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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20220327T194030Z
DTSTART:20220406T130000Z
DTEND:20220406T140000Z
SUMMARY:Marina Evangelou  - Multi-SNE\, an approach for the visualisation
 \, clustering and classification of multiple datasets
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}gky-ku8cof0
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DESCRIPTION:Marina Evangelou\, Senior Lecturer in Statistics in the Schoo
 l of Mathematics at Imperial College London is our speaker for the Stati
 stics seminar series.\n\nTitle: Multi-SNE\, an approach for the visualis
 ation\, clustering and classification of multiple datasets\n\nAbstract: 
  Recent biomedical studies generate multiple OMICS for the same individu
 als\, for example transcriptomics and proteomics. Researchers are intere
 sted in understanding the relationships between the OMICS datasets and w
 ith the complex traits\, including diseases of interest. In this work\, 
 I will present how we have adapted the well-known single-dataset visuali
 sation approach Student's t-distributed Stochastic Neighbour Embedding (
 t-SNE) for the visualisation of multiple datasets that are generated on 
 the same individuals. I will further show how the outcome of the propose
 d multi-SNE approach can be used for the clustering and classification o
 f the samples of the study [1-2].  \n\n[1] Rodosthenous\, Shahrezaei\, E
 vangelou\, Multi-view Data visualisation via manifold learning\, arXiv:2
 101.06763  \n\n[2] Rodosthenous\, Shahrezaei\, Evangelou\, S-multi-SNE: 
 Semi-supervised classification and visuallisation of multi-view data\, a
 rXiv:2111.03519  
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Zoom link: https://zoom.us/j/92947173491
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