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

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Publication Details

Journal
Bioinformatics
Published
2025-03-20
DOI
https://doi.org/10.1093/bioinformatics/btaf122
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Zuqi Li, Sam F. L. Windels, Seth M. Weinberg, Kristel Van Steen et al.
Bioinformatics
Gene expression and cancer classification
article

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

Zuqi Li, Sam F. L. Windels, Seth M. Weinberg, Kristel Van Steen, Peter D. Claes, Mary L. Marazita, Mark D. Shriver, Nataša Pržulj, Noël Malod‐Dognin, David W. Fardo, Susan Walsh
article en

Abstract

No abstract available for this paper.
BioinformaticsVol. 41(4)
Institució Catalana de Recerca i Estudis Avançats (ES), Pennsylvania State University (US), University of Indianapolis (US), University of Kentucky (US), University of Liège (BE), University of Pittsburgh (US), Barcelona Supercomputing Center (ES), Universitair Ziekenhuis Leuven (BE), International Craniofacial Institute (US), Center for Human Genetics (US), Murdoch Children's Research Institute (AU), University College London (GB), Indiana University – Purdue University Indianapolis (US), Universitat Politècnica de Catalunya (ES), KU Leuven (BE)
European Commission, Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación
Openalex Percentile: Top 95%
Gene expression and cancer classification
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Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data — Zuqi Li, Sam F. L. Windels, et al. · Bioinformatics (2025) | TGRS Research Map | TGRS