Teaching code

4S003713

Credits

12

Coordinator

Alejandro Giorgetti

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/10 - BIOCHEMISTRY

Moodle Seminars 0

The teaching is organized as follows:

Learning outcomes

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 repositories. Via group oral presentations, students will also acquire communication and self-evaluation skills.

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 networks. 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 analysis, 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 biological problems.

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

Examination Methods

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MM: Modulo 1
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In order to pass the examination, students shall demonstrate: - to understand the concept of homology and its practical implications in bioinformatics - to understand the difference between similarity and identity of biological sequences - to know how to query bioinformatics databases, in order to obtain and store relevant data and to conduct appropriate cross-searches on different databases - to know how to use algorithms for comparison of nucleotide and amino acid sequences - to know how to use software for molecular graphics and visualization - to know how to build simple interaction networks of biomolecules and simulate their time course.
Theory:
The exam consists of a written test with 5 open questions on the topics discussed in the course. Each correct question will score a maximum of 6 points. The test will last 75 minutes.
Laboratory :
The exam, which can be given on the same day of the theory part, is made of 3 exercises to be solved using the computer (each one has a maximum 10 points-score). The test will last 75 minutes.
Presentations:
At the end of January, groups of 2 or 3 students will present a database of their choice, which has been described in the January issue of Nucleic Acids Research (Database issue). A10 minute presentation (+ 3 minute for questions / discussion) shall be given, illustrating the database goals and an original test-case. Presentation will be given a score of 1 to 4, taking into account the depth of the presented subject, clarity and effectiveness of communication and mastery of the tools used.
Final score : The final score, in thirty's (/30), will be given by the average score of the theoretical and laboratory part, plus the score for the presentation.

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MM: Modulo 2
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The written exam is divided in two: a session of open questions regarding the theoretical arguments of the course: modelling, docking and gene annotation. The second phase consists in the preparation of a scientific-like article presenting the results obtained during the project development