Computational decomposition of molecular signatures based on blind source separation of non-negative dependent sources with NMF

Neural Networks for Signal Processing - Proceedings of the IEEE Workshop

Volumn 2003-January, Issue , 2003, Pages 409-418

  Zhang, Junying ^a   Wei, Le ^a   Wang, Yue ^b  

^a XIDIAN UNIVERSITY   (China)

^b State University   (United States)

Author keywords

Blind sowce separation (BSS); Independent component analysis (ICA); Matrix factorization; Non negative matrix factorization (NMF)

Indexed keywords

BLIND SOURCE SEPARATION; FACTORIZATION; GENE EXPRESSION; INDEPENDENT COMPONENT ANALYSIS; MIXING; SIGNAL PROCESSING;

BLIND SOWCE SEPARATION (BSS); GENE EXPRESSION PROFILES; INDEPENDENT COMPONENT ANALYSIS(ICA); MATRIX FACTORIZATIONS; NONNEGATIVE MATRIX FACTORIZATION; PARTIAL VOLUME CORRECTION; SENSITIVITY AND SPECIFICITY; STATISTICAL CHARACTERISTICS;

MATRIX ALGEBRA;

EID: 33646184668     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NNSP.2003.1318040     Document Type: Conference Paper

References (13)

1. D. Lee and H. S. Seung. "learning the parts of objects by non-negative matrix factorizafian". Nature, 401, October 1999.
2. Daniel D. Lee and H. Sebastian Seung. "algorithms for non-negative matrix factorization". In Advances in Neural Information Processing Systems 13,2001.
3. M. NOVA and R. Mammone, "use of non-negafive matrix factorization for language model adaptafion in a lecture transcripfion task", in Proceedings of the 2001.
4. D. Guillamet, M. Bressan, and J. Vitria. "weighted non-negafive matrix factorization for local represenfafions". In Proc of Computer vision and Pattern Recognition, 2001, http:llciteseer.nj.nec.com/context/209581210
5. Hyvarinen, J.Karhunen, and E.Oja, "independent Component Analysis", New York John Wiley, 2001
6. P.O. Hoyer and A. Hyviirinen. "independent component analysis applied to feafure extraction from colour andstereo images". Network Computation in Neural Systems, 11(3):191-210,2000.
7. WWW address: http://wwv.cis.hut.fi/projects/icdfastica/
8. David Guillamet, Jordi Vitria, "application of non-negative matrix facforization to dynamic posihon emission fomography ", ht~://citesee~nj.nec.com/554532.html
9. David Guillamet, Jordi Vitria classting faces with non-negative matrix factorization", http:/lciteseer.nj .nec.com/update/544952
10. David Guillamet, Jordi Vitria, "unsupervised learning of parf-based representations", http://citeseer.nj.nec.com/
11. P.Foldiak, 'yorming sparse wpresenfations by local anti-Hebbian learning", Biological Cybernetics, vo1.64, pp.165-170, 1990
12. J.Khan, J.S.Wei, M.Ringner, L.H.Saal, M.Lananyi, F.Westermann, EBerthold, MSchwab, C.R.Antonescu, C.Peterson, and P.S.Meltzer, "classficafion and diagnosric prediction of cancers using gene expression profiling and artficial neural networks", Nature Medicine, 7(6):673-679, June 2001
13. J. Zhang, K. Huang, J. Khan, K. Li, Z. Bhujwalla, R. Clarke, Z. Gu, Z. Szabo, J. Xuan, and Y. Wang, "computational Decomposition of Molecular Signatures", International Conference on Diagnostic Imaging and Analysis(ICDIA'02), August 12-20,2002, Shanghai, China