Author

Sonja Georgievska

Netherlands eScience CenterORCID 0000-0002-8094-4532Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Organism:human· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Dario F. MarzellaiD· 2 shared Lars RidderiD· 2 shared Li C. XueiD· 2 shared Nicolas RenaudiD· 2 shared Alexandre M. J. J. BonviniD· 1 shared Amy L. KessleriD· 1 shared Arnold KuzniariD· 1 shared Brent S. PederseniD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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2 shared papersBioinformatics

Dario F. MarzellaORCID

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Author profile →

3 papers

Recent·Most cited

sv-channels: filtering genomic deletions using one-dimensional convolutional neural networks

Luca Santuari, Sonja Georgievska, Arnold Kuzniar, Brent S. Pedersen, Carl Shneider, Sarah L. Mehrem, Lars Ridder, Wigard P. Kloosterman, Jeroen de Ridder

sv-channels improves SV detection precision using deep learning, outperforming GRIDSS while maintaining Manta's recall.

bioRxiv · Oct 17, 2024 · PreprintBioinformatics

Improving generalizability for MHC-I binding peptide predictions through geometric deep learning

Dario F. Marzella, Giulia Crocioni, Tadija Radusinović, Daniil Lepikhov, Heleen Severin, Dani L. Bodor, Daniel T. Rademaker, ChiaYu Lin, Sonja Georgievska, Nicolas Renaud, Amy L. Kessler, Pablo López‐Tarifa, Sonja I. Buschow, Erik J. Bekkers, Li C. Xue

This paper improves MHC-I binding peptide prediction generalizability using geometric deep learning, outperforming sequence-based methods without binding affinity data.

bioRxiv · Dec 4, 2023 · PreprintBioinformatics

DeepRank: A deep learning framework for data mining 3D protein-protein interfaces

Nicolas Renaud, Cunliang Geng, Sonja Georgievska, Francesco Ambrosetti, Lars Ridder, Dario F. Marzella, Manon F. Réau, Alexandre M. J. J. Bonvin, Li C. Xue

DeepRank uses 3D CNNs to mine protein-protein interfaces, achieving competitive or better performance in classification and docking model ranking.

Nature Communications · Dec 3, 2021Peer-reviewedBioinformatics