Functional Genomics

• Functional Genomics and Phenotypic Impacts: Correlation of gene expression with physiological or pathological conditions. Analysis of genomes from model organisms. Strategies for linking variants to traits.
• Sequencing and Genome Analysis: DNA sequencing methods, from first-generation sequencing (Sanger) to next-generation sequencing (NGS) technologies. Tools for genome assembly, alignment, and annotation.
• Next-Generation Sequencing (NGS) Data Analysis: Basic principles of data preprocessing, quality control, alignment to reference genome.
• Bioinformatics Approaches to RNA: Introduction to transcriptome studies, types of RNA (mRNA, ncRNA, miRNA, lncRNA), RNA-seq methodologies, tools for differential gene expression analysis.
• Gene Expression Analysis: Microarray and RNA-seq technologies. Approaches for normalization, statistical analysis of differential expression, visualization (heatmaps, PCA). Comparison of methodologies and applications.
• Databases and Software Tools for Functional Genomics: Familiarity with databases such as Ensembl, UCSC Genome Browser, GTEx, Expression Atlas. Use of software tools like Galaxy, Bioconductor, and IGV.

Βιοπληροφορική και Λειτουργική Γονιδιωματική, 3η Έκδοση , Jonathan Pevsner Εκδόσεις, Ακαδημαϊκές Εκδόσεις. 2019