Module Details

Bioinformatics, genomics and genetics applied to environment and food interaction with human health: Applied bioinformatics

MF0337

Course
Bioinformatics, genomics and genetics applied to environment and food interaction with human health: Applied bioinformatics
Code
MF0337
Academic Year
2024/2025
Curriculum Year
2023/2024
Degree Programme
FOOD HEALTH AND ENVIRONMENT
Curriculum
000 - CORSO GENERICO
Course coordinator
Lecturers
Credits
5
Lecture Hours
40
Scientific Disciplinary Sector (SSD)
BIO/11 - Molecular Biology
Course Type
Single-subject learning activity
Course Delivery
OBB - Obbligatoria
Year
2
Teaching period
Secondo Semestre
Campus
VERCELLI
Teaching language
English
Course Contents
The course aims to provide adequate knowledge of the molecular basis of biological systems, the structure and functions of biological macromolecules and the cellular processes in which they intervene; technological and biotechnological platforms of omics analysis (genomics, transcriptomics, proteomics); bioinformatics analysis tools and omics data; IT methods for biomolecular data management and analysis.
Case studies and practical exercises are proposed, focusing on the analysis of the interaction between food, environment, and human health.
Students will receive a theoretical and practical introduction to genomic and protein sequence databases and computer tools for data retrieval, mining, visualisation, and analysis.
Reference Texts
The educational material will consist of the material used in class, as well as scientific articles and manuals, the references for which will be provided during the lessons.
Students who need to deepen their understanding of the biological aspects are recommended the following text: Arthur Lesk, 'Introduction to Genomics,' Oxford University Press.
Learning Outcomes
To provide a basic overview of the most used bioinformatics tools in the field of research on the interaction between food, environment and human health. To provide basic skills in reading and interpreting scientific articles with bioinformatics content.
Prerequisites
Basic knowledge in molecular biology and genetics.
Teaching Methods
Lectures, analysis of case studies, computer lab exercises and lessons using application software and online tools.
Additional Information
Classes are designed to be very interactive. Students work in groups and carry out analytical projects by putting into practice the principles learned in class.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request
specific services and tools via the
, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities

Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination
modalities, concerning academic aspects.
Assessment Methods
In-class exercises will be conducted throughout the course on the topics covered in the lectures.
Additionally, each group will present their Analysis Project during an oral presentation at the end of the course, and the results of the data analysis in a report to be submitted within two weeks of the exam date.
The final oral examination will consist of questions regarding the group projects and the general topics covered in the course.
The final grade will be based on the quality and punctuality of the practical exercises and the report on the group project results."
Detailed Syllabus
Introduction to bioinformatics: definition, objectives, terminology, applications, and limitations.

Implication of genomics/bioinformatics for health and nutrition: understanding the molecular mechanisms underlying the relationships between food and health, from basic nutrient actions to the interactions between food microorganisms and the human intestinal system.

How to explore the knowledge: the use of PubMed to search the Medline scientific literature database, how to build an efficient and specific research string, how to plan a literature search.

The sequencing process: Sanger chain-termination method and automated fluorescence sequencing, the Next-generation sequencing method.

The sequencing data: Bioinformatics databases and tools, how to explore the main repository of genomic data:
• Genome browsers and analysis platforms: NCBI Genome (organises NCBI’s information on genomes including sequences, maps, chromosomes, assemblies, and annotations), ENSEMBL (the European eukaryotic genome resource web server), UCSC Genome Browser (the site for the genomic programme at the University of California, Santa Cruz), and Gramene genome browser (as part of the Gramene project that aggregates tools for Comparative plant genomics for crops and model organisms). Learn how they are structured, how to personalise the data displayed and how to extract information from them and. how to use them efficiently.
• The NCBI’s Blast tool: how to use it to determine the putative role of a DNA or protein sequence that are newly identified; and to find out whether a genome (or the other large sequence database) has a comparable sequence with a recognised gene.
• Gene expression database: the example of Human Protein Atlas.

How gene expression is epigenetically regulated, the example of DNA methylation. How do the laboratory analysis work, the Illumina Infinium method and the NGS method.
• The EWAS Toolkit a web toolkit for epigenome-wide association study, how to use it and understand the results.

Looking for a meaning: metabolic pathway and network of protein interaction, tools for visualization, and integrated discovery.
• The gene ontology and the food ontology, how they work and how to use them.
• Pathway analysis: learn how to integrate the extensive information on metabolic pathways available in the literature and databases, explore the protein function and interaction using the Kegg database, String, and Reactome.
• How to query the Database for Annotation, Visualization and Integrated Discovery (DAVID). this website provides a comprehensive set of functional annotation tools for investigators to understand the biological meaning behind large lists of genes.

How to report the results, presentation and discussion of the projects conducted by students over the course.
Expected Learning Outcomes
By the end of the course, students will have a deeper understanding of the principles of bioinformatics and will be able to use basic bioinformatics tools and techniques to visualise, analyse and interpret biological data. They will learn how to obtain information on the internet to build background knowledge on a topic related to the interaction between food, the environment and human health. They will also improve their critical thinking, learn to collaborate and carry out a research project.
Last update:09-09-2026 00:14:31