Author

Sam F. L. Windels

Barcelona Supercomputing CenterORCID 0000-0001-8443-5041Unclaimed 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:statistical model· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:graph neural network· 2 Research Focus:batch correction / integration· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Nataša PržuljiD· 3 shared Noël Malod‐DogniniD· 3 shared Daniel Tello VelascoiD· 1 shared David W. FardoiD· 1 shared Kristel Van SteeniD· 1 shared Mark D. ShriveriD· 1 shared Mary L. MarazitaiD· 1 shared Mikhail RotkevichiD· 1 shared

Activity by Year

2018-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersBioinformatics

Nataša PržuljORCID

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3 papers

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedMar 20, 2025

Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data

Zuqi Li, Sam F. L. Windels, Noël Malod‐Dognin…·Kristel Van Steen

INMTD integrates omics and 3D imaging data to produce unconfounded individual subgroups with biologically meaningful embeddings.

DOI 10.1093/bioinformatics/btaf122

humanbulk RNA-seq

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BioinformaticsbioRxivPreprintOct 27, 2023

Graphlet-based hyperbolic embeddings capture evolutionary dynamics in genetic networks

Daniel Tello Velasco, Sam F. L. Windels, Mikhail Rotkevich…·Nataša Pržulj

The paper introduces GraCoal embedding to improve functional organization analysis of scale-free biological networks by incorporating graphlet patterns, outperforming traditional Spring embedding methods.

DOI 10.1101/2023.10.27.564419

Drosophilayeast

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BioinformaticsbioRxivPreprintNov 4, 2018

Graphlet Laplacians: graphlet-based neighbourhoods highlight topology-function and topology-disease relationships

Sam F. L. Windels, Noël Malod‐Dognin, Nataša Pržulj

The paper introduces Graphlet Laplacians to capture topology-function and topology-disease relationships in biological networks by generalizing Laplacian matrices to consider graphlet-based neighbourhoods.

2 citations

graph neural networkstatistical model

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