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Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data.

, , , and . ICANN (2), volume 5769 of Lecture Notes in Computer Science, page 20-29. Springer, (2009)

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Detection of active transcription factor binding sites with the combination of DNase hypersensitivity and histone modifications., , , and . Bioinform., 30 (22): 3143-3151 (2014)Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information., , and . BSB, volume 4643 of Lecture Notes in Computer Science, page 81-92. Springer, (2007)Inferring differentiation pathways from gene expression., , , and . ISMB, page 156-164. (2008)A Symbolic Approach to Gene Expression Time Series Analysis., , and . SBRN, page 25-30. IEEE Computer Society, (2002)Predicting Gene Functions Using Semi-supervised Clustering Algorithms with Objective Function Optimization., , , and . SBRN, page 61-66. IEEE Computer Society, (2012)Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data., , , and . BMC Bioinform., (2007)Random Forest and Gene Networks for Association of SNPs to Alzheimer's Disease., , , and . BSB, volume 8213 of Lecture Notes in Computer Science, page 104-115. Springer, (2013)Prediction of Transcription Factor Binding Sites by Integrating DNase Digestion and Histone Modification., , and . BSB, volume 7409 of Lecture Notes in Computer Science, page 109-119. Springer, (2012)Comparative study on normalization procedures for cluster analysis of gene expression datasets., , , , , and . IJCNN, page 2792-2798. IEEE, (2008)Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data., , , and . ICANN (2), volume 5769 of Lecture Notes in Computer Science, page 20-29. Springer, (2009)