Sean O’Callaghan

582 total citations
15 papers, 408 citations indexed

About

Sean O’Callaghan is a scholar working on Molecular Biology, Epidemiology and Physiology. According to data from OpenAlex, Sean O’Callaghan has authored 15 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Epidemiology and 3 papers in Physiology. Recurrent topics in Sean O’Callaghan's work include Metabolomics and Mass Spectrometry Studies (6 papers), Adipose Tissue and Metabolism (3 papers) and Probiotics and Fermented Foods (2 papers). Sean O’Callaghan is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (6 papers), Adipose Tissue and Metabolism (3 papers) and Probiotics and Fermented Foods (2 papers). Sean O’Callaghan collaborates with scholars based in Australia, United States and Italy. Sean O’Callaghan's co-authors include Malcolm J. McConville, Joachim Kloehn, Eleanor Saunders, Michael J. Dagley, Dedreia Tull, David P. De Souza, Greg M. Kowalski, Steven Hamley, Ahrathy Selathurai and Clinton R. Bruce and has published in prestigious journals such as Applied Physics Letters, Bioinformatics and Scientific Reports.

In The Last Decade

Sean O’Callaghan

15 papers receiving 399 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sean O’Callaghan Australia	11	179	105	100	55	47	15	408
Fiona Achcar United Kingdom	14	325 1.8×	234 2.2×	226 2.3×	55 1.0×	39 0.8×	23	598
Tawanda Zininga South Africa	15	501 2.8×	32 0.3×	163 1.6×	40 0.7×	5 0.1×	35	782
Junai Gan United States	9	270 1.5×	62 0.6×	24 0.2×	39 0.7×	65 1.4×	15	490
Michael L. Patnode United States	6	272 1.5×	11 0.1×	21 0.2×	76 1.4×	17 0.4×	8	402
Dagmar Jürgens Germany	11	160 0.9×	31 0.3×	93 0.9×	99 1.8×	33 0.7×	21	390
Mark J. Sartain United States	9	308 1.7×	156 1.5×	29 0.3×	21 0.4×	90 1.9×	10	538
Ravikant Ranjan India	11	101 0.6×	115 1.1×	204 2.0×	13 0.2×	3 0.1×	11	436
Lilian L. Nohara United States	11	180 1.0×	237 2.3×	122 1.2×	24 0.4×	5 0.1×	16	477
Deyuan Ou China	10	97 0.5×	13 0.1×	11 0.1×	49 0.9×	5 0.1×	21	387
Mirella Ciaccio Italy	13	328 1.8×	114 1.1×	76 0.8×	3 0.1×	12 0.3×	20	561

Countries citing papers authored by Sean O’Callaghan

Since Specialization

Citations

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

Fields of papers citing papers by Sean O’Callaghan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sean O’Callaghan. 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 Sean O’Callaghan. The network helps show where Sean O’Callaghan may publish in the future.

Co-authorship network of co-authors of Sean O’Callaghan

This figure shows the co-authorship network connecting the top 25 collaborators of Sean O’Callaghan. A scholar is included among the top collaborators of Sean O’Callaghan 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 Sean O’Callaghan. Sean O’Callaghan 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:

15 of 15 papers shown

O’Callaghan, Sean, et al.. (2021). Using Peptidomics and Machine Learning to Assess Effects of Drying Processes on the Peptide Profile within a Functional Ingredient. Processes. 9(3). 425–425. 4 indexed citations

Corrochano, Alberto R., et al.. (2021). Characterising the efficacy and bioavailability of bioactive peptides identified for attenuating muscle atrophy within a Vicia faba-derived functional ingredient. Current Research in Food Science. 4. 224–232. 23 indexed citations

Kloehn, Joachim, Berin A. Boughton, Eleanor Saunders, et al.. (2021). Identification of Metabolically Quiescent Leishmania mexicana Parasites in Peripheral and Cured Dermal Granulomas Using Stable Isotope Tracing Imaging Mass Spectrometry. mBio. 12(2). 17 indexed citations

Leeming, Michael G., Sean O’Callaghan, Luana Licata, et al.. (2020). Phosphomatics: interactive interrogation of substrate–kinase networks in global phosphoproteomics datasets. Bioinformatics. 37(11). 1635–1636. 11 indexed citations

Ruethers, Thimo, Aya C. Taki, Roni Nugraha, et al.. (2019). Variability of allergens in commercial fish extracts for skin prick testing. Allergy. 74(7). 1352–1363. 46 indexed citations

Klatt, Stephan, Rajini Brammananth, Sean O’Callaghan, et al.. (2018). Identification of novel lipid modifications and intermembrane dynamics in Corynebacterium glutamicum using high-resolution mass spectrometry [S]. Journal of Lipid Research. 59(7). 1190–1204. 28 indexed citations

Souza, David P. De, Saravanan Dayalan, Sean O’Callaghan, et al.. (2017). Comparative Metabolomics of Mycoplasma bovis and Mycoplasma gallisepticum Reveals Fundamental Differences in Active Metabolic Pathways and Suggests Novel Gene Annotations. mSystems. 2(5). 29 indexed citations

Hunter, Adam, Saravanan Dayalan, David P. De Souza, et al.. (2016). MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics. Metabolomics. 13(2). 14–14. 11 indexed citations

Kowalski, Greg M., Steven Hamley, Ahrathy Selathurai, et al.. (2016). Reversing diet-induced metabolic dysregulation by diet switching leads to altered hepatic de novo lipogenesis and glycerolipid synthesis. Scientific Reports. 6(1). 27541–27541. 28 indexed citations

10.

O’Callaghan, Sean, et al.. (2016). A Simple Method for Measuring Carbon-13 Fatty Acid Enrichment in the Major Lipid Classes of Microalgae Using GC-MS. Metabolites. 6(4). 42–42. 9 indexed citations

11.

Kowalski, Greg M., David P. De Souza, Steve Risis, et al.. (2015). In vivo cardiac glucose metabolism in the high-fat fed mouse: Comparison of euglycemic–hyperinsulinemic clamp derived measures of glucose uptake with a dynamic metabolomic flux profiling approach. Biochemical and Biophysical Research Communications. 463(4). 818–824. 10 indexed citations

12.

Kowalski, Greg M., David P. De Souza, Micah L. Burch, et al.. (2015). Application of dynamic metabolomics to examine in vivo skeletal muscle glucose metabolism in the chronically high-fat fed mouse. Biochemical and Biophysical Research Communications. 462(1). 27–32. 32 indexed citations

13.

Kloehn, Joachim, Eleanor Saunders, Sean O’Callaghan, Michael J. Dagley, & Malcolm J. McConville. (2015). Characterization of Metabolically Quiescent Leishmania Parasites in Murine Lesions Using Heavy Water Labeling. PLoS Pathogens. 11(2). e1004683–e1004683. 101 indexed citations

14.

O’Callaghan, Sean, David P. De Souza, Qiao Wang, et al.. (2012). PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools. BMC Bioinformatics. 13(1). 115–115. 57 indexed citations

15.

O’Callaghan, Sean, Scott Monaghan, Simon D. Elliott, & James C. Greer. (2007). Stress in silicon interlayers at the SiOx∕Ge interface. Applied Physics Letters. 90(14). 2 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.

Explore authors with similar magnitude of impact