First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Medicine
Course unit
MEM0016063, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course 6 years single cycle degree in
ME1726, Degree course structure A.Y. 2015/16, A.Y. 2017/18
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Number of ECTS credits allocated 4.0
Type of assessment Mark
Course unit English denomination BIOINFORMATICS
Department of reference Department of Medicine
Mandatory attendance
Language of instruction Italian
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in MEDICINE AND SURGERY (Ord. 2015)

Teacher in charge STEFANO TOPPO BIO/10

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines BIO/10 Biochemistry 4.0

Course unit organization
Period Second semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 4.0 32 68.0 No turn

Start of activities 26/02/2018
End of activities 01/06/2018
Show course schedule 2019/20 Reg.2015 course timetable

Examination board
Board From To Members of the board
1 BIOINFORMATICA - COMMISSIONE D'ESAME A.A. 2013/2014 01/10/2013 31/12/2018 TOPPO STEFANO (Presidente)
FALDA MARCO (Membro Effettivo)

Prerequisites: basic knowledge of molecular biology and biochemistry
Target skills and knowledge: The course aims to provide a general overview of the most salient aspects of computer science applied to the analysis of biological data and in particular to data from omics projects such as genomics, proteomics and transcriptomics. The educational objective is to give consciousness to the student of a discipline that appears to be increasingly necessary and interdisciplinary in clinical and basic research. During the course the necessary elements will be provided for the achievement of a critical evaluation capacity on various aspects ranging from the design of complex experimental projects to the bioinformatics analysis of the generated data.
Examination methods: multiple-choice and exercises
Course unit contents: Elements of algorithms and their motivations

Introduction to computational biology and related motivations and methodologies; how to analyze the data called "Big Data" in the age of "omics" technologies.

Sequencing technologies
History of the first generation of DNA sequencing: Maxam-Gilbert and Sanger method; Revolution of NGS (Next Generation Sequencing) for massive data production; 2nd generation: Roche 454, Illumina, ABI Solid, IonTorrent; 3rd generation: Pacific Bio, Oxford NanoporeSequencing, Genia.

Sequence alignment
To introduce the problems of how to treat the DNA sequences generated, we will mention the basic algorithms of all the programs.

The problem of alignment; the dot plot matrices; exact local alignment algorithms, global, freeshift; dynamic programming; scoring of an alignment (edit distance, similarity); meaning of an alignment; multiple alignment of sequences; progressive and iterative algorithms; search in sequence database; BLAST and FASTA algorithms;

Molecular phylogeny
Introduction to the analysis of sequences belonging to different species; synonymous non-synonymous nucleotide substitutions; molecular clock; phylogenetic tree types and phylogenetic reconstruction methods; distance methods (UPGMA, Neighbor Joining, etc.); methods of maximum parsimony; Maximum Likelihood and Bayesian inference methods; bootstrap; advantages and disadvantages of the different phylogenetic reconstruction methods.

Assemblies of a genome and a transcriptome
Introduction to the problem of genome assembly; design and management of shot-gun genome project: short and long reads; database, sequence quality; assembly algorithms; creation of the contig; the problem of repeated sequences; management of mate-pairs sequences; the scaffolds or supercontig; finishing of a genome; analysis of the validity of the assemblies; Genome Browser for displaying data; RNA-Seq sequencing projects (RNA sequencing); analysis and management of splice variants: presence or lack of a complete reference genome or in draft.

Gene prediction
Introduction to the problems of gene prediction; prokaryotic and eukaryotic genomes: differences and complexity; recognition of Open Reading Frames (ORF); examples of predictors for eukaryotic and prokaryotic genomes; hybrid methods based on the use of transcript sequences; methods based on comparative genomics for identification of coding parts of a genome.

Introduction to databases of biological / biomedical interest

Gene ontology and function prediction on primary sequence
Introduction to ontologies in the biological / biomedical field; structure of a graph; the consortium of the Gene Ontology (GO) and the Gene Ontology Annotation; protein function prediction;

After the introduction on some basic themes of bioinformatics, some research areas of interest will be considered as:
1) Analysis of the microbiome: The microbiome is becoming increasingly important in terms of analysis and correlation with human diseases.
1) Analysis of gene variants: genome-wide association study (genome-wide association study GWAS) and haplotype analysis
Planned learning activities and teaching methods: lectures and the possibility of bioinformatic lab practice on some aspects covered during the course.
Additional notes about suggested reading: pdf/powerpoint slides
Textbooks (and optional supplementary readings)