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Semester (Sem)
1First Semester
2Second Semester
AAnnual course
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Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Context
Academic Year 2016/2017
School School of Industrial and Information Engineering
Name (Master of Science degree)(ord. 270) - MI (481) Computer Science and Engineering
Track T2A - COMPUTER SCIENCE AND ENGINEERING
Programme Year 2

Course Details
ID Code 050706
Course Title GENOMIC COMPUTING
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 5.0
Semester --
Course Description An introduction to Genomic Computing, i.e. the application of computer science and mathematics to genomics. Intended for first-year PhD students who will focus their research on biological problems, as well as for students who wish to broaden their culture. This course provides an introduction to Genomic Computing, i.e. the application of computer engineering and mathematics to genomics, with an emphasis on concrete technologies and hands-on practice. It is intended for first-year PhD students, who will focus their research on bioinformatics, but it can be followed by PhD students and researchers of DEIB, MAT and other departments who wish to broaden their culture. The course will start by familiarizing students on the foundational molecular biology concepts (encoding of information in the DNA sequences and its functional use at the genomic, epigenomic, transcriptomic and proteomic levels), as well as on the DNA/RNA sequencing techniques (including the novel Next Generation Sequencing - NGS). Then, current sequencing data standards and tools for their (pre)processing and visualization will be presented, with emphasis on info-math issues related to their management and analysis. The last part of the course will be devoted to the (epi)genomic analysis of multiple heterogeneous NGS data using different instruments, including the recently developed GenoMetric Query Language - GMQL (http://www.bioinformatics.deib.polimi.it/GMQL/) for the analysis of NGS big data. Approaches for knowledge extraction from processed NGS data will be also presented. Subjects: - Foundations of biology, with emphasis on defining info-math problems - DNA Next Generation Sequencing (NGS) and tools for DNA and NGS data visualization and browsing - Current bioinformatics data management technology and standards - NGS data processing and analysis - New approaches for Genomic Computing challenges

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--AZZZZMasseroli Marco
manifesti v. 3.4.3 / 3.4.3
Area Servizi ICT
22/10/2020