Topics Discussed in the Courses
Cell Signaling and Metabolism
Monday, 4th September & Tuesday, 5th September
Cell signaling I
- From extracellular signal to cellular response.
- Studying cell surface receptors and signal transduction pathways.
- G protein-coupled receptors.
From genes to protein
- Transcriptional control of gene expression.
- Post-transcriptional gene control.
Cell signaling II
- The cytoskeleton: cell structure and movement.
- Metabolism
Tools for Modeling Biological Systems: a “hands-on” course
Monday, 4th September & Tuesday, 5th September
Mathematical models of intra-cellular processes
- Quantitative mathematical descriptions of coupled reactions by ordinary differential equations (ODEs)
- Michaelis Menten kinetics, Hill kinetics, stochastic terms and other common variations of ODEs used in the literature
Computational modeling of Biological systems
- Introduction to computational modeling and coding in MatLab.
- Practical examples of modeling intra-cellular processes
Mathematical models of extra-cellular processes
- Quantitative mathematical descriptions of diffusion and chemotaxis through partial differential equations (PDEs)
- Computational implementation
Data Science - application to Biology
Monday, 4th September
Basic Concepts of Machine-learning (ML)
Unsupervised learning
- Clustering (k-means and hierarchical)
- Dimensionality reduction (Principal Component Analysis)
Supervised Learning/ Classification
- Generative vs discriminative models
- Model validation (bias variance trade-off and learning curves)
- Classifiers (Naive Bayes, KNN, Linear SVM)
Ensemble methods (Boosting, Bagging, and Random Forests)
Application of ML to genomics and proteomics
Modeling Proteins and Membranes: folding and aggregation
Wednesday, 6th September & Thursday, 7th September
- Foundations of molecular dynamics
- Molecular dynamics for lipid bilayers
- Molecular dynamics for proteins
- Studying protein folding and aggregation
- Protein-Ligand interactions and Drug Discovery
Transcriptomics to Characterize Cellular Mechanisms
Wednesday, 6th September & Thursday, 7th September
- Next-generation sequencing technologies (NGS)
- RNA, transcriptomes and RNA
- Experimental design for RNA-Seq
- RNA-Seq data processing
- RNA-Seq data analysis methods
- Differential expression and functional analysis
- Analysis of time-series data
- Reconstruction of signaling networks
Modeling Metabolic and Signaling Pathways
Thursday, 7th September & Friday, 8th September
- Graphical representation of regulatory networks
- From diagrams to equations
- Relating concentrations to process rates
- Handling compartments
- Studying steady state behavior
- Simulating dynamics
- Taming complexity
- The dynamic bestiary
Mathematical Models of Age-Related Diseases
Friday, 8th September
Modeling physiological systems using continuous and discrete methods.
Exemplification of the methods by analysing tumor growth, blood vessel formation and vessel irrigation in pathological settings.
- Angiogenesis and tumor growth using cell based models.
- Coupling cell signalling to matrix elasticity to regulate vessel morphology.
- Quantifying blood flow and hypoxia in pathological vascular network.
- Models of drug release in the context of glaucoma.
