Microarray-based cancer diagnosis with artificial neural networks.
作者： Markus Ringnér , Carsten Peterson
DOI: 10.2144/MAR03RINGNER
关键词: Experimental methods 、 Artificial neural network 、 Machine learning 、 Classification procedure 、 Sample selection 、 Biology 、 Microarray 、 Analysis method 、 Artificial intelligence 、 Cancer 、 Bioinformatics 、 Classifier (UML)
摘要: In recent years, the advent of experimental methods to probe gene expression profiles cancer on a genome-wide scale has led widespread use supervised machine learning algorithms characterize these profiles. The main applications analysis range from assigning functional classes previously uncharacterized genes classification and prediction different tissues. This article surveys application diagnosis based To exemplify important issues procedure, emphasis this is one such method, namely artificial neural networks. addition, extract that are for performance classifier, as well influence sample selection results discussed.
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sci-hub.se 参考文章(31)
Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nature Genetics. ,vol. 14, pp. 457- 460 ,(1996) , 10.1038/NG1296-457
Tobey J. MacDonald, Kevin M. Brown, Bonnie LaFleur, Katia Peterson, Christopher Lawlor, Yidong Chen, Roger J. Packer, Philip Cogen, Dietrich A. Stephan, Expression profiling of medulloblastoma: PDGFRA and the RAS/MAPK pathway as therapeutic targets for metastatic disease Nature Genetics. ,vol. 29, pp. 143- 152 ,(2001) , 10.1038/NG731
M. Bittner, P. Meltzer, Y. Chen, Y. Jiang, E. Seftor, M. Hendrix, M. Radmacher, R. Simon, Z. Yakhini, A. Ben-Dor, N. Sampas, E. Dougherty, E. Wang, F. Marincola, C. Gooden, J. Lueders, A. Glatfelter, P. Pollock, J. Carpten, E. Gillanders, D. Leja, K. Dietrich, C. Beaudry, M. Berens, D. Alberts, V. Sondak, N. Hayward, J. Trent, Molecular classification of cutaneous malignant melanoma by gene expression profiling Nature. ,vol. 406, pp. 536- 540 ,(2000) , 10.1038/35020115
Javed Khan, Jun S Wei, Markus Ringner, Lao H Saal, Marc Ladanyi, Frank Westermann, Frank Berthold, Manfred Schwab, Cristina R Antonescu, Carsten Peterson, Paul S Meltzer, None, Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks Nature Medicine. ,vol. 7, pp. 673- 679 ,(2001) , 10.1038/89044
Markus Ringnér, Patrik Edén, Peter Johansson, Classification of Expression Patterns Using Artificial Neural Networks A Practical Approach to Microarray Data Analysis; pp 201-215 (2003). pp. 201- 215 ,(2003) , 10.1007/0-306-47815-3_11
Sofia K Gruvberger, Markus Ringnér, Patrik Edén, Åke Borg, Mårten Fernö, Carsten Peterson, Paul S Meltzer, Expression profiling to predict outcome in breast cancer: the influence of sample selection Breast Cancer Research. ,vol. 5, pp. 23- 26 ,(2002) , 10.1186/BCR548
M. Schena, D. Shalon, R. W. Davis, P. O. Brown, Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray Science. ,vol. 270, pp. 467- 470 ,(1995) , 10.1126/SCIENCE.270.5235.467
Ingrid Hedenfalk, David Duggan, Yidong Chen, Michael Radmacher, Michael Bittner, Richard Simon, Paul Meltzer, Barry Gusterson, Manel Esteller, Mark Raffeld, Zohar Yakhini, Amir Ben-Dor, Edward Dougherty, Juha Kononen, Lukas Bubendorf, Wilfrid Fehrle, Stefania Pittaluga, Sofia Gruvberger, Niklas Loman, Oskar Johannsson, Håkan Olsson, Benjamin Wilfond, Guido Sauter, Olli-P. Kallioniemi, Åke Borg, Jeffrey Trent, Gene-Expression Profiles in Hereditary Breast Cancer The New England Journal of Medicine. ,vol. 344, pp. 539- 548 ,(2001) , 10.1056/NEJM200102223440801
Jonas S. Almeida, Predictive non-linear modeling of complex data by artificial neural networks Current Opinion in Biotechnology. ,vol. 13, pp. 72- 76 ,(2002) , 10.1016/S0958-1669(02)00288-4
F. Rosenblatt, The perceptron: a probabilistic model for information storage and organization in the brain. Psychological Review. ,vol. 65, pp. 386- 408 ,(1958) , 10.1037/H0042519