Demystifying dimensionality reduction techniques in the 'omics' era: A practical approach for biological science students
Description
Dimensionality reduction techniques are essential in analyzing large 'omics' datasets in biochemistry and molecular biology. Principal component analysis, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection
