Journal of Biomedical Informatics
Sparse p-norm Nonnegative Matrix Factorization for clustering gene expression data
International Journal of Data Mining and Bioinformatics
Improving Tumor Clustering Based on Gene Selection
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Sparse p-norm Nonnegative Matrix Factorization for clustering gene expression data
International Journal of Data Mining and Bioinformatics
Tumor clustering using nonnegative matrix factorization with gene selection
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Gene expression data classification based on non-negative matrix factorization
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Matrix factorisation methods applied in microarray data analysis
International Journal of Data Mining and Bioinformatics
Using underapproximations for sparse nonnegative matrix factorization
Pattern Recognition
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Molecular cancer class discovery using non-negative matrix factorization with sparseness constraint
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Nonnegative Principal Component Analysis for Cancer Molecular Pattern Discovery
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Sparse nonnegative matrix factorization for protein sequence motif discovery
Expert Systems with Applications: An International Journal
Molecular Pattern Discovery Based on Penalized Matrix Decomposition
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Algorithms for nonnegative matrix factorization with the β-divergence
Neural Computation
Non-monotone projection gradient method for non-negative matrix factorization
Computational Optimization and Applications
Multistability of α-divergence based NMF algorithms
Computers & Mathematics with Applications
Nonnegative matrix factorizations performing object detection and localization
Applied Computational Intelligence and Soft Computing
Solving non-negative matrix factorization by alternating least squares with a modified strategy
Data Mining and Knowledge Discovery
Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Computational Optimization and Applications
Tumor gene expressive data classification based on locally linear representation fisher criterion
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
A convergent algorithm for orthogonal nonnegative matrix factorization
Journal of Computational and Applied Mathematics
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Motivation: Identifying different cancer classes or subclasses with similar morphological appearances presents a challenging problem and has important implication in cancer diagnosis and treatment. Clustering based on gene-expression data has been shown to be a powerful method in cancer class discovery. Non-negative matrix factorization is one such method and was shown to be advantageous over other clustering techniques, such as hierarchical clustering or self-organizing maps. In this paper, we investigate the benefit of explicitly enforcing sparseness in the factorization process. Results: We report an improved unsupervised method for cancer classification by the use of gene-expression profile via sparse non-negative matrix factorization. We demonstrate the improvement by direct comparison with classic non-negative matrix factorization on the three well-studied datasets. In addition, we illustrate how to identify a small subset of co-expressed genes that may be directly involved in cancer. Contact:g1m1c1@receptor.med.harvard.edu, ygao@receptor.med.harvard.edu Supplementary information: http://arep.med.harvard.edu/snmf/supplement.htm