Titlebook: Genome Data Analysis; Ju Han Kim Textbook 2019 Springer Nature Singapore Pte Ltd. 2019 Genome data analysis.Bioinformatics.Practice in dat

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https://doi.org/10.1007/978-1-4842-3712-0ta. Analysis requires one to have a thorough understanding of basic biology. We will go over gene sets used to interpret data as well as analyzing data. DAVID, ArrayXPath are two apparatuses used to gather fundamental biological interpretation using gene sets given. BioLattice is also designed to an

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Ju Han KimDescribes recent advances in genomics and bioinformatics.Provides numerous examples of genome data analysis.Meets the needs of life scientists, medical scientists, and others who are new to the field

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Mohamad Al Ali,Michal Tomko,Ivo DemjanThe objectives of this chapter are to teach generating DEGs in microarray gene expression data, extracting a gene cluster of genes with similar patterns of expression, classifying the observed data using SVM and KNN, and learning the basic syntax of the R program, a useful tool for genome data analysis.

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Mladen Kezunovic,Jinfeng Ren,Saeed LotfifardIn this chapter, in order to investigate the biological function, we will practice verifying existing knowledge with concurrent experiments on microarray data analysis to identify significant correlations of miRNA-mRNA pairs derived from the miRNA and mRNA analysis profile of the same sample.

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