Marina Evangelou - Multi-SNE, an approach for the visualisation, clustering and classification of multiple datasets
|Dates:||6 April 2022|
|Times:||14:00 - 15:00|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
Marina Evangelou, Senior Lecturer in Statistics in the School of Mathematics at Imperial College London is our speaker for the Statistics seminar series.
Title: Multi-SNE, an approach for the visualisation, clustering and classification of multiple datasets
Abstract: Recent biomedical studies generate multiple OMICS for the same individuals, for example transcriptomics and proteomics. Researchers are interested in understanding the relationships between the OMICS datasets and with the complex traits, including diseases of interest. In this work, I will present how we have adapted the well-known single-dataset visualisation 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 proposed multi-SNE approach can be used for the clustering and classification of the samples of the study 1-2.
1 Rodosthenous, Shahrezaei, Evangelou, Multi-view Data visualisation via manifold learning, arXiv:2101.06763
2 Rodosthenous, Shahrezaei, Evangelou, S-multi-SNE: Semi-supervised classification and visuallisation of multi-view data, arXiv:2111.03519
Organisation: Imperial College London
Travel and Contact Information
Zoom link: https://zoom.us/j/92947173491