Subject

Fundamentals of Bioinformatics

Course Title

Fundamentals of Bioinformatics
Fundamentals of Bioinformatics

Code

Business Information - 02

Study Programme

Bioinformatics

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

9 / Winter

Number of ECTS credits

Teacher

Kire Trivodaliiev, Nevena Atzkoska, Slobodan Kajaldjiski

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

The student will be able to use the already existing algorithms developed for
solving bioinformatics problems, and will also be able to develop
proprietary algorithms.

11.

Course content

In this course, the fundamentals of algorithms and their advanced variations will be studied.
Solving various problems. Special emphasis will be placed on their application in
bioinformatics problems. The structure of the course will cover: algorithms and their
complexity, greedy algorithms, dynamic programming, divide and conquer algorithms,
graph algorithms, combinatorial pattern recognition, clustering and trees,
hidden Markov models, probabilistic algorithms, global/local alignment of
pairwise sequence alignment, multiple sequence alignment, substitution matrices, searching
Sequence databases, BLAST and its variations.

12.

Learning methods

Lectures supported by slide presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, invited guest lecturers, independent preparation and defense of a project assignment and seminar paper, learning in an electronic environment (forums, consultations).

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	60 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	0 hours

16.

Other forms of activities

16.1.	Project assignments	45 hours
16.2.	Independent assignments	45 hours
16.3.	Home study	30 hours

17.

Assessment method

17.1.	Tests	15 points
17.2.	Seminar paper / project (presentation: written and oral)	45 points
17.3.	Activities and learning	15 points
17.4.	Final exam	0 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

Activities completed 15

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature 1. N. C. Jones, P. A. Pevzner \| An Introduction to Bioinformatics Algorithms \| MIT Press \| 2004 2. Andreas D. Baxevanis, B. F. Ouellette \| Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins \| Wiley \| 2010 3. A. Lesk \| Introduction to Bioinformatics \| Oxford University Press; 4th edition \| 2014
22.2.	Additional literature No. Author Title Publisher Year