Tomasz G. Smolinski & Mariofanna G Milanova 
Computational Intelligence in Biomedicine and Bioinformatics 
Current Trends and Applications

The purpose of this book is to provide an overview of state-of-the-art methodologies currently utilized for biomedicine and/or bioinformatics-oriented applications. Researchers working in these fields will learn new methods to help tackle their problems.

Cuprins

Techniques and Methodologies.- Computational Intelligence in Solving Bioinformatics Problems: Reviews, Perspectives, and Challenges.- Data Mining and Genetic Algorithms: Finding Hidden Meaning in Biological and Biomedical Data.- The Use of Rough Sets as a Data Mining Tool for Experimental Bio-data.- Integrating Local and Personalised Modelling with Global Ontology Knowledge Bases for Biomedical and Bioinformatics Decision Support.- Computational Intelligence in Biomedicine.- Data-Mining of Time-Domain Features from Neural Extracellular Field Data.- Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers.- Computational Intelligence Techniques in Image Segmentation for Cytopathology.- Curvature Flow Based 3D Surface Evolution Model for Polyp Detection and Visualization in CT Colonography.- Assisting Cancer Diagnosis with Fuzzy Neural Networks.- Computational Intelligence in Clinical Oncology: Lessons Learned from an Analysis of a Clinical Study.- Computational Intelligence in Bioinformatics.- Artificial Immune Systems in Bioinformatics.- Evolutionary Algorithms for the Protein Folding Problem: A Review and Current Trends.- Flexible Protein Folding by Ant Colony Optimization.- Considering Stem-Loops as Sequence Signals for Finding Ribosomal RNA Genes.- Power-Law Signatures and Patchiness in Genechip Oligonucleotide Microarrays.- Case Study: Structure and Function Prediction of a Protein with No Functionally Characterized Homolog.- From Biomedical Literature to Knowledge: Mining Protein-Protein Interactions.