Introduction in Bioinformatic of the Centromere of Human Genome

Introduction in Bioinformatic of the Centromere of Human Genome

Code: 63067
ECTS: 7.0
Lecturers in charge: doc. dr. sc. Matko Glunčić - Lectures
Lecturers: Matko Glunčić - Exercises
Take exam: Studomat
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1. komponenta

Lecture typeTotal
Lectures 30
Exercises 15
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
COURSE GOALS: The course goal is to introduce students to ways of computer identification of repeats and high-order repeats (HOR) and its structure for centromeric region of human genome in GenBank data and to give a preliminary insight into relevant actual theoretical literature.

LEARNING OUTCOMES AT THE LEVEL OF THE PROGRAMME:
1. KNOWLEDGE AND UNDERSTANDING
1.3. demonstrate a thorough knowledge of the most important physics theories (logical and mathematical structure, experimental support, described physical phenomena)
1.4. describe the state of the art in - at least- one of the presently active physics specialities;
2. APPLYING KNOWLEDGE AND UNDERSTANDING
2.3. apply standard methods of mathematical physics, in particular mathematical analysis and linear algebra and corresponding numerical methods;
3. MAKING JUDGMENTS:
3.3. develop a personal sense of responsibility, given the free choice of elective/optional courses;
4. COMUNICATION SKILLS
4.2. present one's own research or literature search results to professional as well as to lay audiences
4.3. develop the written and oral English language communication skills that are essential for pursuing a career in physics;
5. LEARNING SKILLS:
5.1. search for and use physical and other technical literature, as well as any other sources of information relevant to research work and technical project development (good knowledge of technical English is required);
5.4. participate in projects which require advanced skills in modelling, analysis, numerical calculations and use of technologies;

LEARNING OUTCOMES SPECIFIC FOR THE COURSE
Upon completing the course, students will be able to:
* use and analyse GenBank database;
* do an automatic annotation of repetitive DNA using BLAST routine;
* partially identify High-order repeats (HORs) using RepeatMasker;
* describe the Key-string algorithm (KSA) and use it to completely identify HORs;
* describe the Global Repeat Map algorithm and use it to completely identify HORs;
* describe algorithms based on frequency analysis and to use them in genome base analysis.

COURSE DESCRIPTION
1. Introduction to GenBank database, usage and analysis;
2. Automatic annotation of repetitive DNA using BLAST program;
3. Partial identification of HORs using RepeatMasker;
4. Complete identification of HORs using the Key-string Algorithm (KSA) and the Global Repeat Map (GRM);
5. Analysis of repetitive and HOR structure and significant substructures using the GRM algorithm;
6. Algorithms based on frequency analysis.

REQUIREMENTS FOR STUDENTS:
Students are required to attend classes, to participate in exercises and to solve problems and quizzes during the semester.

GRADING AND ASSESSING THE WORK OF STUDENTS
It includes all elements of monitoring student achievements during the semester plus one final oral exam.
Literature:
  1. S.A. Krawetz, D.D. Womble, Introduction to Bioinformatics ((Humana Press, Totowa, 2003)
  2. G. Benson, Tandem Repeats Finder: a program to analyze DNA sequencesNucleic Acids
    Res.27, 573 (1999).
  3. M. Rosandić, V. Paar, I. Basar, Key-string segmentation algorithm, J. Theor. Biol. 221, 29
    (2003).
  4. M. Glunčić, V. Paar (2012) Direct mapping of symbolic DNA sequence into frequency domain in Global Repeat Map (GRM) algorith. Nucleic Acid Res doi: 10.1093/nar/gks721.
Prerequisit for:
Enrollment :
Passed : Classical Mechanics 2
9. semester
Izborni predmeti - Mandatory studij - Physics
Consultations schedule:

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