FUNCTIONAL GENOMICS

Course objectives

General skills: The course aims to introduce the students to the main approaches to functional genomics. Students will learn to apply the high-throughput techniques based on DNA microarrays and Next Generation Sequencing (NGS), measuring their potentials and their problems and limits. Focus will be placed on data mining methodologies, from image analysis to data normalization and statistical filtering to gene clustering and gene ontology. The availability of functional database and their use for improving biomedical research will also be explained. Specific skills: The course aims to introduce the students to the main approaches to functional genomics, using the most advanced model systems currently available. Students will learn the principles and the perspectives of application of the high-throughput techniques based on DNA microarrays and Next Generation Sequencing (NGS), measuring their potentials and their problems and limits. Focus will be placed on data mining methodologies, from image analysis to data normalization and statistical filtering to gene clustering and gene ontology analysis. The perspectives of next generation sequencing in extending the limits of DNA microarray technology will also be illustrated. At the end of the course students should be able to critically read papers from scientific literature and research projects in the functional genomics field and understand methodological choices, perspectives, eventual problems and week points.

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RODOLFO NEGRI Lecturers' profile

Program - Frequency - Exams

Course program
Functional genomics and high-throughput methodologies: Next generation sequencing and array-based techniques ; DNA microarrays technology: designing an experiment ; Preparing targets, labeling and hybridization; Image analysis, normalization and statistical filtering; Microarray analysis softwares; False discovery rate and experimental design ;Gene clustering and data mining methods;Gene ontology Il metaclustering; Local and general Databases; model organisms’ Databases; Chromatin Immunoprecipitation; Genomic localization of proteins; Transcriptional regulation of cell cycle ; Damage response; Transcriptional networks in eukaryotic genomes; Genome-wide analysis of epigenetic modifications; Protein Interaction networks and functional networks. Functional Genomics and high-throughput techniques: Microarrays and next generation sequencing 0.3 CFU DNA microarrays technology – experimental design 0.3 Target selection, probe labeling and hybridization 0.3 Data normalization and statistical filtering 0.2 Softwares for microarray analysis 0.3 False discovery rate and data significance 0. 2 Gene clustering methods and data mining 0.4 Gene ontology 0.4 Meta-clustering and meta-analysis 0.4 Using microarrays for pathology profiling 0.2 RNAseq Methodologies 0.2 Pipeline for processing RNAseq data 0.2 Transcriptomics databases 0.2 Model Organisms Databases 0.2 Chromatin Immunoprecipitation 0.2 Genomic mapping of proteins (ChIP on chip and Chipseq) 0.3 Analysis of genetic interactions 0.2 Analysis of physical interactions 0.2 Transcriptional networks and their evolution 0.3 Genomewide chromatin modification analysis 0.4 Techniques for studying single cell transcriptome and epigenome 0.2 Models for systems’ biology 0.2 Microbiome analysis tools 0.2
Prerequisites
Basic Knowledge of Molecular Biology
Books
Materials available on Moodle plattform
Frequency
Four hours in a week
Exam mode
Videopresentation of papers from scientific literature
Lesson mode
Front lessons with viedeoprojection
  • Lesson code1035089
  • Academic year2025/2026
  • CourseBiotechnology and Genomic for Industry and Environment
  • CurriculumSingle curriculum
  • Year1st year
  • Semester2nd semester
  • SSDBIO/11
  • CFU6