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Your search keyword '"Feldner-Busztin, Dylan"' showing total 6 results
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6 results on '"Feldner-Busztin, Dylan"'

2. Dealing with dimensionality:the application of machine learning to multi-omics data

Author

Feldner-Busztin, Dylan, Nisantzis, Panos Firbas, Edmunds, Shelley Jane, Boza, Gergely, Racimo, Fernando, Gopalakrishnan, Shyam, Limborg, Morten Tønsberg, Lahti, Leo, de Polavieja, Gonzalo G., Feldner-Busztin, Dylan, Nisantzis, Panos Firbas, Edmunds, Shelley Jane, Boza, Gergely, Racimo, Fernando, Gopalakrishnan, Shyam, Limborg, Morten Tønsberg, Lahti, Leo, and de Polavieja, Gonzalo G.

Abstract

Motivation Machine learning (ML) methods are motivated by the need to automate information extraction from large datasets in order to support human users in data-driven tasks. This is an attractive approach for integrative joint analysis of vast amounts of omics data produced in next generation sequencing and other -omics assays. A systematic assessment of the current literature can help to identify key trends and potential gaps in methodology and applications. We surveyed the literature on ML multi-omic data integration and quantitatively explored the goals, techniques and data involved in this field. We were particularly interested in examining how researchers use ML to deal with the volume and complexity of these datasets.Results Our main finding is that the methods used are those that address the challenges of datasets with few samples and many features. Dimensionality reduction methods are used to reduce the feature count alongside models that can also appropriately handle relatively few samples. Popular techniques include autoencoders, random forests and support vector machines. We also found that the field is heavily influenced by the use of The Cancer Genome Atlas dataset, which is accessible and contains many diverse experiments.Availability and implementationAll data and processing scripts are available at this GitLab repository: or in Zenodo: .Supplementary informationare available at Bioinformatics online.

Published
2023

4. Notch controls the cell cycle to define leader versus follower identities during collective cell migration

Author

Alhashem, Zain, primary, Feldner-Busztin, Dylan, additional, Revell, Christopher, additional, Alvarez-Garcillan Portillo, Macarena, additional, Camargo-Sosa, Karen, additional, Richardson, Joanna, additional, Rocha, Manuel, additional, Gauert, Anton, additional, Corbeaux, Tatianna, additional, Milanetto, Martina, additional, Argenton, Francesco, additional, Tiso, Natascia, additional, Kelsh, Robert N, additional, Prince, Victoria E, additional, Bentley, Katie, additional, and Linker, Claudia, additional

Published
2022
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5. OpenABM-Covid19—An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing

Author

Hinch, Robert, primary, Probert, William J. M., additional, Nurtay, Anel, additional, Kendall, Michelle, additional, Wymant, Chris, additional, Hall, Matthew, additional, Lythgoe, Katrina, additional, Bulas Cruz, Ana, additional, Zhao, Lele, additional, Stewart, Andrea, additional, Ferretti, Luca, additional, Montero, Daniel, additional, Warren, James, additional, Mather, Nicole, additional, Abueg, Matthew, additional, Wu, Neo, additional, Legat, Olivier, additional, Bentley, Katie, additional, Mead, Thomas, additional, Van-Vuuren, Kelvin, additional, Feldner-Busztin, Dylan, additional, Ristori, Tommaso, additional, Finkelstein, Anthony, additional, Bonsall, David G., additional, Abeler-Dörner, Lucie, additional, and Fraser, Christophe, additional

Published
2021
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6. Notch controls the cell cycle to define leader versus follower identities during collective cell migration

Author

Alhashem, Zain, primary, Feldner-Busztin, Dylan, additional, Revell, Christopher, additional, Portillo, Macarena Alvarez-Garcillan, additional, Richardson, Joanna, additional, Rocha, Manuel, additional, Gauert, Anton, additional, Corbeaux, Tatianna, additional, Prince, Victoria E, additional, Bentley, Katie, additional, and Linker, Claudia, additional

Published
2021
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