Manifold Learning in Computational Biology
This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions to various machine learning tasks. Gene expression data analysis is the analysis of measurements of the abundance of gene products from a set of ge
