Epidemiology, Biostatistics and Bioinformatics
A.Y. 2023/2024
Learning objectives
The course aims to provide the necessary and indispensable notions of biomedical statistics, epidemiology, molecular epidemiology and bioinformatics for the design, development and interpretation of studies based on molecular and genomic methods. This knowledge is essential for the student to make the best use of the different molecular techniques and methodologies when applied in the practice of different fields (health, zootechnical, biological).
Expected learning outcomes
-) Ability to correctly apply epidemiological techniques in the evaluation of molecular and non-molecular diagnostic tests
-) Ability to correctly apply epidemiological techniques in the design of experimental and observational studies.
-) Ability to analyze structural genomics and gene expression data for the identification of genes related to mendelian and complex traits
-) Ability to use databases (ENSEMBL / NCBI) for genomic features annotation
-) Ability to correctly apply epidemiological techniques in the design of experimental and observational studies.
-) Ability to analyze structural genomics and gene expression data for the identification of genes related to mendelian and complex traits
-) Ability to use databases (ENSEMBL / NCBI) for genomic features annotation
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Teaching in a possible emergency phase will be carried out remotely and will maintain the same contributions and programs as the conventional one.
Course syllabus
Module: Bioinformatics and Biostatistics
1. Biostatistics vs. Bioinformatics;
2. Genomic data for structural, functional and epigenetic analysis;
3. Tools for the computerized analysis of molecular data, with particular reference to genomic data.
4. Statistical models for the analysis and biological interpretation of genomic, structural and expression data
5. Databases and tools available for bioinformatic analysis.
The lab practice will be carried out in the classroom on genomic data, using different software (including Excel and R) and databases available for bioinformatic analysis.
Module: Molecular epidemiology
The course has the aim to supply the basic and fundamental information on molecular epidemiology including the specific aspects concerning phylogenesis and molecular evolution. Student knowledge on molecular epidemiology are needed to apply in an efficient way molecular methods.
Lectures will cover the following topics:
1.Biostatistics: principles and applications.
2. Epidemiology: principles and applications.
3.introduction to molecular epidemiology
4.Principles and practice of taxonomy methods and pathogen classification by molecular methods
5.Statistical methods in molecular evolution
6.Building phylogenetic threes
7. Principles and practice of experimental design and of epidemiological studies for both infectious and zoonotic diseases
8. Principles and practice for the epidemiological analysis of data obtained from experiments and from field studies on both infectious and zoonotic diseases
1. Biostatistics vs. Bioinformatics;
2. Genomic data for structural, functional and epigenetic analysis;
3. Tools for the computerized analysis of molecular data, with particular reference to genomic data.
4. Statistical models for the analysis and biological interpretation of genomic, structural and expression data
5. Databases and tools available for bioinformatic analysis.
The lab practice will be carried out in the classroom on genomic data, using different software (including Excel and R) and databases available for bioinformatic analysis.
Module: Molecular epidemiology
The course has the aim to supply the basic and fundamental information on molecular epidemiology including the specific aspects concerning phylogenesis and molecular evolution. Student knowledge on molecular epidemiology are needed to apply in an efficient way molecular methods.
Lectures will cover the following topics:
1.Biostatistics: principles and applications.
2. Epidemiology: principles and applications.
3.introduction to molecular epidemiology
4.Principles and practice of taxonomy methods and pathogen classification by molecular methods
5.Statistical methods in molecular evolution
6.Building phylogenetic threes
7. Principles and practice of experimental design and of epidemiological studies for both infectious and zoonotic diseases
8. Principles and practice for the epidemiological analysis of data obtained from experiments and from field studies on both infectious and zoonotic diseases
Prerequisites for admission
None
Teaching methods
Frontal lessons with the aid of media supports, including specific software. Exercises through discussion for the development and application of epidemiological studies and genomic studies and analysis of data collected with specific software.
Teaching Resources
Bottarelli & Ostanello. Epidemiologia. Teoria ed esempi di medicina veterinaria - Edagricole 2011
- Thrusfield - Veterinary Epidemiology - IV edition Blackwell, 2018
- Riley Molecular Epidemiology of Infectious Diseases: Principles and Practices ASM 2004
- Foxman - Molecular Tools and Infectious Disease Epidemiology Ap 2011
-Class notes provided by the teachers
- Thrusfield - Veterinary Epidemiology - IV edition Blackwell, 2018
- Riley Molecular Epidemiology of Infectious Diseases: Principles and Practices ASM 2004
- Foxman - Molecular Tools and Infectious Disease Epidemiology Ap 2011
-Class notes provided by the teachers
Assessment methods and Criteria
Learning will be evaluated through the participation of the students in the practical phase and at the end of the course through an oral exam.
AGR/17 - LIVESTOCK SYSTEMS, ANIMAL BREEDING AND GENETICS - University credits: 3
VET/05 - INFECTIOUS DISEASES OF DOMESTIC ANIMALS - University credits: 5
VET/05 - INFECTIOUS DISEASES OF DOMESTIC ANIMALS - University credits: 5
Practicals: 24 hours
Lessons: 36 hours
Lessons: 36 hours
Professors:
Bagnato Alessandro, Zecconi Alfonso Agostino
Professor(s)