Marija Pizurica

Journal Article
A1
open access

Towards a more inductive world for drug repurposing approaches

Jesus de la Fuente, Guillermo Serrano, Uxía Veleiro, Mikel Casals, Laura Vera, Marija Pizurica (UGent) , Nuria Gómez-Cebrián, Leonor Puchades-Carrasco, Antonio Pineda-Lucena, Idoia Ochoa, et al.

(2025) NATURE MACHINE INTELLIGENCE. 7(3). p.495-508

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Conference Paper
open access

Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images

Max Hallemeesch, Marija Pizurica (UGent) , Paloma Rabaey (UGent) , Olivier Gevaert, Thomas Demeester (UGent) and Kathleen Marchal (UGent)

(2025) Imageomics-AAAI-25 , Discovering Biological Knowledge from Images using AI, part of AAAI 2025.

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Journal Article
A1
open access

GeNNius: an ultrafast drug-target interaction inference method based on graph neural networks

Uxia Veleiro, Jesus de la Fuente, Guillermo Serrano, Marija Pizurica (UGent) , Mikel Casals, Antonio Pineda-Lucena, Silve Vicent, Idoia Ochoa, Olivier Gevaert and Mikel Hernaez

(2024) BIOINFORMATICS. 40(1).

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Journal Article
A1
open access

Digital profiling of gene expression from histology images with linearized attention

Marija Pizurica (UGent) , Yuanning Zheng, Francisco Carrillo-Perez, Humaira Noor, Wei Yao, Christian Wohlfart, Antoaneta Vladimirova, Kathleen Marchal (UGent) and Olivier Gevaert

(2024) NATURE COMMUNICATIONS. 15(1).

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Miscellaneous

Synthetic multimodal data modelling for data imputation

Francisco Carrillo-Perez, Marija Pizurica (UGent) , Kathleen Marchal (UGent) and Olivier Gevaert

(2024) NATURE BIOMEDICAL ENGINEERING.

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Journal Article
A1
open access

Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models

Francisco Carrillo-Perez, Marija Pizurica (UGent) , Yuanning Zheng, Tarak Nath Nandi, Ravi Madduri, Jeanne Shen and Olivier Gevaert

(2024) NATURE BIOMEDICAL ENGINEERING. 8(5).

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Abstract LB272: Spatial cellular architecture predicts prognosis in glioblastoma

Yuanning Zheng, Francisco Carrillo-Perez, Marija Pizurica (UGent) and Olivier Gevaert

(2023) CANCER RESEARCH. 83(8).

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Abstract 4270: Prediction of cancer transcriptomes from whole-slide images with Vis-Gene

Yuanning Zheng, Marija Pizurica (UGent) , Francisco Carrillo-Perez, Christian Wohlfart, Wei Yao, Nadia Shamout, Olivier Gevaert and Antoaneta Vladimirova

(2023) CANCER RESEARCH. 83(7).

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Conference Paper
open access

Towards a more inductive world for drug repurposing approaches

J. de la Fuente Cedeño, G. Serrano, U. Veleiro, M Casals, L. Vera, Marija Pizurica (UGent) , A. Antonio Pineda-Lucena, I. Ochoa, S. Vicent, O. Gevaert, et al.

(2023) NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development.

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Journal Article
A1
open access

Whole slide imaging-based prediction of TP53 mutations identifies an aggressive disease phenotype in prostate cancer

Marija Pizurica (UGent) , Maarten Larmuseau (UGent) , Kim Van der Eecken, Louise de Schaetzen van Brienen (UGent) , Francisco Carrillo-Perez, Simon Isphording (UGent) , Nicolaas Lumen (UGent) , Jo Van Dorpe (UGent) , Piet Ost (UGent) , Sofie Verbeke (UGent) , et al.

(2023) CANCER RESEARCH. 83(17). p.2970-2984

Academic Bibliography

Marija Pizurica

Towards a more inductive world for drug repurposing approaches

Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images

GeNNius: an ultrafast drug-target interaction inference method based on graph neural networks

Digital profiling of gene expression from histology images with linearized attention

Synthetic multimodal data modelling for data imputation

Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models

Abstract LB272: Spatial cellular architecture predicts prognosis in glioblastoma

Abstract 4270: Prediction of cancer transcriptomes from whole-slide images with Vis-Gene

Towards a more inductive world for drug repurposing approaches

Whole slide imaging-based prediction of TP53 mutations identifies an aggressive disease phenotype in prostate cancer

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