Using a single neuron as a marker selector - A breast cancer case study

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn , Issue , 2007, Pages 4219-4222

  Blazadonakis, Michalis E ^a   Perperoglou, Ans ^a   Zervakis, Michalis ^a  

^a TECHNICAL UNIVERSITY OF CRETE   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMARKERS; DNA; MICROARRAYS; SUPPORT VECTOR MACHINES; TUMORS;

BREAST CANCER; LINEAR ESTIMATOR; LINEAR METHODS; MARKER SELECTION;

NEURONS;

TUMOR MARKER;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOSYNTHESIS; BREAST TUMOR; DNA MICROARRAY; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HUMAN; METABOLISM; METHODOLOGY; NERVE CELL;

BREAST NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; NEURAL NETWORKS (COMPUTER); NEURONS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; TUMOR MARKERS, BIOLOGICAL;

EID: 57649225866     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2007.4353267     Document Type: Conference Paper

References (9)

1. rd International IEEE Conference on Intelligent Systems, 2006, pp. 626-630.
2. J.J. Goeman, S.A. Van de Geer, F. de Kor, H.C. Van Houwelingen. "A global test for groups of genes: testing association with a clinical outcome". Bionformatics, 2004, 20 pp. 93-99.
3. R. T. Golub, K. D. Slonim, P. Tamayo, C. Huard, et al. "Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring", Science, 1999, 286, pp. 531-536.
4. I. Guyon, J. Weston, S. Barnhill and V. Vapnik. "Gene selection for cancer classification using Support vector machines", machine learning, 2002, 36, pp. 389-422.
5. F. Li and Y. Yang. "Analysis of recursive gene selection approaches from microarray data", Bioinformatics, 2005, 21 pp. 3741-3747.
6. M. Riedmiller, and H. Braun. "A direct adoptive method for faster backpropagation learning: The RPROP algorithm." Proceedings of the IEEE International Conference on Neural Networks (ICNN), 1993, pp. 586-591.
7. R Shen. D. Ghosh, A. Chinnaiyan and M. Zhaoling. "Eigengene-based linear discriminant model for tumor classification using gene expression microarray data", Bioinformatics, 2006, 22, pp. 2635-2642.
8. R. Simon, M.D. Radmacher, K. Dobbin, L. M. McShane. "Pitfalls in the Use of DNA microrray Data for Diagnostic and Prognostic Classification", Journal of the National Cancer Institute, 2003, 95, pp. 14-18.
9. L. J. Van't Veer, H. Dai, M. J. Van de Vijver, Y. D. He, et al. "Gene expression profiling predicts clinical outcome of breast cancer", Letters to Nature, 2002, 415 pp. 530-536.