Dr Robert Leigh
Biography
Dr. Robert Leigh is now Research Fellow with the School of Medicine, Trinity College Dublin.
Please see the below link for more information:
https://tilda.tcd.ie/people/profile/rleigh/
Dr. Robert Leigh was Senior Postdoctoral Researcher with the Antimicrobial Resistance and Microbiome Research Group. During his time with this Research Group, Rob worked on microbiomic (metagenomic) modulation of the avian GI tract using non-antibiotic supplementation. Specifically, Rob was interested in reducing the bioburden of infectious agents and antimicrobial resistance genes whilst increasing microbial population diversity and the survivability of beneficial symbionts by using dietary supplementation. Rob designed bespoke software for bioinformatic and biostatistical analyses and has spent some time tackling the problem of rampant variability often observed between samples from the same source, leading to the development of a novel machine learning application for this task. Additionally, Rob investigated the prevalence and mechanism of resistance plasmid evolution.
Prior to joining the Antimicrobial Resistance and Microbiome Research Group, Rob undertook a Ph.D. in Bioinformatics and Molecular Evolution at Maynooth University (under the supervision of Dr. David Fitzpatrick (Maynooth University) and Prof. James McInerney (University of Nottingham)) and a B.Sc.(Hons.) in Microbiology at University College Dublin. During his time with the Research Group, Rob has completed an M.Sc. in Innovation at National University of Ireland, Galway (now University of Galway) and a Specialist Diploma in Artificial Intelligence & Machine Learning at the University of Limerick.
Peer Reviewed Journal
Year | Publication | |
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2023 | Corrigan, A.; Leigh, R.J.; Walsh, F.; Murphy, R. (2023) 'Microbial community diversity and structure in the cecum of laying hens with and without mannan-rich fraction supplementation'. Journal of Applied Poultry Research, 32 . [Link] [DOI] | |
2022 | Smyth C.; Leigh R.J.; Delaney S.; Murphy R.A.; Walsh F. (2022) 'Shooting hoops: globetrotting plasmids spreading more than just antimicrobial resistance genes across One Health'. Microbial Genomics, 8 (8). [DOI] | |
2022 | Leigh R.J.; McKenna C.; McWade R.; Lynch B.; Walsh F. (2022) 'Comparative genomics and pangenomics of vancomycin-resistant and susceptible Enterococcus faecium from Irish hospitals'. Journal of Medical Microbiology, 71 (10). [DOI] | |
2021 | R.J. Leigh; R.A. Murphy; F. Walsh; (2021) 'statSuma: automated selection and performance of statistical comparisons for microbiome studies'. Biorxiv : The Preprint Server For Biology, . [DOI] [Full-Text] | |
2021 | R.J. Leigh; R.A. Murphy; F. Walsh; (2021) 'uniForest: an unsupervised machine learning technique to detect outliers and restrict variance in microbiome studies'. Biorxiv : The Preprint Server For Biology, . [DOI] [Full-Text] | |
2021 | Leigh R.J., McKenna C., McWade R., Lynch B., Walsh F (2021) 'Comparative genomics and pangenomics of vancomycin resistant and susceptible Enterococcus faecium from Irish hospitals across 20 years'. Biorxiv : The Preprint Server For Biology, . https://doi.org/10.1101/2021.11.22.469549 [Full-Text] | |
2024 | Leigh, R.J.; Corrigan, A.; Murphy, R.A.; Walsh, F. (2024) 'Yeast mannan rich fraction positively influences microbiome uniformity, productivity associated taxa, and lay performance'. Animal Microbiome, 6 . [Link] [DOI] | |
2023 | Tyrrell, C.; Do, T.T.; Leigh, R.J.; Burgess, C.M.; Brennan, F.P.; Walsh, F. (2023) 'Differential impact of swine, bovine and poultry manure on the microbiome and resistome of agricultural grassland'. Science of the Total Environment, 886 . [Link] [DOI] | |
2022 | Leigh RJ; Corrigan A; Murphy RA; Walsh F; (2022) 'Effect of Mannan-rich fraction supplementation on commercial broiler intestinum tenue and cecum microbiota'. Animal Microbiome, 4 (1). [DOI] |
Other Publication
Year | Publication | |
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2024 | Leigh, R.J.; Corrigan, A.; Murphy, R.A.; Taylor-Pickard, J.; Moran, C.A.; Walsh, F. (2024) Correction to: Yeast mannan rich fraction positively influences microbiome uniformity, productivity associated taxa, and lay performance (Animal Microbiome, (2024), 6, 1, (9), 10.1186/s42523-024-00295-7). [Link] [DOI] |