Bioinformatics 420-IS1-3BIO

Profile of studies: general-academic
Form of study: full-time
Course type: optional
Field: Natural and exact sciences, discipline: Informatics.
Year of study / semester 3 / 5
Prerequisites: (the so-called sequential system of classes and exams):

Introductory subjects:
Fundamentals of structural programming
Introduction to object-oriented programming
Advanced programming
Databases

Lecture: 15h Laboratory: 30h
Teaching methods: Teaching materials are prepared in pdf slide format and presented during lectures. Laboratory instructions are made available to students at each class. Consultations are also provided.
ECTS credits: 4
Balance of student workload:
Attendance in classes:
- lecture 15h
- laboratory 30h
Preparation for classes:
- lecture 0h
- laboratory 10h
Familiarisation with the literature: 5h
Reports, class reports, homework: 25h
Preparation for the colloquium: 10h
Participation in consultations: 5h
Quantitative indicators:

Student workload related to classes:
- activities requiring direct participation of the teacher: 50h, 2ECTS
- individual work: 50h, 2 ECTS

Type of course

elective courses

Mode

(in Polish) w sali

Requirements

Introduction to Structured Programming
Advanced Programming
Introduction to Object-Oriented Programming

Prerequisites

Discrete Mathematics
Elements of Logic and Set Theory

Prerequisites (description)

Assumptions and objectives of the course The aim of the course is to show practical applications of various algorithmic methods and IT tools in scientific applications on the example of biology and medicine. The main emphasis is placed on the applications of data analysis, machine learning and the use of programming languages used in data analysis: R and Python.

Course coordinators

Witold Rudnicki

Learning outcomes

Learning outcomes of the course:

1. knows the basics of selected bioinformatics languages. KA6_WG4

2. knows fundamental issues and problems of bioinformatics, in particular selected artificial intelligence algorithms used in medical and biological data analysis. KA6_WG11

3. is able to program in selected programming languages used in bioinformatics KA6_U01, KA6_UO2, KA6_UK3

4. is able to search genetic databases, analyze simple bioinformatics problems and find their solution using appropriate programming language and the Internet. KA6_U01, KA6_UK3

5 Be able to apply and combine into a single protocol the available bioinformatics tools to develop experimental results. KA6_U01, KA6_UK3

6. recognizes the benefits and importance to society of using information technology tools to solve problems in biology and medicine. KA6_KO1, KA6_UU1

Assessment criteria

General form of assessment: written examination end results of the projects.

Bibliography

Core literature:
Programming in R : data analysis, calculations, simulations / Marek Gągolewski., 2014
Python for everyone : programming basics. / Michael Dawson
Podstawy bioinformatyki / Jin Xiong, Warszawa : Wydawnictwa Uniwersytetu Warszawskiego, 2009.
Bioinformatics and molecular evolution / Paul G. Higgs, Teresa K. Attwood 2008
Supplementary literature:
Introductory Bioinformatics, Fourth Edition. Stefanie Hartmann, Joachim Selbig
Bioinformatics and Functional Genomics, Second Edition, Jonathan Pevsner.
Bioinformatics for Dummies, Second Edition, Jean-Michel Claverie and Cedric Notredame
http://pl.python.org/kursy,jezyka.html
http://www.r-project.org/

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 420-IS1-3BIO in USOSweb