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Algoritmi per la bioinformatica
Codice: | 315AA | Crediti: | 6 | Semestre: | 2 | Sigla: | ABI | |
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Settore disciplinare: | INF/01 - Informatica |
Docente
Ultima versione disponibile: programma da confermare per l’a.a. 2014/2015
Prerequisiti
Knowledge requirements:
A basic course on algorithmic.
Obiettivi di apprendimento
Learning goals:
This course has the goal to give the student an overview of algorithmic
methods that have been conceived for the analysis of genomic sequences,
and to be able to critically observe the practical impact of algorithmic
design on real problems with relevant applications.
The exam (see below for its description) has the goal to evaluate the
students understanding of the problems and the methods described in the
course. Moreover, the exam is additionally meant as a chance to learn
how a scientific paper is like, and how to make an oral presentation on
scientific/technical topics, that is designed for a specific audience.
Conoscenze.
Descrizione
Since 2012 this Master Program is no longer in italian.
English Description
Description of the course:
The course focuses both on theoretical and combinatorial aspects of
algorithmical problems that raise from applications in molecular
biology, as well as on practical issues such as whole
genomes sequencing and the consequent assembly task, sequences alignments, the inference of repeated
patterns and of long approximated repetitions, and several biologically
relevant problems for the management and investigation of genomic data.
Programma
Contents:
A brief introduction to molecular biology: DNA, proteins, the cell, the
synthesis of a protein.
Motifs Extraction: KMR Algorithm for the extracion of exact motifs and
its modifications for the inference of approximate motifs.
Finding Repetitions: Algorithms for the inference of long approximate
repetitions. Filters for preprocessing.
Sequences Alignments: Dynamic Programming methods for local, global, and
semi-local alignments. Computing the Longest Common Subsequences.
Multiple Alignments.
Fragment Assembly: Genomes sequencing: some history, scientific
opportunities, and practical problems. Some possible approaches for the
problem of assembling sequenced fragments. Link with the “Shortest
common superstring” problem, the greedy solution. Data structures for
representing and searching sequencing data.
New Generation Sequencing: Applications of High Throughput Sequencing
and its algorithmic problems and challenges. Investigating data types
resulting from the existing biotechnologies, and the possible data
structures and algorithms for their storage and analysis.
Bibliografia
References:
- JEWELS OF STRINGOLOGY, M.Crochemore and W.Rytter, World Scientific, 2002.
- INTRODUCTION TO COMPUTATIONAL MOLECULAR BIOLOGY, J.Setubal and J.Meidanis, PWS, 1997.
- More course material given by the lecturer.