Titlebook: Computational Intelligence in Biomedicine and Bioinformatics; Current Trends and A Tomasz G. Smolinski,Mariofanna G. Milanova,Aboul-E Book

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Data-Mining of Time-Domain Features from Neural Extracellular Field Data would be desirable for automated seizure detection in both experimental and clinical venues. We have developed a time-domain algorithm denominated SPUD to facilitate data-mining of large electroencephalogram/electrocorticogram datasets to identify the occurrence of spike-wave or other activity patt

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Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers keys for efficient processing of the complex data. One major class are prototype based algorithms. Prototype based vector quantizers or classifiers are intuitive approaches realizing the principle of characteristic representatives for data subsets or decision regions between them. Examples for such

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Inflammation

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Assisting Cancer Diagnosis with Fuzzy Neural Networksrk (FNN) proposed earlier for cancer classification. This FNN contains three valuable aspects i.e., automatically generating fuzzy membership functions, parameter optimization, and rule-base simplification. One major obstacle in microarray data set classifier is that the number of features (genes) i

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Computational Intelligence in Clinical Oncology: Lessons Learned from an Analysis of a Clinical Studtion from gene expression data enabled an improved oncological clinical analysis. This study focuses on a survival analysis of estrogen receptor (ER) positive breast cancer patients treated with tamoxifen. The chapter describes each step of the gene expression data analysis procedure, from the quali

EVADE

Artificial Immune Systems in Bioinformatics field of research is still in its infancy, several relevant results have been achieved by using the AIS paradigm in demanding tasks such as the ones coming from computational biology and biochemistry. The chapter will show how AIS have been successfully used in computational biology problems and wi

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Evolutionary Algorithms for the Protein Folding Problem: A Review and Current Trendsction of a protein is determined by the way it is folded into a specific tri-dimensional structure, known as native conformation. Understanding how proteins fold is of great importance to Biology, Biochemistry and Medicine. Considering the full analytic atomic model of a protein, it is still not pos

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Flexible Protein Folding by Ant Colony Optimizationunctions, predicting the folding structure of a protein to judge its functions is meaningful to the humanity. This chapter proposes a flexible ant colony (FAC) algorithm for solving protein folding problems (PFPs) based on the hydrophobic-polar (HP) square lattice model. Different from the previous