Clustering

…correction, dimensionality reduction, clustering, annotation and differential expression. Later sessions cover trajectory and pseudotime inference, RNA velocity, single-cell multi-omics integration and functional analysis. Participants finish with an independent dataset analysis and presentation. Bash and R/Bioconductor support reproducible workflows and interpre

…trees to single-cell preprocessing, clustering and annotation, followed by cross-species comparisons. The course examines duplication, gene loss, study design and how evolutionary relationships among genes affect proposed correspondences between cell populations. It also addresses limitations of using expression similarity as evidence for cell-type homology. The audience is postgraduate students and researchers with basic evolu

…normalisation, integration and clustering to interpretation. The course covers experimental design, differential expression and abundance, Single Cell Expression Atlas and standards for repository submission. Lectures, computational exercises and a mentored group challenge use virtual machines, Zoom and Slack. Basic Unix/Linux and Python skills are required. Participants should be available 09:00–17:30 UK time each day. There are 35 selected places, at £250 for aca

Optimal transport supports clustering, dictionary learning and domain adaptation, but high-dimensional data often force projections that discard information. Charles Bouveyron develops an alternative for Gaussian distributions with parsimonious covariance structure and low intrinsic dimension. A low-dimensional decomposition of empirical covariance matrices gives an efficient, robust closed form for the 2-Wasserstein distance without projecting the data. An explicit Monge map uses exact covariance square roots and inverse square roots. Numerical comparisons demonstrate analytical and computati

…eigenvectors, expansion, transport and clustering, illustrating how a local invariant can yield global information about a graph.

…using trace representations and clustering to discover emergent behaviour and feed improvements into evaluations and training.

…support applications such as clustering and recent breakthroughs in static maximum-flow and minimum-cost-flow algorithms.