Cancer classification and pathway discovery using non-negative matrix factorization

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a...

Galaxy Image Classification using Non-Negative Matrix Factorization

In modern astronomy with the advent of astronomical imaging technology developments and the increased capacity of digital storage, lead to the production of photographic atlases of data which need to be processed autonomously. Galaxies morphology is an important topic to understand questions concerning the evolution and formation of galaxies and their content. In this work, morphological classi...

Galaxy Image Classification using Non-Negative Matrix Factorization

In modern astronomy with the advent of astronomical imaging technology developments and the increased capacity of digital storage, lead to the production of photographic atlases of data which need to be processed autonomously. Galaxies morphology is an important topic to understand questions concerning the evolution and formation of galaxies and their content. In this work, morphological classi...

Cancer Class Discovery Using Non-negative Matrix Factorization Based on Alternating Non-negativity-Constrained Least Squares

Many bioinformatics problems deal with chemical concentrations that should be non-negative. Non-negative matrix factorization (NMF) is an approach to take advantage of non-negativity in data. We have recently developed sparse NMF algorithms via alternating nonnegativity-constrained least squares in order to obtain sparser basis vectors or sparser mixing coefficients for each sample, which lead ...

Non-negative matrix factorization