FI:PV269 Adv. methods in bioinformatics - Course Information

PV269 Advanced methods in bioinformatics

Extent and Intensity

2/0/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

Teacher(s)

doc. Ing. Matej Lexa, Ph.D. (lecturer)
Mgr. Monika Čechová, Ph.D. (seminar tutor)
doc. RNDr. David Šafránek, Ph.D. (alternate examiner)

Guaranteed by

doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics

Timetable

Tue 10:00–11:50 B311

Prerequisites

The student is expected to have basic knowlege in bioinformatics. They must have passed IV108. Previous study of IV107, PA052 a PB050 is recommended.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Image Processing and Analysis (programme FI, N-VIZ)
• Bioinformatics and systems biology (programme FI, N-UIZD)
• Computer Games Development (programme FI, N-VIZ_A)
• Computer Graphics and Visualisation (programme FI, N-VIZ_A)
• Computer Networks and Communications (programme FI, N-PSKB_A)
• Cybersecurity Management (programme FI, N-RSSS_A)
• Formal analysis of computer systems (programme FI, N-TEI)
• Graphic design (programme FI, N-VIZ)
• Graphic Design (programme FI, N-VIZ_A)
• Hardware Systems (programme FI, N-PSKB_A)
• Hardware systems (programme FI, N-PSKB)
• Image Processing and Analysis (programme FI, N-VIZ_A)
• Information security (programme FI, N-PSKB)
• Informatics (programme FI, B-INF) (2)
• Informatics in education (programme FI, B-IVV) (2)
• Information Security (programme FI, N-PSKB_A)
• Quantum and Other Nonclassical Computational Models (programme FI, N-TEI)
• Computer graphics and visualisation (programme FI, N-VIZ)
• Computer Networks and Communications (programme FI, N-PSKB)
• Principles of programming languages (programme FI, N-TEI)
• Programming and development (programme FI, B-PVA)
• Cybersecurity management (programme FI, N-RSSS)
• Services development management (programme FI, N-RSSS)
• Software Systems Development Management (programme FI, N-RSSS)
• Services Development Management (programme FI, N-RSSS_A)
• Software Systems Development Management (programme FI, N-RSSS_A)
• Software Systems (programme FI, N-PSKB_A)
• Software systems (programme FI, N-PSKB)
• Machine learning and artificial intelligence (programme FI, N-UIZD)
• Teacher of Informatics and IT administrator (programme FI, N-UCI)
• Informatics for secondary school teachers (programme FI, N-UCI) (2)
• Computer Games Development (programme FI, N-VIZ)
• Processing and analysis of large-scale data (programme FI, N-UIZD)
• Natural language processing (programme FI, N-UIZD)

Course objectives

To acquire practical skills in bioinformatics beyond the scope of bachelor courses, extending theoretical topics from IV108.

Learning outcomes

The student will be able to choose appropriate computational methods for a given problem; obtain and prepare relevant data; carry out necessary computation using their own or publicly available programs.

Syllabus

• Genomic sequences
• - Advanced techniques for NGS data
• - Sequence motif detection and genome annotation
• - Advanced work with genome browsers
• Proteins
• - Hidden Markov models (HMM)
• - Protein structure analysis

Literature

• Next-generation DNA sequencing informatics. Edited by Stuart M. Brown. Second edition. Cold Spring Harbor: Cold Spring Harbor Laboratory Press, 2015, xiv, 402. ISBN 9781621821236. info
• ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info

Teaching methods

a combination of short lectures, exercises and homework

Assessment methods

Graded exercises; written exam (zk) or project (k)

Language of instruction

Czech

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (Spring 2021, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2021/PV269