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Computational Genomics (course held in English)

Code: 172476
ECTS: 6.0
Lecturers in charge: prof. dr. sc. Kristian Vlahoviček
izv. prof. dr. sc. Rosa Karlić
Take exam: Studomat
Load:

1. komponenta

Lecture typeTotal
Lectures 30
Practicum 30
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
COURSE CONTENT:
LECTURES
1. - 2. Introduction to computational genomics. The history of genome sequencing. Sequencing the human genome. Definition of genes.
3. - 4. Next generation sequencing methods. Roche 454 pyrosequencing, Illumina GAII, Illumina Hiseq, ABI Solid, Helicos, Pacific bioscience. Advantages and disadvantages of different sequencing methods
5. - 6. De novo genome assembly methods. Greedy algorithms, overlap layout consensus methods, de Bruijn graphs.
7. - 8. Methods of mapping short fragments (reads) obtained by next-generation sequencing to previously assembled genomes.
9. - 10. Methods for transcriptome analysis based on next generation sequencing (RNA-Seq).
11. - 12. Methods for the analysis of protein and DNA interactions (chromatin immunoprecipitation combined with next generation sequencing, ChIP-Seq).
13. - 14. Determination of the three-dimensional structure of the genome (3C, 4C, 5C and Hi-C methods).
15. Repetition of the adopted material and review of selected recent scientific discoveries based on next generation sequencing methods.

PRACTICAL
1. Introduction to using tools for searching genomic data (UCSC Genome Browser).
2. Introduction to Bioconductor, a repository of software packages for the analysis of biological data in the R statistical environment.
3. Manipulation and analysis of strings using the Biostrings package.
4. Searching for patterns in strings.
5. - 6. Operations on intervals. IRanges and GenomicRanges packages.
7. - 8. Retrieve annotations from the UCSC and Ensembl databases. GenomicFeatures package.
9. - 10. Loading and analysis of short fragments obtained by next generation sequencing methods. ShortRead and RSamtools packages.
11. Filtering and quality control of data obtained by next-generation sequencing methods.
12. Normalization of data obtained by next generation sequencing methods.
13. Analysis of differentially expressed genes. DESeq, EdgeR and DEXSeq packages.
14. Analysis of overrepresentation of gene sets and Gene Ontology terms.
15. ChIP-Seq data analysis methods. Determination of protein binding sites on DNA.
Literature:
3. semester
Izborni predmeti - Računalna biologija - Regular study - Molecular Biology
Consultations schedule: