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 Using Recurrence Time Statistics -- Clustering Proteomics Data Using Bayesian Principal Component Analysis -- Bioinformatics for Traumatic Brain Injury: Proteomic Data Mining -- Characterization and Prediction of Protein Structure -- Computational Methods for Protein Fold Prediction: an Ab-initio Topological Approach -- A Topological Characterization of Protein Structure -- Applications of Data Mining Techniques to Brain Dynamics Studies -- Data Mining in EEG: Application to Epileptic Brain Disorders -- Information Flow in Coupled Nonlinear Systems: Application to the Epileptic Human Brain -- Reconstruction of Epileptic Brain Dynamics Using Data Mining Techniques -- Automated Seizure Prediction Algorithm and its Statistical Assessment: A Report from Ten Patients -- Seizure Predictability in an Experimental Model of Epilepsy -- Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling. Data minin g technique s ar e applie d i n a grea t variet y o f practica l problem s nowadays. Wit h th e overwhelmin g growt h o f th e amount s o f dat a arisin g i n diverse areas , th e developmen t o f appropriat e method s fo r extractin g usefu l information fro m thi s dat a become s a crucia l task . Biomedicine ha s alway s bee n on e o f th e mos t importan t area s wher e i- formation obtaine d fro m massiv e dataset s ca n assis t medica l researcher s an d practitioners i n understandin g th e structur e o f huma n genome , explorin g th e dynamics o f huma n brain , diseas e diagnosi s an d treatment , dru g discovery , etc. Dat a minin g technique s pla y a n essentia l rol e i n analyzin g an d integra- ing thes e datasets , a s wel l a s i n discoverin g biologica l processe s underlyin g this data . This volum e present s a collectio n o f chapter s coverin g variou s aspect s o f data minin g problem s i n biomedicine .