Gene selection and classification for cancer microarray data based on machine learning and similarity measures

[1]  Qingzhong Liu,et al.  An improved approach to steganalysis of JPEG images , 2010, Inf. Sci..

[2]  Youping Deng,et al.  Feature Selection and Classification of MAQC-II Breast Cancer and Multiple Myeloma Microarray Gene Expression Data , 2009, PloS one.

[3]  Zhaohui S. Qin.  Clustering microarray gene expression data using weighted Chinese restaurant process , 2006, Bioinform..

[4]  A. Brazma,et al.  Standards for systems biology , 2006, Nature Reviews Genetics.

[5]  Xin Yao,et al.  Gene selection algorithms for microarray data based on least squares support vector machine , 2006, BMC Bioinformatics.

[6]  Ramón Díaz-Uriarte,et al.  Gene selection and classification of microarray data using random forest , 2006, BMC Bioinformatics.

[7]  A. Brazma,et al.  A new algorithm for comparing and visualizing relationships between hierarchical and flat gene expression data clusterings , 2005, Bioinform..

[8]  D. Hand,et al.  Finding Groups in Gene Expression Data , 2005, Journal of biomedicine & biotechnology.

[9]  D. Koller,et al.  From signatures to models: understanding cancer using microarrays , 2005, Nature Genetics.

[10]  Lawrence Carin,et al.  Sparse multinomial logistic regression: fast algorithms and generalization bounds , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  J. Suykens,et al.  Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction , 2004, Bioinform..

[12]  T. Subba Rao,et al.  Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB , 2004 .

[13]  Léon Personnaz,et al.  MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling , 2003, J. Mach. Learn. Res..

[14]  T. H. Bø,et al.  New feature subset selection procedures for classification of expression profiles , 2002, Genome Biology.

[15]  E. Lander,et al.  Gene expression correlates of clinical prostate cancer behavior. , 2002, Cancer cell.

[16]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[17]  T. Poggio,et al.  Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.

[18]  William Stafford Noble,et al.  Analysis of strain and regional variation in gene expression in mouse brain , 2001, Genome Biology.

[19]  A D Long,et al.  Improved Statistical Inference from DNA Microarray Data Using Analysis of Variance and A Bayesian Statistical Framework , 2001, The Journal of Biological Chemistry.

[20]  Gérard Dreyfus,et al.  Withdrawing an example from the training set: An analytic estimation of its effect on a non-linear parameterised model , 2000, Neurocomputing.

[21]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[22]  U. Alon,et al.  Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[23]  R. Tibshirani.  The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.

[24]  S. Noah,et al.  Classification Using Support Vector Machines , 2012 .

[25]  Qingzhong Liu,et al.  Feature mining and pattern classification for steganalysis of LSB matching steganography in grayscale images , 2008, Pattern Recognit..

[26]  Qingzhong Liu,et al.  A distribution free summarization method for Affymetrix GeneChip arrays. , 2007, Bioinformatics.

[27]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[28]  Jiangsheng Yu,et al.  Bayesian neural network approaches to ovarian cancer identification from high-resolution mass spectrometry data , 2005, ISMB.

[29]  BIOINFORMATICS ORIGINAL PAPER Gene expression LS Bound based gene selection for DNA microarray data , 2004 .

[30]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[31]  Partha S. Vasisht.  Computational Analysis of Microarray Data , 2003 .

[32]  Iñaki Inza,et al.  Gene selection by sequential search wrapper approaches in microarray cancer class prediction , 2002, J. Intell. Fuzzy Syst..

[33]  Todd,et al.  Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.

[34]  Christina Kendziorski,et al.  On Differential Variability of Expression Ratios: Improving Statistical Inference about Gene Expression Changes from Microarray Data , 2001, J. Comput. Biol..

[35]  L. Breiman.  Random Forests , 2001, Machine Learning.

[36]  Vladimir Cherkassky,et al.  Statistical learning theory , 1998 .

[37]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[38]  A. Franklin,et al.  University of Texas Health Science Center at Houston. , 1983, Cutis.