Computational biology of genome projects: Sequencing strategies and algorithms for sequence assembly; genome annotation and gene ontology. Visualization of genome content. Hypothesis generation from genomics data.
Genome browsers. UCSC Genome Browser and Ensembl Genome Browser. Locating genes, functional elements and annotations.
Structure and composition of genomes. Genomes of Bacteria and Archaea. Genomes of eukaryotes and the C-value paradox. Human genome, genome variation and genetic diseases.
Introduction to computational methods in biology. Basic data types and algorithms (sorting, searching, string algorithms). Comparison of two or more biological sequences (dynamic programming algorithms). Phylogenetic reconstruction. Algorithms applicable to genome-wide analyses.
Detection and discovery of functional elements in genomes: Use of comparative genomics for functional element detection. Predictive models for detection of regulatory elements and modules in genomes. Fundamental principles of design and validation of predictive models in computational biology.
Gene finding: An applied introduction to machine learning methods (Hidden Markov Models, Neural Networks, Support Vector Machines)
Expression profiles and microarrays: Statistical approaches to analysis of large data sets and hypothesis generation. Rational design of microarray experiments.
Networks and systems biology: The concept of networks: grapg representation, structure and properties. Scale-free networks. Construction and analysis of interactome and transcriptional regulatory networks. Network dynamics. Metabolic networks.
A lecture (delivered by instructor) on the topic chosen by students. Final exam. Course evaluations.
Learning outcomes:
Name and describe commonly used databases in the field of bioinformatics.
Find the sequence for the protein of interest and all related information.
Find the homologues of desired protein and evaluate the reliability of the search results.
Align the sequences of homologous proteins, analyze the quality and reliability of the alignment and construct the phylogenetic tree.
Describe the next generation DNA sequencing methods, and compare them to each other and to Sanger method of DNA sequencing.
List and explain the strategies used in the sequencing and assembly of compact microbial genomes and complex eukaryotic genomes
Describe the procedures used in genome annotation.
Compare the gene expression analysis by DNA microarrays and next generation sequencing
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