Titlebook: Applications of Computational Intelligence in Biology; Current Trends and O Tomasz G. Smolinski,Mariofanna G. Milanova,Aboul-E Book 2008 Sp

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Phylogenomics, Protein Family Evolution, and the Tree of Life: An Integrated Approach between Molecus. The application of integrated computational and biological approaches may help to achieve a better system-based understanding of biological processes in different environments. This will help to fully access valuable information regarding the evolution of genes and genomes in the wide diversity of organisms.

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https://doi.org/10.37307/b.978-3-503-20967-5ith some promising paths for future research, aiming to identify areas of opportunity for those interested in the intersection of these two disciplines: multi-objective evolutionary algorithms and Biology.

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An Introduction to Multi-Objective Evolutionary Algorithms and Some of Their Potential Uses in Bioloith some promising paths for future research, aiming to identify areas of opportunity for those interested in the intersection of these two disciplines: multi-objective evolutionary algorithms and Biology.

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Statistically Based Pattern Discovery Techniques for Biological Data Analysissignificant associations. The rules resulting from this analysis capture all the patterns observable within a data set for which a statistically sound rationale is available. The validity of such patterns recommends their use in cases where the rationale underlying a decision must be understood. Hig

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Rough Sets In Data Analysis: Foundations and Applicationsea proposed by Z. Pawlak in 1982 goes back to classical idea of representing uncertain and/or inexact notions due to the founder of modern logic, Gottlob Frege: uncertain notions should possess around them a region of uncertainty consisting of objects that can be qualified with certainty neither int

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