Systems Biology and Network Analysis
A.Y. 2024/2025
Learning objectives
Systems biology is the study of interrelationships between molecular constituents of a living cell through the integration of experimental and computational approaches. Most biological characteristics arise from complex interactions between the cell's functional elements; to understand how genes determine phe¬notypes, both in physiology and disease, it is necessary to adopt quantitative methods that allows a holistic approach. The course describes the principles useful to explore interactions by introducing methods for the analysis of gene-regulatory and large-scale networks exploiting availability of big functional genomics data sets. Analysis and modelling of genetic and epigenetic determinants of gene expression regulation will be considered.
Expected learning outcomes
At the end of the course, students will be able to apply systems biology techniques and pipelines to the analysis and characterization of regulatory (genetic and epigenetic) and interaction networks.
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
Lesson period
First semester
Course syllabus
Biological networks and basic concepts of graphs.
Hill function. Negative and positive autoregulation.
Network motifs: feed-forward loop, single input modules and dense overlapping regulons (DORs). Positive and negative feedback loops. Oscillators.
Modelling of circadian rhythms in cellular networks.
Annotation and pathway analysis (over-representation, functional class scoring, topology based).
Network analytics. Scale-free nature of cellular networks. Biological small worlds.
Dependencies estimation in co-expression networks (WGCNA).
Network modularity.
Network rewiring and comparative genomics to study gene essentiality.
Identification of DNA sequence alterations: statistical genetics for linkage analysis and genome wide association studies (GWASs). Linkage disequilibrium. Expression quantitative trait loci (eQTLs).
Hill function. Negative and positive autoregulation.
Network motifs: feed-forward loop, single input modules and dense overlapping regulons (DORs). Positive and negative feedback loops. Oscillators.
Modelling of circadian rhythms in cellular networks.
Annotation and pathway analysis (over-representation, functional class scoring, topology based).
Network analytics. Scale-free nature of cellular networks. Biological small worlds.
Dependencies estimation in co-expression networks (WGCNA).
Network modularity.
Network rewiring and comparative genomics to study gene essentiality.
Identification of DNA sequence alterations: statistical genetics for linkage analysis and genome wide association studies (GWASs). Linkage disequilibrium. Expression quantitative trait loci (eQTLs).
Prerequisites for admission
The course Bioinformatics and Computational Biology must be successfully completed to take the exam of this class.
Teaching methods
The course consists of 24 hours of theoretical lectures and 24 hours of practical lessons in Matlab environment.
Teaching Resources
The slides presented during the course along with additional material recommended for specific topics will be available on the Webeep portal (https://webeep.polimi.it/login/index.php), accessible to students registered to the course.
Assessment methods and Criteria
The assessment is based on an oral exam concerning a preliminary exercise (writing of a Matlab script) and general questions about the topics covered during the course along with the discussion of an assignment developed during the semester.
ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING - University credits: 6
Lectures: 48 hours
Professor:
Pattini Linda