PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



Inference in biological systems

01TYLPF

A.A. 2022/23

Course Language

Inglese

Degree programme(s)

Master of science-level of the Bologna process in Physics Of Complex Systems (Fisica Dei Sistemi Complessi) - Torino/Trieste/Parigi

Course structure
Teaching Hours
Lezioni 60
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Bosia Carla   Professore Associato PHYS-02/A 30 0 0 0 1
Co-lectures
Espandi

Context
SSD CFU Activities Area context
ING-INF/05 6 B - Caratterizzanti Discipline ingegneristiche
2022/23
The course provides an introduction to quantitative methods allowing to extract meaningful information from complex biological systems. These include the analysis of DNA, RNA and protein sequences, the reconstruction of phylogenetic trees, and the study of the cell inner workings via quantitative models of gene regulation, cell compartimentalization and metabolism.
Students will become acquainted with basic notions of molecular biology, probabilistic approaches to sequence alignment and inference of protein structures, and physical modeling of cell functions.
Basics of probability theory, principles of statistical physics, basic programming skills.
• Elements of molecular biology: DNA, RNA, proteins. • Inference techniques: sequence alignments, structural inference, phylogeny reconstruction. • Physical biology of the cell: gene regulation, cell compartments, vesicle trafficking, metabolism.
The course alternates lectures on theoretical topics (approximately 48 hours) and hands-on computer lab (approximately 12 hours), where the students will be invited to apply theoretical ideas and algorithms to selected problems.
• Course handouts • R. Phillips et al, Physical Biology of the Cell, Garland Science, 2012 • P. Nelson, Biological physics, Freeman, 2004 • M. Kardar and L. Mirny, Statistical Physics in biology, MIT OpenCourseWare 8.592J / HST.452J • B. Alberts et al., Molecular Biology of the Cell, Garland Science, 2015 • R. Durbin et al., Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge Un. Press, 2002 • H.C. Nguyen, R. Zecchina and J. Berg, Inverse statistical problems: from the inverse Ising problem to data science, Adv. Phys., 66 (2017) 197-261. • S. Cocco et al., Inverse statistical physics of protein sequences: a key issues review, Rep. Progr. Phys. 81 (2018) 032601. • J. Felsenstein, Inferring phylogenies, Sinauer Associates, 2004 • Suggested scientific publications
Exam: Compulsory oral exam;
The oral test will consist of the in-depth presentation of a scientific work chosen by the Student among those discussed in the course and uploaded in the 'Material' section of the course site (or among other works otherwise related to the topics of the course), and of 2-3 broad questions on the main topics of the lectures. The grading of the presentation will contribute to 1/3 of the overall assessment (the maximum grade being 30L). The purpose of the exam will be to verify the Student's understanding of basic notions of molecular biology, probabilistic approaches to sequence alignment and inference of protein structures, and physical approaches to the modeling of cell functions.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
Esporta Word