Regularized non-negative matrix factorization for identifying differentially expressed genes and clustering samples: a survey

摘要

This paper surveys the application of non-negative matrix factorization (NMF), a well-known dimensionality reduction technique in bioinformatics "for identifying differentially expressed genes and clustering samples." The idea behind NMF is to factorize a given matrix without negative elements into two matrices that also have no negative elements. The dimensions of the factor matrices can be significantly lower than the original one, which makes the method practically interesting. Yet another reason why NMF is popular is its applicability in data analysis-"in the real world, many data are always non-negative."