BACKGROUND: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community. RESULTS: Our objective is to provide the bioinformatics community with an...
The 3D microarrays, generally known as gene-sample-time microarrays, couple the information on diffe...
Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data...
We present libNMF -- a computationally efficient high performance library for computing nonnegative ...
Background: Nonnegative Matrix Factorization ( NMF) is an unsupervised learning technique that has b...
Nonnegative Matrix Factorization (NMF) has acquired a relevant role in the panorama of knowledge ext...
Abstract: In the last decade, advances in high-through-put technologies such as DNA microarrays have...
This book collects new results, concepts and further developments of NMF. The open problems discusse...
This edited book collects new results, concepts and further developments of NMF. The open problems d...
Nonnegative Matrix Factorization (NMF) is a class of low-rank dimensionality reduction methods whic...
Nonnegative Matrix Factorization (NMF) is a class of low-rank dimensionality reduction methods whic...
Nonnegative Matrix Factorization (NMF) revealed to be useful for analysing microarray data and extr...
9 pages, 4 figures.[Background] In the Bioinformatics field, a great deal of interest has been given...
Inspect data for searching valuable information hidden in represents a key aspect in several fields....
AbstractIn the past decades, advances in high-throughput technologies have led to the generation of ...
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension re...
The 3D microarrays, generally known as gene-sample-time microarrays, couple the information on diffe...
Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data...
We present libNMF -- a computationally efficient high performance library for computing nonnegative ...
Background: Nonnegative Matrix Factorization ( NMF) is an unsupervised learning technique that has b...
Nonnegative Matrix Factorization (NMF) has acquired a relevant role in the panorama of knowledge ext...
Abstract: In the last decade, advances in high-through-put technologies such as DNA microarrays have...
This book collects new results, concepts and further developments of NMF. The open problems discusse...
This edited book collects new results, concepts and further developments of NMF. The open problems d...
Nonnegative Matrix Factorization (NMF) is a class of low-rank dimensionality reduction methods whic...
Nonnegative Matrix Factorization (NMF) is a class of low-rank dimensionality reduction methods whic...
Nonnegative Matrix Factorization (NMF) revealed to be useful for analysing microarray data and extr...
9 pages, 4 figures.[Background] In the Bioinformatics field, a great deal of interest has been given...
Inspect data for searching valuable information hidden in represents a key aspect in several fields....
AbstractIn the past decades, advances in high-throughput technologies have led to the generation of ...
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension re...
The 3D microarrays, generally known as gene-sample-time microarrays, couple the information on diffe...
Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data...
We present libNMF -- a computationally efficient high performance library for computing nonnegative ...