Systems and “In Silico” Biology.  Pier Luigi Martelli

Course aims: Presenting advanced tools for large scale data analysis and their applications to Systems Biology. At the end of the course, students will be able to: -adopt Principal Component Analysis, Correspondence Analysis and clustering methods for data analysis; -work with Support Vector Machines and Kernel methods -model the structure of complex biological systems with the network theory; -model the dynamics of a biological system with differential equations; - model and design simple gene circuits.

Course contents: Advanced methods for unsupervised and supervised data analysis: i)Methods for qualitative data analysis: Principal Component Analysis, Correspondence Analysis; ii) Clustering methods; iii) Support Vector Machines; iv) Kernel methods.
Introduction to Systems Biology: i) Complexity in Biological Systems; ii) Integration of data from Genomics, Proteomics, Interactomics, Transcriptomics, Metabolomics, Physiomics; iii) Modelling the structure of complex biological systems: Network theory; iv) Modelling the dynamics of complex biological systems: Differential equations, Process Algebra.
The prokaryotic transcription network as a model system: i) Basics on transcription networks; ii)Dynamics and response time of simple gene circuits; iii) Extraction and analysis of significant motifs: the autoregulation motif, the feed-forward loop motif.

Readings/Bibliography: on line, selected papers and books.
Bishop C (2006) Pattern recognition and Machine Learning. Springer [ISBN 0-38-731073-8]
Klipp, E., Herwig, R., Kowald, A., Wierling, C. and Lehrach, H. 2005. Systems Biology in Practice: Concepts, Implementation and Application. Wiley-VCH [ISBN 3-527-31078-9]
Aron U. 2006. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/CRC . [ISBN-13: 9781584886426]

Teaching methods: Lectures,  seminars.

Assessment methods: The test of assessment will be written based on a series of questions to test the knowledge of the student, followed by an oral section.

Teaching tools: Video beam, PC, overhead projector, laboratory activity