Author

Andrew Benjamin Forbes

Monash UniversityORCID 0000-0003-4269-914XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Assay:bulk RNA-seq· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Organism:chicken / avian· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Aya MousaiD· 2 shared Daniel JönssoniD· 2 shared Joanne EnticottiD· 2 shared Kushan De SilvaiD· 2 shared Ryan T. DemmeriD· 2 shared Jennifer McIntyreiD· 1 shared Kathryn Amanda EllisiD· 1 shared Kerry O’NeilliD· 1 shared

Activity by Year

2022-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersBioinformatics

Aya MousaORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Characterising anthelmintic resistance against benzimidazoles and macrocyclic lactones in gastrointestinal nematode populations of dairy cattle

Paul Campbell, Jennifer McIntyre, Kerry O’Neill, Andrew Benjamin Forbes, Kathryn Amanda Ellis, Roz Laing

This study assesses anthelmintic resistance in cattle nematodes using FECRT and molecular methods, finding high resistance allele frequencies and multidrug resistance in Scottish populations.

bioRxiv · Sep 14, 2025 · PreprintMicrobiology

Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: A bioinformatics analytic workflow

Kushan De Silva, Ryan T. Demmer, Daniel Jönsson, Aya Mousa, Andrew Benjamin Forbes, Joanne Enticott

The paper identifies highly perturbed and hub genes associated with type 2 diabetes across human tissues using a bioinformatics workflow and meta-analysis.

Functional & Integrative Genomics · Jul 5, 2022Peer-reviewedBioinformatics

Marker genes of incident type 1 diabetes in peripheral blood mononuclear cells of children: A machine learning strategy for large-p, small-n scenarios

Kushan De Silva, Ryan T. Demmer, Daniel Jönsson, Aya Mousa, Andrew Benjamin Forbes, Joanne Enticott

This paper identifies marker genes for incident type 1 diabetes in children's PBMCs using a machine learning approach tailored for high-dimensional data, finding EGR2 as the top marker gene.

medRxiv · Feb 7, 2022 · PreprintGenetic & Genomic Medicine