Politecnico di Torino
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Politecnico di Torino
Academic Year 2015/16
01OVFOV, 01OVFOQ, 01OVFOT, 01OVFPE
Bioinformatics
Master of science-level of the Bologna process in Computer Engineering - Torino
Master of science-level of the Bologna process in Electronic Engineering - Torino
Master of science-level of the Bologna process in Telecommunications Engineering - Torino
Espandi...
Teacher Status SSD Les Ex Lab Years teaching
Ficarra Elisa ORARIO RICEVIMENTO A2 ING-INF/05 30 0 30 5
SSD CFU Activities Area context
ING-INF/05 6 D - A scelta dello studente A scelta dello studente
Esclusioni:
01OVA; 01OUW; 01OVD; 01OVC; 01OVE; 01OUX; 01OUZ; 01OUY; 01OVB
ORA-01722: invalid number
Subject fundamentals
Hardware/Software solutions will be studied for the analysis of genetic data provided by the latest generation biotechnologies (e.g. DNA/RNA next generation sequencers, nanotechnology, etc..). During the course, it will be described the state of the art of such technologies, and it will be deeply studied computational and algorithmic issues for the development of tool-flows for complex genetic analyses (such as genetic mutations and aberrations). It will be presented also techniques for genetic data distributed computing. During the course, the basic concepts of the molecular biology will be introduced, and the programming language Python will be presented (even if every programming language will be allowed in the final project development). The purpose of the course is therefore to provide training in order to make students experts of the biomolecular/genetic issues, technologies and processing techniques the most advanced in the field of biotechnology and genetic analysis.
Expected learning outcomes
The student should acquire i) the knowledge of the latest generation biotechnologies for genetic and molecular screening, ii) the knowledge of some the most up-to-date genetic issues in the personalised medicine approach, iii) the knowledge of the main SW solutions for complex bioinformatics analyses, iv) the ability to design and implement effective and computationally efficient algorithmic solutions for biological problems, vi) the experience on SW optimization techniques on cluster infrastructures.
Prerequisites / Assumed knowledge
High level language computer programming (eg C, C + + or Java), scripting languages.
Contents
- Introduction to the Bioinformatics: Concepts of Molecular Biology, Computational, technological and efficacy requirements of the algorithms, Relevant problems in research, industry and businesses
- DNA-, microRNA- and RNA-sequencing: Description of sequencing technologies, algorithmic and computational issues, main tools used for sequencing and data analysis, issues related to software development for advanced analyses (e.g. mutations and gene fusions detection, microRNA and long RNA non coding identification and expression, etc.), SW optimization on parallel and distributed infrastructures.
- Bioinformatics techniques for gene expression analysis: Description of the key technologies (eg microarrays, real-time PCR, RNA-Seq, etc..), SW methodologies for expression analysis and description of main tools, biostatistics.
- Bioinformatics techniques for the study and the prediction of regulatory processes: SW techniques for the prediction of miRNA targets, Derivation of regulatory networks.