|UMF011 - Introduction to bioinformatics
5,0 Credits (ECTS 7,5)
|Grading: UG - Fail, pass
Department: 0345 - MEDICINSK OCH FYSIOLOGISK KEMI GU
Teaching language: English
15 Oct 2005 pm V
TM Teknisk matematik, Year 2 (elective)
TITEA SOFTWARE ENGINEERING - Software development and management, Year 4 (elective)
TITEA SOFTWARE ENGINEERING - Data communication, Year 4 (elective)
TITEA SOFTWARE ENGINEERING - Embedded systems, Year 4 (elective)
TITEA SOFTWARE ENGINEERING - Interaction design, Year 4 (elective)
TITEA SOFTWARE ENGINEERING - Interactive simulations, Year 4 (elective)
TITEA SOFTWARE ENGINEERING - Bioinformatics, Year 4 (compulsory)
TDATA COMPUTER SCIENCE AND ENGINEERING, Year 3 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING - Algorithms, Year 4 (elective)
BIMAS MSc PROGRAMME IN BIOINFORMATICS, Year 1 (compulsory)
Professor Tore Samuelsson
Introduction to bioinformatics
Eligibility:For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.
Course specific prerequisites
Applicants should have at least 3 years of previous studies in any of the fields biology, medicine, engineering, mathematics, statistics, or computing science. A first course in mathematics, in statistics, and in computer programming is recommended.
Experimental research in molecular biology has in recent years yielded a
wealth of information. Genomes are being mapped and sequenced at a high
rate, information about the three dimensional structure of an increasing
number of proteins is becoming available, and a large amount of gene
expression data is being collected. In this development new tools are
required to handle and analyze data. Bioinformatics, an
interdisciplinary field involving a collaboration between computer
scientists, mathematicians, statisticians and experimental biologists,
has therefore become a rapidly expanding area of research. The aim of
the course is to provide an introduction to this area and it is assumes
that the student has a background in biology and/or mathematics/computer
The course gives an introduction to the field, with
particular emphasis on 1) molecular biology databases, 2) the
mathematical and computational problem of aligning biological
sequences, 3) hidden Markov models in biological sequence analysis, 4)
statistical analysis of gene expression data and 5) the basics of
structural bioinformatics. The course will also introduce the student to
perl programming for bioinformatics.
At the end of the course, students should:
be aware of the three kingdoms of life and fundamental evolutionary
mechanisms; understand basic properties of nucleic acids and proteins,
understand the flow of genetic information in the cell; be familiar with
the processes of of DNA replication, transcription and translation; know
examples of how gene expression is controlled;
- become familiar with the different kinds of molecular biology data,
the basic databases as well as web tools to query those databases. The
exercises will also illustrate the complexity of molecular biology data
that is stored in such databases.
- be familiar with the concepts of orthology and paralogy; know basic
principles of sequence analysis, know the dynamic programming algorithm
for optimal local or global alignment of two biological sequences; have
experience from program code implementing such an algorithm; know basic
principles of algorithms to seach sequence database for similarity; know
basic principles of multiple alignments and profiles.
- understand technology of DNA microarrays; know statistical approaches
to the analysis of microarray data.
- be familiar with the basic features of protein conformation, and some
properties of the amino acid building blocks; be able to recognise
common protein secondary structure elements and understand how these can
be recognised automatically; be aware of some common secondary structure
motifs and of alternative structural classification hierarchies;
understand the objectives and the approaces to protein structure prediction
- know basic principles of hidden Markov models and their use in
biological sequence analysis.
- be able to understand and write simple code in the perl programming
language for bioinformatics.
Lectures and supervised computer laborations.
Preliminary course book:
Introduction to Bioinformatics, by Arthur Lesk.
Computer laborations and written exam.