Bioinformatics 1

Learning Outcomes

  1. Explain some of the issues and challenges in contemporary bioinformatics
  2. Evaluate bioinformatics algortihms
  3. Design algorithms solving sequence assembly problems
  4. Compare and evalute methods for sequence alignment
  5. Design algorithms for building phylogenetics trees
  6. Analyze data from biological databases
  7. 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

  1. Protein, RNA and DNA; Bioinformatics databases; Data formats.
  2. Biological sequences and structures; Dynamic programming algorithms; Project.
  3. Dynamic programming algorithms; Project.
  4. Suffix trees; Project.
  5. Suffix trees; Project.
  6. Suffix arrays; Project.
  7. Suffix arrays; FM index; Project.
  8. Midterm exam.
  9. Multiple sequence alignment; Database search; Basic Local Alignment Search Tool (BLAST) algorithm.
  10. Alignment; Substitution model; Project.
  11. Tree building; Tree evaluation; Project.
  12. Sequencing methods; Read mapping; Project.
  13. De novo assembly; Overlap-Layout-Consensus; Project.
  14. String graph; De Bruijn graph; Project.
  15. Final exam.

Study Programmes

University undergraduate
Computing (study)
Elective Courses (6. semester)
Electrical Engineering and Information Technology (study)
Elective Courses (6. semester)
University graduate
Audio Technologies and Electroacoustics (profile)
Elective Courses (2. semester)
Computational Modelling in Engineering (profile)
Elective Courses (2. semester)
Computer Engineering (profile)
Elective Courses (2. semester) Specialization Course (2. semester)
Control Systems and Robotics (profile)
Elective Courses (2. semester)
Data Science (profile)
Elective Courses (2. semester)
Electrical Power Engineering (profile)
Elective course (2. semester)
Electric Machines, Drives and Automation (profile)
Elective Courses (2. semester)
Electronic and Computer Engineering (profile)
Elective Courses (2. semester)
Electronics (profile)
Elective Courses (2. semester)
Information and Communication Engineering (profile)
Elective courses (2. semester)
Information Processing (profile)
Specialization Course (2. semester)
Software Engineering and Information Systems (profile)
Elective Courses (2. semester) Specialization Course (2. semester)

Literature

(.), Mile Sikic, Mirjana Domazet-Loso, Skripta iz bioinformatike,
(.), N.C. Jones, P. J. Pevzner, An Introduction to Bioinformatics Algorithms,
(.), D. Gusfield, Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology,

Lecturers

Prof.
Mile Šikić
Assoc. Prof.
Mirjana Domazet-Lošo

Associate Lecturers

Asst. Prof.
Krešimir Križanović

For students

General

ID 183492
  Summer semester
5 ECTS
L1 English Level
L1 e-Learning
30 Lectures
0 Exercises
5 Laboratory exercises
0 Project laboratory

Grading System

90 Excellent
75 Very Good
60 Good
50 Acceptable

Similar Courses