Titlebook: Discovering Biomolecular Mechanisms withComputational Biology; Frank Eisenhaber Book 2006 Springer-Verlag US 2006 Amino acid.DNA.Nucleotid

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Prediction of Protein Function a life science research environment. The understanding of protein function is typically the main difficulty. This chapter intends to give practical advise to students and researchers that have only introductory knowledge in the field of protein sequence analysis..Applicable theoretical approaches r

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Literature and Genome Data Mining for Prioritizing Disease-Associated Genestarts with locating the mutations in a chromosomal band, as narrow as possible, and follows with the manual analysis of all the genes mapping in this region. Usually this is not an easy task, but it can be facilitated by complementary computational approaches that evaluate all genes in a region of i

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Theory of Early Molecular Evolutionssical cycle is then repeated generating the earliest picture of evolving Life. First, a consensus temporal order (“chronology”) of appearance of amino acids and their respective codons on evolutionary scene is reconstructed on the basis of 60 different criteria, resulting in the order: G, A, D, V,

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Hitchhiking Mappingand could be applied in an ecological context. This review focuses on the use of microsatellite markers in genome scans for the identification of beneficial mutations. The pitfalls and potential of the lnR6 test statistic are discussed as well as different approaches for the identification of the mo

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Understanding the Functional Importance of Human Single Nucleotide Polymorphismsding regions, contributes to phenotypic variation. However, much of the variation in coding regions may not produce any functional effects. There are two broad strategies for classifying polymorphism as functional or neutral: sequence-based methods predict functional significance based on conservati

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1431-0414 ction of gene function and gene-disease association), with t.In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans