Bioinformatics for Horticultural Sciences
A.Y. 2025/2026
Learning objectives
The introduction of bioinformatics and computational biology into the area of plant biology is drastically accelerating scientific research in life science. Next-generation sequencing (NGS) technologies and other potent computational tools, which allow sequencing of whole genomes and transcriptomes, have led to the extensive studies of plants towards stress response, production physiology, and biodiversity on a molecular basis. Therefore, the utilization of bioinformatic tools is important to study and analyze the vast amount of data generated. The scope of this course is both to provide an overview of the tools available and to enable the student to perform real-case data analyses with a practical approach.
Expected learning outcomes
At the end of the course, the student will have an overview of the main plant bioinformatic techniques and tools. Moreover, he/she will be able to address the analysis and information mining of complex data sets. A basic knowledge of a programming and data analysis language (R and Bioconductor) is also expected.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
- Review of research methods and technologies and use of molecular markers.
- Practical examples of application of the tools described above in species of agricultural interest.
- The main software for the analysis of gene expression on a large scale.
- Methods of bioinformatic analysis of genomes.
- Principles and methods of metagenomic analysis.
- Introduction to the "R" scripting language and to the main packages of interest for bioinformatics applications.
- Overview of the Python programming language with practical examples.
- Fundamentals of database structure and management and analysis of some cases of agricultural interest.
- Methods of analysis of non-coding RNAs (search and analysis of expression).
- The main software for creating genetic maps and integrating with genomic projects.
- High-performance computing infrastructures (HPC) and examples of use of the INDACO university platform.
- Practical examples of application of the tools described above in species of agricultural interest.
- The main software for the analysis of gene expression on a large scale.
- Methods of bioinformatic analysis of genomes.
- Principles and methods of metagenomic analysis.
- Introduction to the "R" scripting language and to the main packages of interest for bioinformatics applications.
- Overview of the Python programming language with practical examples.
- Fundamentals of database structure and management and analysis of some cases of agricultural interest.
- Methods of analysis of non-coding RNAs (search and analysis of expression).
- The main software for creating genetic maps and integrating with genomic projects.
- High-performance computing infrastructures (HPC) and examples of use of the INDACO university platform.
Prerequisites for admission
- Students should already have knowledge of genetics, biochemistry, and molecular biology.
Teaching methods
- The course includes lectures and computer exercises.
Teaching Resources
- During the course, consultation texts, original articles, multimedia material and the PDF files containing the material illustrated in class and the subject of the practical exercises updated every year are suggested, which the student can download from the teacher's personal websites:
https://fgeunammmg.ariel.ctu.unimi.it/
https://fgeunammmg.ariel.ctu.unimi.it/
Assessment methods and Criteria
- The exam consists of a written test which may include the solution of applicative exercises, similar to those addressed in the classroom and the discussion of concepts covered in the course.
- Students with SLD or disability certifications are kindly requested to contact the teacher at least 15 days before the date of the exam session to agree on individual exam requirements. In the email please make sure to add in cc the competent offices: [email protected] (for students with SLD) o [email protected] (for students with disability).
- Students with SLD or disability certifications are kindly requested to contact the teacher at least 15 days before the date of the exam session to agree on individual exam requirements. In the email please make sure to add in cc the competent offices: [email protected] (for students with SLD) o [email protected] (for students with disability).
AGR/03 - ARBORICULTURE AND FRUITCULTURE - University credits: 6
Practicals: 32 hours
Lessons: 32 hours
Lessons: 32 hours
Professor:
Geuna Filippo
Professor(s)
Reception:
Free upon request by email
Dipartimento di Scienze Agrarie ed Ambientali (DISAA) letter "I" - Sezione di Coltivazioni Arboree" at page: https://www.unimi.it/sites/default/files/2019-01/SAAA_mappa_facolta.pdf