Teaching code

4S003713

Credits

12

Coordinator

Alejandro Giorgetti

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/10 - BIOCHEMISTRY

Courses Single

Authorized

Moodle Seminars 0

The teaching is organized as follows:

Learning objectives

The course will provide the theoretical and practical basis to understand and employ algorithms and programs currently used to retrieve and analyze data contained in the most used biological data re-positories. The course is divided into two modules, as detailed below. Module 1: In this module student will become acquainted with some of the most used software tools for managing data in proteomics, genomics, biochemistry, molecular and structural biology. Students will be introduced to the analysis and the visualization of structural data of biological macromolecules and their complexes, and to the design of simple static and dynamic models of biomolecular net-works. The students will also be introduced to the most modern fields of systems biology. Module 2: In this module students will learn how to employ the basic bioinformatic tools for the ana-lysis, interpretation and prediction of biological data in proteomics, genomics, biochemistry, molecular biology. This course offers the possibility of applying state of the art bioinformatic tools to solve biolo-gical problems

Prerequisites and basic notions

There are no prerequisites

Program

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MM: Modulo 1
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Theoretical Module
- Overview of the main structural features of proteins and nucleic acids in relation to the concept of evolution. Introduction to biomolecular databases: online resources and their use
- Biological databases: organization and integration of information concerning: a) protein and nucleic acid sequences; b) biomolecular structures; c) bibliographic and scientific literature. Retrieve of specific information: use of limitations and Boolean operators.
- Sequence comparison and alignments: static and dynamic algorithms; substitution matrices (PAM,BLOSUM) - Search-algorithms: dynamic algorithms; Smith-Waterman; Needleman-Wunsch; statistic significance for an alignment (z-score, expectation values and probability); heuristic methods for local alignments; BLAST
- Multiple sequence alignments: ClustalW, search on specific databases, other algorithms, PSI-BLAST
- Introduction to Structural Bioinformatics: visualization and analysis of protein and nucleic acid 3D structures
- Methods to predict protein secondary structure elements starting from the sequence; introduction to neural networks. NN-based methods - Introduction to Systems Biology: Spatial and temporal scales, static and dynamic models, mathematical frameworks, introduction on signal transduction networks Laboratory Module
- NCBI databases: Entrez interface, Gene, UniGene, Protein, Uniprot and EBI
- Single and multiple sequence alignments, score matrices, optimal methods; online resources and spreadsheets - BLAST,PSI-BLAST and BLAT: online tools and their use
- Tools for multiple alignments, the Homologene databank, computation and visualization of multiple alignments - Introduction to PyMol and molecular visualization. Use of PSI-PRED and JPRED for predicting secondary structures from sequences - Systems biology: numerical simulation of simple biochemical reactions. Building simple kinetic models by using SBOTOOLBOX2 for Matlab; application to G-potein signalling cycles.
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MM: Modulo 2
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Bioinformatic tools for the analysis of molecular evolution and phylogenesis: Molecular clock, substitution models, methods for the construction of phylogenetic trees.
Protein structural predictions: Comparative modeling, Fold recognition and ab initio methods.
Gene prediction Functional annotation Microarrays: databases and programs for the analysis of expression data. Introduction to the energetic treatment of proteins: MD simulations, ligand-protein and protein-protein docking.
The teaching includes: front lectures and hands-on laboratories on the PC. The students are also involved in a project to be developed in groups.

Bibliography

Didactic methods

The course consists of frontal theory lessons, analysis and presentation of relevant scientific articles in the field of bioinformatics and laboratory lessons

Learning assessment procedures

------------------------ MM: Module 1 ---------------------- - Theory -------- The exam consists of a written test with 5 open questions on the topics covered in the course, each with a maximum score of 6 points. The paper has a duration of 75 minutes. The vote will be out of thirty. Laboratory ----------------- The exam, which can be taken on the same day as the theory paper, contains 3 exercises to be solved using the computer (each with a maximum of 10 points). The paper has a duration of 75 minutes. The vote will be out of thirty. Presentations -------------------- At the end of January the students present, in groups of 2 or 3 members, a database of their choice contained in the January issue of the journal Nucleic Acids Research (Database issue). They will have to illustrate, through a presentation of 10 minutes + 3 minutes for questions / discussions, the purpose of the database and an original application. They will obtain a score from 1 to 4, which will take into account the deepening of the topic, the clarity of presentation, the effectiveness of communication and mastery of the tools used. Final grade --------------- The final grade, out of thirty, will be obtained by adding the average between the grade of the theory test and the laboratory grade to the grade obtained in the presentation. ------------------------ MM: Module 2 ---------------------- - The exam is written and consists of an oral session of open questions on the topics covered in the course. In particular modeling, docking and gene annotation theories are required. The second phase consists in the drafting of a scientific handwritten document with the results obtained in the realization of the project assigned in class.

Evaluation criteria

To pass the exam, the student must demonstrate: - to have understood the concept of homology and its practical implications in the bioinformatics field - to have understood the difference between similarity and identity between biological sequences - to be able to query databases of bioinformatics interest, to obtain and store the related data, carrying out appropriate cross-searches on different databases in order to carry out specific searches - knowing how to use algorithms for the comparison of nucleotide and amino acid sequences - knowing how to use software for molecular graphics and visualization - knowing how to build simple interaction networks between biomolecules and simulate the time course. Knowing how to use the specific language of bioinformatics Understanding critically in a scientific article in the field of applied bioinformatics
Building three-dimensional models of proteins
Using molecular docking techniques and understanding the underlying theory

Criteria for the composition of the final grade

The grade of module I consists of a presentation of scientific articles in groups and a written exam during the exam session. The form II grade has the same structure. The total grade is the arithmetic average of the grades of the two modules

Exam language

Italiano