Author

Andrew Fuller

Newcastle University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:imaging· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Andrew J. FilbyiD· 3 shared David McDonaldiD· 2 shared Alain ChédotaliD· 1 shared Alexandra–Chloé VillaniiD· 1 shared Amanda ThomsoniD· 1 shared Andrew John FisheriD· 1 shared Anindita RoyiD· 1 shared Aviv RegeviD· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersBioinformatics

Andrew J. FilbyORCID

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Author profile →

3 papers

Recent·Most cited

OPTIMAL: An OPTimsed Imaging Mass cytometry AnaLysis framework for benchmarking segmentation and data exploration

Bethany Hunter, Ioana Nicorescu, Emma Foster, David McDonald, Gillian Hulme, Andrew Fuller, Amanda Thomson, Thibaut Goldsborough, Catharien M. U. Hilkens, Joaquim Majo, Luke Milross, Andrew John Fisher, Peter Bankhead, John W. Wills, Paul C. T. Rees, , George Merces

OPTIMAL benchmarks segmentation and analysis methods for Imaging Mass Cytometry data, identifying optimal parameters for cell type identification and spatial analysis.

Cytometry Part A · Sep 26, 2023Peer-reviewedBioinformatics

Classification of human white blood cells using machine learning for stain-free imaging flow cytometry

Maxim Lippeveld, Carly Knill, Emma Ladlow, Andrew Fuller, Louise Jane Michaelis, Yvan Saeys, Andrew J. Filby, Daniel Peralta

This study compares classical machine learning and deep learning for classifying white blood cells using stain-free imaging flow cytometry, achieving balanced accuracies of 0.776 and 0.697 for white blood cells and 0.866 and 0.867 for eosinophils.

Cytometry Part A · Nov 5, 2019Peer-reviewedBioinformatics

Decoding the development of the blood and immune systems during human fetal liver haematopoiesis

Dorin-Mirel Popescu, Rachel Anne Botting, Emily Stephenson, Kile Green, Laura Jardine, Emily F. Calderbank, Mirjana Efremova, Meghan J. Acres, Daniel Maunder, Péter Végh, Issac Goh, Yorick Gitton, Jong-Eun Park, Krzysztof Polański, Roser Vento‐Tormo, , Muzlifah A. Haniffa

The paper uses single-cell transcriptomics to map hematopoiesis in human fetal liver, identifying cell differentiation trajectories and shifts in hematopoietic composition during development.

bioRxiv · May 31, 2019 · PreprintDevelopmental Biology