Author

Etienne Waelkens

KU LeuvenORCID 0000-0001-5756-0605Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Research Focus:dimensionality reduction· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Bart De MooriD· 2 shared Marc ClaeseniD· 1 shared Mark Reid GrosecloseiD· 1 shared Nico VerbeeckiD· 1 shared Thomas MoermaniD· 1 shared Thomas TousseyniD· 1 shared Tina SmetsiD· 1 shared Tom De Keyser· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Bart De MoorORCID

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2 papers

Recent·Most cited

BioinformaticsAnalytical and Bioanalytical ChemistryPeer-reviewedMar 1, 2021

Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Using Deep Learning

Wanqiu Zhang, Marc Claesen, Thomas Moerman…·Nico Verbeeck

This paper uses deep learning to improve clustering of mass spectrometry imaging data by transforming ion images into neural ion images, resulting in more consistent and fine-grained spatial clusters.

37 citations

imagingdeep learning

𝕏 PostBluesky

BioinformaticsAnalytical ChemistryPeer-reviewedFeb 8, 2021

Correspondence-aware manifold learning for microscopic and spatial omics imaging: a novel data fusion method bringing MSI to a cellular resolution.

Tina Smets, Tom De Keyser, Thomas Tousseyn…·Bart De Moor

This paper introduces a data fusion method that integrates spatial omics and microscopic data to visualize molecular trends at cellular resolution.

22 citations

spatial transcriptomicsimaging

𝕏 PostBluesky