Bioinformatics 1

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Bioinformatics 1

Course Description

In the last two decades, bioinformatics has expanded rapidly as the discipline that narrowly connects biology with computer science. The accelerating growth of biological data collection has inspired development of new computational methods for storage, retrieval, analysis and visualization of such data. This course will focus on the computational aspects of biological sequence analysis. Lectures will cover algorithms and tools developed for pairwise and multiple sequence alignment, genome and transcriptome assembly, gene finding and phylogenetic tree reconstruction.

Learning Outcomes

Explain some of the issues and challenges in contemporary bioinformatics
Evaluate bioinformatics algortihms
Design algorithms solving sequence assembly problems
Compare and evalute methods for sequence alignment
Design algorithms for building phylogenetics trees
Analyze data from biological databases
Design index structures based on suffix trees and suffix arrays

Forms of Teaching

Lectures

Lectures in the classroom

Independent assignments

Team work on the implementation of a method.

Grading Method

	Continuous Assessment		Exam
Type	Threshold	Percent of Grade	Threshold	Percent of Grade
Seminar/Project	0 %	40 %	0 %	40 %
Mid Term Exam: Written	40 %	25 %	0 %
Final Exam: Written	40 %	35 %
Exam: Written			40 %	60 %

Week by Week Schedule

Protein, RNA and DNA, Bioinformatics databases, Data formats
Biological sequences and structures, Dynamic programming algorithms, Project
Dynamic programming algorithms, Project
Suffix trees, Project
Suffix trees, Project
Suffix arrays, Project
Suffix arrays, FM index, Project
Midterm exam
Multiple sequence alignment, Database search, Basic Local Alignment Search Tool (BLAST) algorithm
Alignment, Substitution model, Project
Tree building, Tree evaluation, Project
Sequencing methods, Read mapping, Project
De novo assembly, Overlap-Layout-Consensus, Project
String graph, De Bruijn graph, Project
Final exam

Study Programmes

University undergraduate

[FER3-HR] Computing - study

Elective Courses (6. semester)

[FER3-HR] Electrical Engineering and Information Technology - study

Elective Courses (6. semester)