Bioinformatics

Educational objectives

Principles of mathematics 1:
The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The first semester (Principles of Mathematics 1) will be devoted mainly to the study of functions of one variables, including limits, derivative and integrals. Basic optimisation results for functions of one variable will also be considered

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Principles of Mathematics 2:

The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The second semester (Principles of Mathematics 2) will be devoted mainly to the study of functions of several variables, linear algebra, and differential equations. Basic optimization results for functions of several variables will also be considered.

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Educational objectives

Principles of mathematics 1:
The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The first semester (Principles of Mathematics 1) will be devoted mainly to the study of functions of one variables, including limits, derivative and integrals. Basic optimisation results for functions of one variable will also be considered

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Principles of Mathematics 2:

The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The second semester (Principles of Mathematics 2) will be devoted mainly to the study of functions of several variables, linear algebra, and differential equations. Basic optimization results for functions of several variables will also be considered.

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Educational objectives

Principles of mathematics 1:
The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The first semester (Principles of Mathematics 1) will be devoted mainly to the study of functions of one variables, including limits, derivative and integrals. Basic optimisation results for functions of one variable will also be considered

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Principles of Mathematics 2:

The aim of this course is to give the student sound mathematical basis in calculus of one or several variables and optimization in a way appropriate for a student of bioinformatics. An emphasis is given to applications and intuitive understanding of the underlying concepts. The second semester (Principles of Mathematics 2) will be devoted mainly to the study of functions of several variables, linear algebra, and differential equations. Basic optimization results for functions of several variables will also be considered.

Knowledge and understanding

The aim of the course is to give students a basic

understanding of calculus in a way appropriate to bioinformatics students. Students will also be exposed to mathematics proofs as an example of rigorous scientific reasoning.

Applying knowledge and understanding

By the end of the course, students will be able to use basic mathematical tools as applied to different environments. They will also be able to interpret in a critical way

results obtained by applying mathematical modelling technique.

Making judgements

Lectures and practical exercises will provide students with the basic ability in

assessing the main strengths and weaknesses of mathematical models when used to explain empirical evidence.

Communication

By the end of the course, students will have basic mathematical skills that will help them to talk in an appropriate way about quantitative models.

Lifelong learning skills

Students are expected to develop learning skills necessary to undertake additional and more advanced studies involving mathematics and mathematical modelling in biology.

Educational objectives

This course is an introduction to chemistry fundamentals addressed to students with limited chemistry background. The purpose of the course is to provide students with the knowledge of general chemistry principles, and with the tools to solve simple chemistry problems. At the end of the course the students are expected to know ho to apply the acquired chemical concepts to different fields, including pharmaceutical chemistry and biochemistry which are the subjects of further courses.
The course aims to provide a correct knowledge of the fundamental principles of organic chemistry, proposing the contents into two distinct phases that are closely and logically linked. In the first phase the teaching is addressed to provide basic knowledge about classification and nomenclature of organic compounds, about the symbolism used to represent both structures and reactions, as well as over the chemical-physics, acid-base, nucleophilic-electrophilic properties of the considered compounds. In the second phase the teaching is instead focused on the description of the different reactivity involved by different classes of compounds, rationalizing the study through the analysis of the relevant mechanisms. In the context of the described methodology the objectives to be achieved are: 1) attainment of a suitable degree of specialized knowledge, understood as the ability to invoke theories, rules, nomenclature etc.; 2) capacity to properly interpret and process the reaction schemes and propose alternatives to the encountered syntheses; 3) establish connections between different studied subjects.

Educational objectives

This course is an introduction to chemistry fundamentals addressed to students with limited chemistry background. The purpose of the course is to provide students with the knowledge of general chemistry principles, and with the tools to solve simple chemistry problems. At the end of the course the students are expected to know ho to apply the acquired chemical concepts to different fields, including pharmaceutical chemistry and biochemistry which are the subjects of further courses.
The course aims to provide a correct knowledge of the fundamental principles of organic chemistry, proposing the contents into two distinct phases that are closely and logically linked. In the first phase the teaching is addressed to provide basic knowledge about classification and nomenclature of organic compounds, about the symbolism used to represent both structures and reactions, as well as over the chemical-physics, acid-base, nucleophilic-electrophilic properties of the considered compounds. In the second phase the teaching is instead focused on the description of the different reactivity involved by different classes of compounds, rationalizing the study through the analysis of the relevant mechanisms. In the context of the described methodology the objectives to be achieved are: 1) attainment of a suitable degree of specialized knowledge, understood as the ability to invoke theories, rules, nomenclature etc.; 2) capacity to properly interpret and process the reaction schemes and propose alternatives to the encountered syntheses; 3) establish connections between different studied subjects.

Educational objectives

The goal of this course is to teach students the basic programming skills needed to deal with bioinformatics data. At the end of the course the students will be able to:

- model problems of medium difficulty and solve them by programming;
- decompose complex programming problems into simpler problems;
- design and implement programs;
- test programs;
- analyze programs in terms of their correctness and efficiency;
- use Python and its libraries.

Educational objectives

This course is an introduction to chemistry fundamentals addressed to students with limited chemistry background. The purpose of the course is to provide students with the knowledge of general chemistry principles, and with the tools to solve simple chemistry problems. At the end of the course the students are expected to know ho to apply the acquired chemical concepts to different fields, including pharmaceutical chemistry and biochemistry which are the subjects of further courses.
The course aims to provide a correct knowledge of the fundamental principles of organic chemistry, proposing the contents into two distinct phases that are closely and logically linked. In the first phase the teaching is addressed to provide basic knowledge about classification and nomenclature of organic compounds, about the symbolism used to represent both structures and reactions, as well as over the chemical-physics, acid-base, nucleophilic-electrophilic properties of the considered compounds. In the second phase the teaching is instead focused on the description of the different reactivity involved by different classes of compounds, rationalizing the study through the analysis of the relevant mechanisms. In the context of the described methodology the objectives to be achieved are: 1) attainment of a suitable degree of specialized knowledge, understood as the ability to invoke theories, rules, nomenclature etc.; 2) capacity to properly interpret and process the reaction schemes and propose alternatives to the encountered syntheses; 3) establish connections between different studied subjects.

Educational objectives

The course aims to provide a correct knowledge of the fundamental principles of organic chemistry, proposing the contents into two distinct phases that are closely and logically linked. In the first phase the teaching is addressed to provide basic knowledge about classification and nomenclature of organic compounds, about the symbolism used to represent both structures and reactions, as well as over the chemical-physics, acid-base, nucleophilic-electrophilic properties of the considered compounds. In the second phase the teaching is instead focused on the description of the different reactivity involved by different classes of compounds, rationalizing the study through the analysis of the relevant mechanisms. In the context of the described methodology the objectives to be achieved are: 1) attainment of a suitable degree of specialized knowledge, understood as the ability to invoke theories, rules, nomenclature etc.; 2) capacity to properly interpret and process the reaction schemes and propose alternatives to the encountered syntheses; 3) establish connections between different studied subjects.

Educational objectives

The course has the objective to deepen the practical understanding of the use of probability and statistics in the context of epidemiological/biomedical research.

In particular the students will learn the differences between the main epidemiological study designs, suitable measures of treatment/exposure effect , the concepts of bias, variability, confounding and causality in epidemiology. They will also learn the concept and application of linear regression and have an introduction to logistic regression. Furthermore they will learn how to manage data and apply statistical methods using the software Stata.

Educational objectives

Educational objectives
The educational goal of the course is students' learning of the fundamentals of probability calculus and statistics.

Knowledge and understanding
At the end of the course, students know and understand how to formalize the uncertainty, how to describe a population in quantitative terms and how to make inference about unknown parameters.

Ability to apply knowledge and understanding
Students learn how to formalize a problem in the field of probability calculus or statistics.

Judgment independence
The discussion of the various methods provides students with the skills necessary to analyze real situations critically and independently.

Communicative skills
Students acquire the basic elements for reasoning in quantitative terms about uncertainty and statistical problems.

Learning skills
Students who pass the exam are able to apply the methods learned in different application contexts.

Educational objectives

The course has the objective to deepen the practical understanding of the use of probability and statistics in the context of epidemiological/biomedical research.

In particular the students will learn the differences between the main epidemiological study designs, suitable measures of treatment/exposure effect , the concepts of bias, variability, confounding and causality in epidemiology. They will also learn the concept and application of linear regression and have an introduction to logistic regression. Furthermore they will learn how to manage data and apply statistical methods using the software Stata.

Educational objectives

Students acquire the knowledge and thinking skills necessary to understand biological problems in a evolutionary perspective. The course will provide students with understanding of the basic molecular mechanisms that operate in living cells, with a focus on the flow of genetic information.

Educational objectives

Students acquire the knowledge and thinking skills necessary to understand biological problems in a evolutionary perspective. The course will provide students with understanding of the basic molecular mechanisms that operate in living cells, with a focus on the flow of genetic information.

Educational objectives

Students acquire the knowledge and thinking skills necessary to understand biological problems in a evolutionary perspective. The course will provide students with understanding of the basic molecular mechanisms that operate in living cells, with a focus on the flow of genetic information.

Educational objectives

General skills
The course of Genetics and computational genomics provides students with a basic knowledge of Genetics aimed at understanding the rules of inheritance, their molecular bases, their main applications and their implications for evolution. In addition, the course will allow students to understand how genetic information is encoded at the DNA level and how it contribute to phenotypic variability. Fundamentals concepts in functional genetics and evolution will be reconsidered in light of the sequencing and re-sequencing projects. The student will be also provided of practical and theoretical tools to solve genetic problems and to use databases for storage, management, analysis, and visualization of genetic data.

Specific skills

A) Knowledge and understanding
-Knowledge and understanding of the characteristics of the genetic material
-Knowledge and understanding of the rules of genetic transmission
-Knowledge and understanding of mutations and their implications
-Basic knowledge on the dynamics of genes in populations as well as on the genetic mechanisms underlying evolution
- Knowledge and understanding of informatic methods used for genomic analyses

B) Applying knowledge and understanding
- Usage of a proper genetic terminology
- Identification of the right procedures to solve genetic problems
- Formulation of hypotheses on the hereditary transmission of characters
- Constructing and interpreting genetic maps and genealogical trees
- Acquisition of conceptual tools for the genetic dissection of biological systems
- Management of genomic browsers and programs for storage, management analysis, and visualization of “big data”

C) Making judgements
- Acquisition of a critical judgment capacity on solving problems of formal genetics, through the study of the evolution of the gene concept from Mendel to the present day and the detailed analysis of some fundamental experiments
- Addressing questions for the elaboration and deepening of the gained information

D) Communication skills
- Communicating the genetic concepts acquired during the course with appropriate terminology

E) Learning skills
- Logically connecting the acquired knowledge
- Identification of the most relevant topics of the issues discussed during the course

Educational objectives

The course aim to introduce the algorithmic approach to solving problems correctly and efficiently. Algorithms are ubiquitous in bioinformatics and are often at the interface of computer science and biology. Well established algorithmic techniques will be studied as well as ways to encode them in a computer programme using python.

Educational objectives

Microorganisms play a key role in the environment, in human health and in biotechnological research.
The course of Microbiology aims to provide the basic principles of structure, function and evolution of microbial cells, with particular regard to bacterial cells.The knowledge and skills acquired during this course will represent a starting point for the application of bioinformatics and -omics tools to study microorganisms and microbial communities, and for the investigation of their impact on human health and the environment.
Students who have passed the exam will know and understand (acquired knowledge)

The structural and functional diversity which is present in the microbial world;
The mechanisms responsible for the structure and functioning of bacterial cells;
The mechanisms responsible for the evolution of bacterial species;
The structure and life cycles of viruses;
The methods used to analyze microbial communities, their gene expression and their metabolic profile.

Students who have passed the exam will be able to (acquired skills):
Understand and analyse microbiological data;
Critically analyze the issues related to the evolution;
Understand and design experimental and bioinformatics approaches.

Educational objectives

General goals
The course aims to introduce the students to the links between DNA, RNA and protein structure and their relevant biological functions with particular emphasis on the bioinformatic approaches to their analysis.
Specific goals:
1. Knowledge and comprehension: the students will have to know the molecular mechanisms which regulate cellular homeostasis and gene expression and the most utilized methodologies in Molecular Biology.
2. Ability in applying Knowledge and comprehension: the students will have to be able to apply this knowledge in the discussion of specific arguments of recent and general interest with a particular focus on the bioinformatic approaches.
3. Abilities in judging methodologic approaches and communication skill: The students will have to show skills in judging strategies in biological problems solving and to communicate their conclusions to the teacher and to the colleagues. This is also applicable to the practical training sessions.
4. The students will have to show skill in applying what they have learned in molecular biology to specific problems to be solved with a bioinformatic approach.

Educational objectives

General goals
The course aims to introduce the students to the links between DNA, RNA and protein structure and their relevant biological functions with particular emphasis on the bioinformatic approaches to their analysis.

Specific goals
1. Knowledge and comprehension: the students will have to know the molecular mechanisms which regulate cellular homeostasis and gene expression and the most utilized methodologies in Molecular Biology.
2. Ability in applying Knowledge and comprehension: the students will have to be able to apply this knowledge in the discussion of specific arguments of recent and general interest with a particular focus on the bioinformatic approaches.
3. Abilities in judging methodologic approaches and communication skill: The students will have to show skills in judging strategies in biological problems solving and to communicate their conclusions to the teacher and to the colleagues. This is also applicable to the practical training sessions.
4. The students will have to show skill in applying what they have learned in molecular biology to specific problems to be solved with a bioinformatic approach.

Educational objectives

Learning results
This course is aimed at providing an overview of the most important cellular and molecular mechanisms involved in the regulation of the immune response. The factors regulating immune system will be put in relation to the molecular mechanisms governing resistance against pathogens and promoting pathologies related to a defective immune response.
Specific aims
Student will acquire fundamental knowledge on
- how immune cells function and interplay to participate to immune responses
- how immune system protects us from pathogens and how mechanisms that inhibit immune responses lead to disease state.
- how interpretation of transcriptomic and proteomic data helps to elucidate mechanisms of development of the immune response.
At the end of the course, students will be able to explain how immune system works and to understand and explain data obtained from multiparametric analysis of immune cell function at transcriptional and post-transcriptional levels. The use of bioinformatics tools to clarify the molecular processes underlying pathologies and their use in diagnosis and treatment of diseases will be discussed.
At the end of the course, students will be able to perform bibliographic searches in public scientific data banks (i.e. PubMed) to develop the topics covered in the course. This will be instrumental to identify the most recent methods of bioinformatic analysis used to approach immunology issues. The independent ability of the student to propose solutions to solve immunological questions is and aim of the course.
Communication skills will be verified during the course by stimulating discussion and implemented by suggestions and the critical analysis of the slides presented during the course

Educational objectives

General goals
The course aims to introduce the students to the links between DNA, RNA and protein structure and their relevant biological functions with particular emphasis on the bioinformatic approaches to their analysis.
Specific goals:
1. Knowledge and comprehension: the students will have to know the molecular mechanisms which regulate cellular homeostasis and gene expression and the most utilized methodologies in Molecular Biology.
2. Ability in applying Knowledge and comprehension: the students will have to be able to apply this knowledge in the discussion of specific arguments of recent and general interest with a particular focus on the bioinformatic approaches.
3. Abilities in judging methodologic approaches and communication skill: The students will have to show skills in judging strategies in biological problems solving and to communicate their conclusions to the teacher and to the colleagues. This is also applicable to the practical training sessions.
4. The students will have to show skill in applying what they have learned in molecular biology to specific problems to be solved with a bioinformatic approach.

Educational objectives

General goals
The course aims to introduce the students to the links between DNA, RNA and protein structure and their relevant biological functions with particular emphasis on the bioinformatic approaches to their analysis.
Specific goals:
1. Knowledge and comprehension: the students will have to know the molecular mechanisms which regulate cellular homeostasis and gene expression and the most utilized methodologies in Molecular Biology.
2. Ability in applying Knowledge and comprehension: the students will have to be able to apply this knowledge in the discussion of specific arguments of recent and general interest with a particular focus on the bioinformatic approaches.
3. Abilities in judging methodologic approaches and communication skill: The students will have to show skills in judging strategies in biological problems solving and to communicate their conclusions to the teacher and to the colleagues. This is also applicable to the practical training sessions.
4. The students will have to show skill in applying what they have learned in molecular biology to specific problems to be solved with a bioinformatic approach.

Educational objectives

This course provides the students with the theoretical knowledge and technical skills and introduce them to the structure and properties of pharmaceutical agents and metabolites. The course outlines the structure, bonding and chemical reactivity of various important classes of organic molecules, ranging from simpler examples of hydrocarbons or those containing a single functional group, to some of the important biological molecules such as carbohydrates, nucleic acids and proteins. Topics include basic concepts in medicinal chemistry: 1) the drug discovery and development process, 2) review of organic functional groups found in drug molecules, 3) drug-target interactions, 4) physicochemical properties related to drug action such as acid-base properties, equilibrium, and stereochemistry, 5) Effect of chemical structure on the metabolism of drug molecules.
By completing Pharmaceutical Chemistry, the student acquires:
1. Recognize and describe zero-, first- and second-order kinetics, perform elementary calculations of rate constants and appreciate the role of enzymes in catalysis.
2. Integrate knowledge from foundational sciences to explain how specific drugs or drug classes work and evaluate their potential value in individuals and populations.
3. Apply knowledge in foundational sciences to solve therapeutic problems.
4. Demonstrate an understanding of the therapeutic potential of a candidate molecule and how chemical properties can affect its potential to become a new drug.

Educational objectives

General Objectives

Bioinformatics is a multidisciplinary field that integrates biology, computer science, mathematics, and statistics. It includes the development and implementation of computational methods and tools to manage, decipher, and interpret the large amount of biomolecular data available today.
It is widely recognized that bioinformatics is fundamental for translational research and the success of molecular medicine.

The aim of the course is to provide students with:

familiarity with bioinformatics tools, databases, and programming languages;

the ability to implement, interpret, and present the results of typical bioinformatics analyses;

the competence to critically discuss current limitations and contribute to the design of next-generation tools;

practical experience in analyzing “omics” sequencing data and protein sequences using a combination of cutting-edge tools and programming languages.

Specific Skills

Students who successfully complete the exam will be able to:

analyze transcriptomics data (RNA-seq and Microarray);

develop a lightweight and reusable RNA-seq pipeline (mapping and transcript reconstruction);

perform read mapping from deep sequencing data;

understand the most common file formats for “omics” data;

interpret “omics” data with functional analysis;

have basic knowledge of the R programming language;

have basic proficiency in Linux command line and shell scripting;

report results in a reproducible way;

understand and select appropriate bioinformatics tools and databases for their investigation;

analyze protein sequences to identify domains and functional motifs;

predict protein structure (secondary and tertiary) using computational tools;

utilize databases and tools for structural bioinformatics (e.g., PDB, AlphaFold, PyMOL);

interpret structural data in relation to biological function and biomedical applications.

Applying Knowledge and Understanding

Students will be able to:

integrate information collected from different sources (datasets, lectures, scientific literature);

apply NGS-based technologies to transcriptomics data;

set up bioinformatics pipelines for transcriptomic analyses using open-source software;

design workflows for protein sequence and structure analysis;

ensure reproducibility and scalability of bioinformatics approaches.

Communication Skills

Students will be able to:

deliver oral presentations of scientific data analyses;

create detailed analysis reports and effective presentations;

communicate results on “omics” and structural data, integrating sequence, structure, and function of proteins.

Learning Skills

Logically connect the acquired knowledge.

Identify the most relevant issues discussed during the course.

Develop autonomy in learning new bioinformatics tools, with special focus on structural bioinformatics and computational proteomics.

Educational objectives

This course offers an introduction to network medicine, a rapidly emerging field that integrates systems biology and network science. It runs counter to the prevailing scientific reductionist trend that dominates current medical research on disease etiology and treatment. Reductionism relies on single molecules or single genes to provide comprehensive and robust insights into the pathophysiology of complex diseases. Similarly, current drug development methodologies target single molecules that very frequently fail because of the unforeseen and unintended effects that result from the application of this piecemeal approach to pharmacology. In contrast, network medicine emphasizes a more holistic approach through the identification and investigation of networks of interacting molecular and cellular components. When network medicine is integrated into biomedical research, it has the potential to transform investigations of disease etiology, diagnosis, and treatment.

The course will explore the concept of network medicine through: (1) a review of the role, identification, and behavior of networks in biology and disease, (2) the integration of multiple types of -omics data into networks as a paradigm for understanding disease expression and course, and (3) systems pharmacology approaches for the development and evaluation of effective therapies of complex disease.

Moreover, this course will provide hands-on experience in the analysis of two specific types of biological networks—gene co-expression networks and drug-disease networks. During the course, attendees will apply the theory to real data sets.
After completing the course, attendees should to be able to apply these methods in their own research.

The course goals are:

Understand the role of networks in biology and disease.
Understand networks as a paradigm for disease expression and course.
Understand the challenges of developing effective therapies for complex diseases.
Understand the role of omics data in networks.
Understand network medicine in terms of investigation for disease etiology, diagnosis, and treatment.

Educational objectives

The Bioethics course provides the students with tools to understand, discuss, present and address ethical issues relevant to bioinformatics, at the intersection between biological and technological sciences.
In order to respond to the course requirements, the students will also acquire general skills such as doing a bibliographic research on academic databases, speaking and arguing in public by using specialized bioethical concepts and theories, and writing a little paper in an academic format including a bibliography.

Educational objectives

General skills
The new generation of sequencing technologies has provided unforeseen chances for high-throughput functional genomic studies. These technologies have been applied in a variety of contexts, including whole-genome sequencing, discovery of transcription factor binding sites, mapping out the DNA accessibility and RNA expression profiling. Intriguingly, recent annotation efforts focused on the discovery of novel noncoding RNA genes and regulatory elements that control temporal or spatial gene expression along cell differentiation. The course of Molecular Biology and Genomics is designed to provide students with an introduction to the structure and function of genomes and transcripts in humans and in other model organisms. Topics discussed will include modern genome sequencing technologies, as well the recent in silico and in vivo approaches used for functional genomics and for the functional role of emerging non-coding RNA classes (practical examples taken from recent literature will be used). The course also provides students with basic knowledge for accessing browsers and public databases for the analysis of gene expression data, GO and miRNA target prediction software.
By the end of the course, students will be able to apply the acquired knowledge to the study of the basic mechanisms of gene expression, as well as of complex processes such as development, cell division and differentiation, and to exploit them for a practical use in both basic and applied research.

Specific skills
The students who have passed the exam will be able to know and to understand (acquired knowledge)

- the origin and the maintenance of the biological complexity;
- the structure and function of the genome in humans and in the main model systems;
- the problems and technologies of genome-wide analyses applied to biological processes;
- the influence of the modern sequencing technologies for a better description and for the study of transcriptome dynamics in humans and in the main model systems;
- the network of interactions between the biological molecules in the mechanisms of regulation of gene expression.

The students who have passed the exam will be able to (acquired expertise):
- interpret the biological phenomena in a multi-scale and multi-factorial context;
- interpret the results of genomic studies and to discriminate which techniques to apply according to the different problems to be dealt with in the genomic field;
- report works already present in the literature in the form of an oral presentation.

Educational objectives

The final exams consists of writing, presenting and discussing a thesis, developed autonomously
by the students, which illustrates in a coherent and detailed manner the
problem tackled during the practical training and all the activities carried
out to develop its solution.

Educational objectives

Acquisition of manual, methodological and organizational skills aimed at the elaboration of technical-scientific issues.

Educational objectives

Basic training in laboratorytechniques aimed to improve professionalization.