Xylopyranosidases from Germinated Wheat. Journal of the Institute of Brewing. 109(1). 8–15. 3 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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