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

Li, Zuqi; Windels, Sam FL; Malod-Dognin, Noel; Weinberg, Seth M; Marazita, Mary L; Walsh, Susan; Shriver, Mark D; Fardo, David W; Claes, Peter; Przulj, Natasa; Van Steen, Kristel

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

Li, Zuqi; Windels, Sam FL; Malod-Dognin, Noel et al.

2024 • In bioRxiv, p. 2024–09

Peer reviewed

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https://hdl.handle.net/2268/323614

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Disciplines :

Life sciences: Multidisciplinary, general & others

Author, co-author :

Li, Zuqi ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Bioinformatique

Windels, Sam FL

Malod-Dognin, Noel

Weinberg, Seth M

Marazita, Mary L

Walsh, Susan

Shriver, Mark D

Fardo, David W

Claes, Peter

Przulj, Natasa

Van Steen, Kristel ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Bioinformatique ; Université de Liège - ULiège > GIGA > GIGA Medical Genomics - Biostatistics, biomedicine and bioinformatics

Language :

English

Title :

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

Publication date :

2024

Journal title :

bioRxiv

Publisher :

Cold Spring Harbor Laboratory

Pages :

2024–09

Peer reviewed :

Peer reviewed

Available on ORBi :

since 18 October 2024

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