DD2404 Applied Bioinformatics 7.5 credits
Bioinformatics has become an important tool for handling and utilizing the large sets of valuable data produced in Molecular Biology. Computerized analysis has a role both as support for wet-lab projects and as a means of extracting knowledge from already available datasets. The fast-growing amount of data makes it necessary to be able to automate analysis and make analysis on a very large scale. This course aims to introduce techniques for meeting this challenge.
Education cycleSecond cycle
Main field of studyBiotechnology
Computer Science and Engineering
Information and Communication Technology
Grading scaleA, B, C, D, E, FX, F
Autumn 18 P2 (7.5 credits)
Language of instruction
Form of study
Number of places
Lars Arvestad <email@example.com>
Searchable for students from year 3 and for students admitted to a master programmes.
Part of programme
- Master's Programme, Computer Science, 120 credits, year 1, CSDA, Conditionally Elective
- Master's Programme, Computer Science, 120 credits, year 2, CSDA, Conditionally Elective
- Master's Programme, Computer Simulations for Science and Engineering, 120 credits, year 2, Optional
- Master's Programme, Machine Learning, 120 credits, year 1, Conditionally Elective
- Master's Programme, Machine Learning, 120 credits, year 2, Conditionally Elective
- Master's Programme, Medical Engineering, 120 credits, year 1, Conditionally Elective
- Master's Programme, Medical Engineering, 120 credits, year 2, Conditionally Elective
Intended learning outcomes
After completion of this course, you will be able to
- structure data for efficient computerized storage and analysis
- use relational databases
- create your own relational databases
- use a scripting language to solve every-day problems in Bioinformatics
- use important Bioinformatic software libraries to quickly find solutions for tedious programming problems.
Course main content
Working in Unix. A quick introduction to Python. Good practice for scientific programming. Important modules for scientific programming.
Terminology and methods in Bioinformatics. Sources of data in Bioinformatics. Databases and basic SQL.
Some of the course contents is useful in many contexts, but we will focus on applications in Bioinformatics.
Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.
For those already studying at KTH: introductory computer programming, for example DD1310, DD1321 or DD1322.
The course literature will be announced at the home page for the course at least 4 weeks before course start.
- LAB1 - Laboratory Assignments, 4.5, grading scale: A, B, C, D, E, FX, F
- PRO1 - Project, 3.0, grading scale: P, F
In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.
Lars Arvestad, e-post: firstname.lastname@example.org
Arvind Kumar <email@example.com>
This course replaces the course DD2397 with the same name from autumn term 2012.
DD2399 Omic Data and Systems Biology
Course syllabus valid from: Autumn 2012.
Examination information valid from: Spring 2019.