Philip Harrison

Combining molecular and cell painting image data for mechanism of action prediction

Tian, Guangyan; Harrison, Philip J.; Sreenivasan, Akshai P.; Carreras-Puigvert, Jordi et al.

Part of Artificial intelligence in the life sciences, 2023

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Evaluating the utility of brightfield image data for mechanism of action prediction

Harrison, Philip John; Gupta, Ankit; Rietdijk, Jonne; Wieslander, Håkan et al.

Part of PloS Computational Biology, 2023

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Deep learning approaches for image cytometry: assessing cellular morphological responses to drug perturbations

Harrison, Philip John

2023

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Predicting protein network topology clusters from chemical structure using deep learning

Sreenivasan, Akshai P.; Harrison, Philip J; Schaal, Wesley; Matuszewski, Damian J. et al.

Part of Journal of Cheminformatics, 2022

• DOI for Predicting protein network topology clusters from chemical structure using deep learning
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A method for Boolean analysis of protein interactions at a molecular level

Raykova, Doroteya; Kermpatsou, Despoina; Malmqvist, Tony; Harrison, Philip J et al.

Part of Nature Communications, 2022

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Combining molecular and cell painting image data for mechanism of action prediction

Tian, Guangyan; Harrison, Philip J.; Sreenivasan, Akshai P.; Carreras-Puigvert, Jordi et al.

Part of Artificial intelligence in the life sciences, 2023

• DOI for Combining molecular and cell painting image data for mechanism of action prediction
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Evaluating the utility of brightfield image data for mechanism of action prediction

Harrison, Philip John; Gupta, Ankit; Rietdijk, Jonne; Wieslander, Håkan et al.

Part of PloS Computational Biology, 2023

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Predicting protein network topology clusters from chemical structure using deep learning

Sreenivasan, Akshai P.; Harrison, Philip J; Schaal, Wesley; Matuszewski, Damian J. et al.

Part of Journal of Cheminformatics, 2022

• DOI for Predicting protein network topology clusters from chemical structure using deep learning
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A method for Boolean analysis of protein interactions at a molecular level

Raykova, Doroteya; Kermpatsou, Despoina; Malmqvist, Tony; Harrison, Philip J et al.

Part of Nature Communications, 2022

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Learning to see colours: Biologically relevant virtual staining for adipocyte cell images

Wieslander, Håkan; Gupta, Ankit; Bergman, Ebba; Hallström, Erik et al.

Part of PLOS ONE, 2021

• DOI for Learning to see colours: Biologically relevant virtual staining for adipocyte cell images
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Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images

Wieslander, Håkan; Harrison, Philip J.; Skogberg, Gabriel; Jackson, Sonya et al.

Part of IEEE journal of biomedical and health informatics, p. 371-380, 2021

• DOI for Deep learning and conformal prediction for hierarchical analysis of large-scale whole-slide tissue images
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Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit

Blamey, Ben; Toor, Salman; Dahlö, Martin; Wieslander, Håkan et al.

Part of GigaScience, p. 1-14, 2021

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Deep-learning models for lipid nanoparticle-based drug delivery

Harrison, Philip J.; Wieslander, Håkan; Sabirsh, Alan; Karlsson, Johan et al.

Part of Nanomedicine, p. 1097-1110, 2021

• DOI for Deep-learning models for lipid nanoparticle-based drug delivery

Occupancy versus colonization-extinction models for projecting population trends at different spatial scales

Norden, Jenni; Harrison, Philip J; Mair, Louise; Siitonen, Juha et al.

Part of Ecology and Evolution, p. 3079-3089, 2020

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Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes

Kensert, Alexander; Harrison, Philip J; Spjuth, Ola

Part of SLAS Discovery, p. 466-475, 2019

• DOI for Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes
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Deep Learning in Image Cytometry: A Review

Gupta, Anindya; Harrison, Philip J.; Wieslander, Håkan; Pielawski, Nicolas et al.

Part of Cytometry Part A, p. 366-380, 2019

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Deep learning approaches for image cytometry: assessing cellular morphological responses to drug perturbations

Harrison, Philip John

2023

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Is brightfield all you need for MoA prediction?

Gupta, Ankit; Harrison, Philip J; Wieslander, Håkan; Rietdijk, Jonne et al.

2022

Exploring the evolution of cellular morphological changes after drug administration based on brightfield image data

Harrison, Philip J.; Rietdijk, Jonne; Holmberg, David; Carreras-Puigvert, Jordi et al.