Improving Tumor Clustering Based on Gene Selection
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A New Orthogonal Discriminant Projection Based Prediction Method for Bioinformatic Data
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Locally Linear Discriminant Embedding for Tumor Classification
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Gene Expression Data Classification Using Independent Variable Group Analysis
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
A GA-Based Approach to ICA Feature Selection: An Efficient Method to Classify Microarray Datasets
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
A New Approach to Improving ICA-Based Models for the Classification of Microarray Data
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Journal of Biomedical Informatics
Microarray data classification based on ensemble independent component selection
Computers in Biology and Medicine
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
Detecting novel hypermethylated genes in Breast cancer benefiting from feature selection
Computers in Biology and Medicine
Cancer identification based on DNA microarray data
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
An ensemble classifier based on kernel method for multi-situation DNA microarray data
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Nonnegative Principal Component Analysis for Cancer Molecular Pattern Discovery
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Gene expression data classification using locally linear discriminant embedding
Computers in Biology and Medicine
Artificial Intelligence in Medicine
A modified method for blind source separation
ACS'06 Proceedings of the 6th WSEAS international conference on Applied computer science
A GA based approach to improving the ICA based classification models for tumor classification
WSEAS Transactions on Information Science and Applications
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
Discovering the transcriptional modules using microarray data by penalized matrix decomposition
Computers in Biology and Medicine
Molecular Pattern Discovery Based on Penalized Matrix Decomposition
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Robust Classification Method of Tumor Subtype by Using Correlation Filters
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Extracting plants core genes responding to abiotic stresses by penalized matrix decomposition
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An eigengene-based classifier committee learning algorithm for tumor classification
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Computers in Biology and Medicine
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Disease-related gene expression analysis using an ensemble statistical test method
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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
Eigenface-based sparse representation for face recognition
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Bayesian predictive kernel discriminant analysis
Pattern Recognition Letters
Hi-index | 3.85 |
Motivation: Microarrays are capable of determining the expression levels of thousands of genes simultaneously. One important application of gene expression data is classification of samples into categories. In combination with classification methods, this technology can be useful to support clinical management decisions for individual patients, e.g. in oncology. Standard statistic methodologies in classification or prediction do not work well when the number of variables p (genes) far too exceeds the number of samples n. So, modification of existing statistical methodologies or development of new methodologies is needed for the analysis of microarray data. Results: This paper proposes a new method for tumor classification using gene expression data. In this method, we first employ independent component analysis to model the gene expression data, then apply optimal scoring algorithm to classify them. Further speaking, this approach can first make full use of the high-order statistical information contained in the gene expression data. Second, this approach also employs regularized regression models to handle the situation of large numbers of correlated predictor variables. Finally, the predictive models are developed for classifying tumors based on the entire gene expression profile. To show the validity of the proposed method, we apply it to classify four DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible. Availability: Matlab scripts are available on request. Contact: dshuang@iim.ac.cn