First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Medicine
MEDICAL BIOTECHNOLOGIES
Course unit
PROTEOMICS AND BIOINFORMATICS
MEO2045677, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
MEDICAL BIOTECHNOLOGIES
ME1934, Degree course structure A.Y. 2012/13, A.Y. 2017/18
N0
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Degree course track MEDICAL BIOTECHNOLOGIES [002PD]
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination PROTEOMICS AND BIOINFORMATICS
Website of the academic structure https://www.medicinamolecolare.unipd.it
Department of reference Department of Molecular Medicine
E-Learning website https://elearning.unipd.it/medicinamolecolare/course/view.php?idnumber=2017-ME1934-002PD-2017-MEO2045677-N0
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit CANNOT be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in MEDICAL BIOTECHNOLOGIES

Lecturers
Teacher in charge STEFANO TOPPO BIO/10

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
MEO2045677 PROTEOMICS AND BIOINFORMATICS STEFANO TOPPO ME1934

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses BIO/10 Biochemistry 6.0

Mode of delivery (when and how)
Period First semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 02/10/2017
End of activities 19/01/2018

Examination board
Examination board not defined

Syllabus
Prerequisites: Good knowledge of spoken and written English is required
Target skills and knowledge: The course aims to provide students with basic concepts of structure and function of proteins, Mass Spectrometry in proteomics, and bioinformatics in the field of protein alignments and structure prediction
Examination methods: The examination is typically 1 hour and a half in length and closed book in format. The test is with open-ended questions on the entire contents of the course. Also planned seminar activity and evaluation
Assessment criteria: The objective is to assess students’ ability to engage critically with the material covered on the course and provide personal interpretation
Course unit contents: BIOCHEMICAL CONCEPTS

1) Basic concepts on general properties of amino acids, secondary structures, protein domains, and common folds
2) Interactions forces in proteins from quantum chemistry to molecular mechanics and dynamics
3) Introduction to force fields in molecular mechanics and the different interaction forces bonded and non-bonded.
4) Protein folding from Anfisen to modern theories: hydrophobic collapse, diffusion and collision, funnel theories and the Levinthal’s paradox. Lattice simulations in a Hydrophobic Polar model
5) Protein folding in the cell: Folding Accessory proteins and mechanism in Eukaryotes and Prokaryotes: PDI, GroEL/GroES, Heat Shock Proteins. Brief introduction to ER stress and protein misfolding, amyloid formation


MASS SPECTROMETRY IN PROTEOMICS

1) Mass spectrometry MS: the basic principles of proteomics techniques up to mass spectrometry present era
2) Description of MS instrumentations
a. ESI and MALDI sources
b. Mass Analyzers: Quadrupole, stability diagram, Mathieu equations
c. 3D and linear Ion Trap: stability diagram and working process as ion ejections and fragmentation
d. Time Of Flight and equations of ion trajectories
e. Orbitrap basic principles
3) Mass Spectrum interpretation: m/z ion detection, isotope distribution, mass accuracy, resolution, Deconvolution and charge state determination
4) Fragmentation rules and ion series
5) MS fingerprinting and MS/MS data identification analysis
6) Interpreting a MS/MS spectrum: algorithms techniques implemented in Mascot and Sequest, PeptideProphet
7) Parametric and non-parametric methods, FDR, decoy sets, spectral clustering
8) Mass spectrometry quantification techniques: label free, tag-based techniques
9) Signal processing, statistical analysis, normalization, Clustering and classification, Gene Set Enrichment Analysis (GSEA), Hypergeometric testing, Statistical experiment design


BIOINFORMATICS

1) Sequence alignments algorithms: motivation
2) Brief introductions to issues and unsolved questions from phylogenetic analysis to protein structure and function. Structural evolutionary models, folds and protein disorders
3) Dot Plot analysis, repeat and inverse repeats
4) Sequence alignment scores: random vs. match model to calculate the alignment score
5) Scoring matrices: PAM and BLOSUM
6) Local (Smith and Waterman), global (Needleman-Wunsch), freeshift algorithms
7) K-tuple algorithms: BLAST and FASTA for database searches, introduction to raw score, bitscore, e-value, detailed FASTA, BLAST algorithms steps
8) Confusion matrices, ROC curves
9) Multiple alignments: progressive and iterative strategies. The operation of CLUSTAL , introduction of molecular phylogeny concepts, neighbor joining
10) Patterns and Profiles
11) Structural modeling from Comparative modeling to Fold recognition techniques
12) Gene Ontology and protein function prediction
Planned learning activities and teaching methods: lectures and learning by example
Additional notes about suggested reading: material provided in class. Slides of the lectures
Textbooks (and optional supplementary readings)