Algorithms and programming languages for bioinformatics - LINGUAGGI PER BIOINFORMATICA (2013/2014)

Course not running

Course code
4S000525
Credits
6
Academic sector
INF/01 - INFORMATICS
Language of instruction
English
Location
VERONA
Teaching is organised as follows:
Activity Credits Period Academic staff Timetable
teoria 4 I semestre Alberto Castellini
laboratorio 2 I semestre Alberto Castellini

Lesson timetable

Learning outcomes

The aim of this course is to provide formalisms and languages for dealing with some typical problems in bioinformatics, such as the analysis of biological data, the representation of biological systems by suitable models and the simulation of such systems. The analysis of some case studies and laboratory classes will enable to understand how methodologies presented during the course can be used in practice.

Syllabus

OUTLINES OF JAVA PROGRAMMING LANGUAGE AND BIOJAVA

Main elements of the Java programming language. Object oriented programming. Polymorphism and inheritance. Overloading. Abstract classes and methods. Interfaces. Main classes, interfaces and data structures available in Java. Main classes provided by the BioJava library for the implementation of bioapplications (alphabets, symbols, symbol lists, sequences). Basic operations on sequences (transcription, complement, reverse, translation). Input/output of sequences from files (main bioinformatic formats, e.g., Fasta, GenBank,…). Classes for the representation of sequence annotations.

MATLAB AND MATLAB BIOINFORMATICS TOOLBOX

Outlines of Matlab programming language main elements. Variables. Matrices and arrays. Operators. Cell arrays. Characters and text variables. Structures. Charts and graphics. Scripts and functions. Flow control and loops. Data analysis. Introduction to Bioinformatics toolbox: data formats and functions for connecting to bioinformatics databases; functions and tools for sequence analysis.

PYTHON E BIOPYTHON

The Python interpreter. Main elements of the Python programming language. Numbers, strings, lists, tuples, sequences, dictionaries. Loops, functions, scripts, modules, input/output. Classes. Errors and exceptions (hints). Main features of Biopython. Sequences and alphabets. Sequence objects: nucleotide frequencies, concatenation, complement, transcription, translation. MutableSeq, UnknownSeq and SeqRecord objects.

OTHER APPLICATIONS FOR STATISTICAL DATA ANALYSIS

Brief introduction to some of the main software for statistical analysis: Excel/Calc, R, SAS JMP, SPSS. Main functionalities and application fields.

Assessment methods and criteria

The exam consists of a project and an oral test. The project concerns the study of an advanced topic or the implementation of a technique explained during the course. The oral test concerns the topics presented during the course.

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