Computational Intelligence Methods for Bioinformatics and Biostatistics

Chapter 1 Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling

Chapter 2 Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Genomic Data: Two Examples from Rare Genetic Diseases and Infectious Diseases

Chapter 3 Bayesian Models for the Multi-sample Time-Course Microarray Experiments

Chapter 4 A Machine Learning Pipeline for Discriminant Pathways Identification

Chapter 5 Discovering Hidden Pathways in Bioinformatics

Chapter 6 Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models

Chapter 7 Computational Intelligence Methods for Bioinformatics and Biostatistics

Chapter 8 Feature Selection for the Prediction and Visualization of Brain Tumor Types Using Proton Magnetic Resonance Spectroscopy Data

Chapter 9 On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins

Chapter 10 Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biomedical Knowledge Discovery

Chapter 11 Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins

Chapter 12 Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree

Chapter 13 DEEN: A Simple and Fast Algorithm for Network Community Detection

Chapter 14 Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Exponents

Chapter 15 Support Vector Machines for Survival Regression

Chapter 16 Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Prediction

Chapter 17 A Faster Algorithm for Motif Finding in Sequences from ChIP-Seq Data

Chapter 18 Case/Control Prediction from Illumina Methylation Microarray’s β and Two-Color Channels in the Presence of Batch Effects

Chapter 19 Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Tool

Chapter 21 Solving Biclustering with a GRASP-Like Metaheuristic: Two Case-Studies on Gene Expression Analysis