FI:PA055 Visualizing Complex Data - Course Information
PA055 Visualizing Complex Data
Faculty of InformaticsAutumn 2010
- Extent and Intensity
- 1/1. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 10:00–11:50 B116
- Prerequisites
- Elementary programming skills and interest in R and Processing (scripting and programming languages)
- 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
- Applied Informatics (programme FI, B-AP)
- Applied Informatics (programme FI, N-AP)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, B-AP)
- Bioinformatics (programme FI, N-AP)
- Economic Information Systems (programme ESF, B-SI)
- Information Systems (programme FI, N-IN)
- Informatics with another discipline (programme FI, B-BI)
- Informatics with another discipline (programme FI, B-FY)
- Informatics with another discipline (programme FI, B-GE)
- Informatics with another discipline (programme FI, B-GK)
- Informatics with another discipline (programme FI, B-CH)
- Informatics with another discipline (programme FI, B-IO)
- Informatics with another discipline (programme FI, B-MA)
- Informatics with another discipline (programme FI, B-TV)
- Informatics (eng.) (programme FI, D-IN4)
- Informatics (programme FI, B-IN)
- Informatics (programme FI, D-IN4)
- Informatics (programme FI, N-IN)
- Mathematical Informatics (programme FI, B-IN)
- Mathematics with Informatics (programme PřF, N-MA)
- Parallel and Distributed Systems (programme FI, B-IN)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics and Image Processing (programme FI, B-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, B-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems and Technologies (eng.) (programme FI, D-IN4)
- Computer Systems and Technologies (programme FI, D-IN4)
- Computer Systems and Data Processing (programme FI, B-IN)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Programmable Technical Structures (programme FI, B-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Theoretical Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- Course objectives
- Students will get aquainted with complex data in bioinformatics and selected other disciplines and their visualization, using examples in R and PROCESSING languages or scientific literature.
At the end of the course they will be able to:
explain the basic principles and goals of visualization
prepare data for visualization
evaluate existing visualizations
create their own static or interactive visualization - Syllabus
- 1. Introduction to data visualization
- 2. The R computing environment and its visualization tools
- 3. The Processing computing environment and its visualization tools
- 4. Visualization and data types in bioinformatics and system biology
- 4. Data preprocessing (dimensionality estimates and reduction, PCA, clustering, similarity metrics, multidimensional scaling)
- 6. Review of isualization techniques (plots, histograms, trees and other graphs, maps, hybrid visualization)
- 7. Examples of visualization in bioinformatics, systems biology and other disciplines
- Literature
- Handbook of data visualization. Edited by Chun-houh Chen - Wolfgang Härdle - Antony Unwin. Berlin: Springer, 2008, xiii, 936. ISBN 9783540330370. info
- SARKAR, Deepayan. Lattice : multivariate data visualization with R. New York: Springer, 2008, xvii, 265. ISBN 9780387759685. info
- FRY, Ben. Visualizing data. Beijing: O'Reilly, 2008, xiii, 366. ISBN 9780596514556. info
- Teaching methods
- lectures, computer exercises, short student presentations
- Assessment methods
- short exercises, group project and a written exam
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2010, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2010/PA055