Data Mining in Biomedicine [Paperback]

This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.

Recent Methodological Developments for Data Mining Problems in Biomedicine.- Pattern-Based Discriminants in the Logical Analysis of Data.- Exploring Microarray Data with Correspondence Analysis.- An Ensemble Method of Discovering Sample Classes Using Gene Expression Profiling.- CpG Island Identification with Higher Order and Variable Order Markov Models.- Data Mining Algorithms for Virtual Screening of Bioactive Compounds.- Sparse Component Analysis: a New Tool for Data Mining.- Data Mining Via Entropy and Graph Clustering.- Molecular Biology and Pooling Design.- An Optimization Approach to Identify the Relationship between Features and Output of a Multi-label Classifier.- Classifying Noisy and Incomplete Medical Data by a Differential Latent Semantic Indexing Approach.- Ontology Search and Text Mining of MEDLINE Database.- Data Mining Techniques in Disease Diagnosis.- Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias.- Diagnosis of Alport Syndrome by Pattern Recognition Techniques.- Clinical Analysis of the Diagnostic Classification of Geriatric Disorders.- Data Mining Studies in Genomics and Proteomics.- A Hybrid Knowledge Based-Clustering Multi-Class SVM Approach for Genes Expression Analysis.- Mathematical Programming Formulations for Problems in Genomics and Proteomics.- Inferring the Origin of the Genetic Code.- Deciphering the Structures of Genomic DNA Sequences Ul³J