Multilevel Computational Modelling of Human Diseases
A.Y. 2025/2026
Learning objectives
The course has the aim of providing to the students the state-of-art information about two central topics about numerical/quantitative modelling methodologies in the realm of molecular biotechnologies:
a. the computational and experimental characterization of biomolecular interactions;
b. the analysis of cell-based "omics" data in the context of human diseases.
These two topics have the purpose of covering the roots of the molecular interpretation of human diseases and, at the same time, of instructing the students about the choice of the right technologies that can be used according to the type and the level of details required. This will be exemplified by the instructors by means of an alternation of frontal lectures and hands-on practicals.
a. the computational and experimental characterization of biomolecular interactions;
b. the analysis of cell-based "omics" data in the context of human diseases.
These two topics have the purpose of covering the roots of the molecular interpretation of human diseases and, at the same time, of instructing the students about the choice of the right technologies that can be used according to the type and the level of details required. This will be exemplified by the instructors by means of an alternation of frontal lectures and hands-on practicals.
Expected learning outcomes
The expected learning outcomes at the end of the course will primarily consist of:
a. an understanding of the physico-chemical description of molecular recognition in biosystems;
b. an understanding of the most suitable modelling techniques for describing and interpreting biophysical data at atomic and molecular level;
c. a comprehension of the most relevant features of next generation sequencing techniques and analysis;
d. the ability to understand their potentiality according to scientific and medical requirements.
Students are expected to develop the ability to critically evaluate and comprehend modern and quantitative molecular-based biotechnological information, also through a correct and well-balanced bibliographic research process.
The combination of theoretical lessons and hands-on practicals has the aim to reinforce the sensibility towards formal and practical aspects of these methodologies. Aside the technical entry-level proficiency, this will provide to the students the correct language to communicate their needs and requirements in a job environment and, consequently, the potential to create the correct network of collaborations around them according to the needs of projects in which they will be involved in during their professional life.
a. an understanding of the physico-chemical description of molecular recognition in biosystems;
b. an understanding of the most suitable modelling techniques for describing and interpreting biophysical data at atomic and molecular level;
c. a comprehension of the most relevant features of next generation sequencing techniques and analysis;
d. the ability to understand their potentiality according to scientific and medical requirements.
Students are expected to develop the ability to critically evaluate and comprehend modern and quantitative molecular-based biotechnological information, also through a correct and well-balanced bibliographic research process.
The combination of theoretical lessons and hands-on practicals has the aim to reinforce the sensibility towards formal and practical aspects of these methodologies. Aside the technical entry-level proficiency, this will provide to the students the correct language to communicate their needs and requirements in a job environment and, consequently, the potential to create the correct network of collaborations around them according to the needs of projects in which they will be involved in during their professional life.
Lesson period: Third trimester
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
Third trimester
Course syllabus
A. Computational and experimental characterization of biomolecular interactions
Molecular architectures in biotechnologies: Essentials of chemistry and physical chemistry of molecules of biological interest (protein, nucleic acids, lipids); Databases of structures and their visualization/quality check via molecular graphics (+ web practicals)
Experimental techniques I: Physical principles of the interaction of radiation and subatomic particles with matter; Experimental models for the biophysical investigation of the molecular basis of diseases; Scattering and diffraction of light, X-ray and neutrons, reflectometry of X-ray and neutrons: principles, experimental set-ups, applications; Isothermal titration calorimetry, Fourier transform infrared spectroscopy, Langmuir films, atomic force microscopy: principles, experimental set-ups, applications.
Experimental techniques II: Cryo EM, X-rays diffraction for biomacromolecules, Nuclear magnetic resonance for biomacromolecules.
Computing structures from experimental data: What does "computing" a structure mean? Monte Carlo simulations/Simulated Annealing.
Structure prediction: Homology modelling (Swissmodel + web practicals); Threading (Rosetta/RNAComposer + web practicals); Machine Learning; Conformational sampling (Monte Carlo).
Application of computational technologies to existing structures: Interacting molecules: molecular docking; Molecules in motion: molecular dynamics (+ visualization practicals).
B. Analysis of cell-based "omics" data in the context of human diseases.
Next generation sequencing technologies and applications to genomics, epigenomics, and transcriptomics, i.e. RNA-seq, ChIP-seq, ATAC-seq, whole exome sequencing, capture HiC. Multi-modal sequencing. Overview of bioinformatics methods and protocols for processing of raw sequencing data: from quality control to read alignment and peak calling. Common data structures in omics for alignment and gene annotation.
Introduction to post-processing NGS analyses, including exploratory data analysis, gene enrichment analysis, dimensionality reduction, clustering, differential analysis. Graphical representation and visualization of biological data.
Bioinformatics protocols and tools for processing and quality control of epigenomic data. Methodological aspects for characterization of protein-DNA interactions and chromatin accessibility. Motif enrichment analysis and in silico prediction of transcription factor binding sites. Integration of epigenomic datasets for chromatin state discovery. Combining multiple omics modalities.
Common bioinformatic workflows for single-cell RNA sequencing (scRNA-seq). Considerations for experimental design and analyses. Computational tools for scRNA-seq data exploration, including reconstruction of regulatory networks, identification of enhancers, inference of developmental trajectories, cell-cell communication, in silico perturbation of transcription factors, detection of genetic alterations.
Practical sessions focusing on the analysis of epigenomic and single-cell RNA sequencing datasets.
Molecular architectures in biotechnologies: Essentials of chemistry and physical chemistry of molecules of biological interest (protein, nucleic acids, lipids); Databases of structures and their visualization/quality check via molecular graphics (+ web practicals)
Experimental techniques I: Physical principles of the interaction of radiation and subatomic particles with matter; Experimental models for the biophysical investigation of the molecular basis of diseases; Scattering and diffraction of light, X-ray and neutrons, reflectometry of X-ray and neutrons: principles, experimental set-ups, applications; Isothermal titration calorimetry, Fourier transform infrared spectroscopy, Langmuir films, atomic force microscopy: principles, experimental set-ups, applications.
Experimental techniques II: Cryo EM, X-rays diffraction for biomacromolecules, Nuclear magnetic resonance for biomacromolecules.
Computing structures from experimental data: What does "computing" a structure mean? Monte Carlo simulations/Simulated Annealing.
Structure prediction: Homology modelling (Swissmodel + web practicals); Threading (Rosetta/RNAComposer + web practicals); Machine Learning; Conformational sampling (Monte Carlo).
Application of computational technologies to existing structures: Interacting molecules: molecular docking; Molecules in motion: molecular dynamics (+ visualization practicals).
B. Analysis of cell-based "omics" data in the context of human diseases.
Next generation sequencing technologies and applications to genomics, epigenomics, and transcriptomics, i.e. RNA-seq, ChIP-seq, ATAC-seq, whole exome sequencing, capture HiC. Multi-modal sequencing. Overview of bioinformatics methods and protocols for processing of raw sequencing data: from quality control to read alignment and peak calling. Common data structures in omics for alignment and gene annotation.
Introduction to post-processing NGS analyses, including exploratory data analysis, gene enrichment analysis, dimensionality reduction, clustering, differential analysis. Graphical representation and visualization of biological data.
Bioinformatics protocols and tools for processing and quality control of epigenomic data. Methodological aspects for characterization of protein-DNA interactions and chromatin accessibility. Motif enrichment analysis and in silico prediction of transcription factor binding sites. Integration of epigenomic datasets for chromatin state discovery. Combining multiple omics modalities.
Common bioinformatic workflows for single-cell RNA sequencing (scRNA-seq). Considerations for experimental design and analyses. Computational tools for scRNA-seq data exploration, including reconstruction of regulatory networks, identification of enhancers, inference of developmental trajectories, cell-cell communication, in silico perturbation of transcription factors, detection of genetic alterations.
Practical sessions focusing on the analysis of epigenomic and single-cell RNA sequencing datasets.
Prerequisites for admission
The competences acquired during Bachelor's years in Chemistry, Physics, Mathematics, Biochemistry and Molecular Biology are the only required prerequisites of the course.
Teaching methods
All the lectures will be given in the form of frontal lessons. They will be alternated with hands-on practicals.
Teaching Resources
All the teaching material will be provided, alongside lectures' slides, by the instructors.
Assessment methods and Criteria
The exam will be based on an open discussion with the course lecturers of two scientific papers (i.e., one for each module that constitutes the course) which will be provided to the students in advance with respect to the exam day.
BIO/11 - MOLECULAR BIOLOGY - University credits: 3
CHIM/02 - PHYSICAL CHEMISTRY - University credits: 2
FIS/07 - APPLIED PHYSICS - University credits: 1
CHIM/02 - PHYSICAL CHEMISTRY - University credits: 2
FIS/07 - APPLIED PHYSICS - University credits: 1
Lessons: 42 hours
Shifts:
Professor(s)