Bioinformatics (2VO)
| Course no.: |
365.038 |
| Lecturer: |
Josef Hochreiter
|
| Times/locations: |
Thur 15:30-17:00, HS 17
Start: Oct 7, 2010 |
| Mode: |
VO, 2h, weekly |
| Registration: |
KUSSS |
| Written examination: |
Tues 25.10.2011, 13:45-15:15, MT 130, registration via KUSSS |
Lecture Notes:
R code chunks for the class:
Videos presented during the class:
For further information see also:
Motivation:
The 21st century is perceived as the century of life sciences:
Pharmaceutical industries are going to proliferate as the number of old
people who need medication increases.
We are witnessing a revolution in biology and medicine as new molecular
measurement techniques are developed. A doctor no longer examines a tumour
at the microscopic level but analyses the pattern of its gene activation.
Are genes activated that promote metastasis, that indicate a certain
therapy, that indicate aggressive growth? A doctor cannot screen all
30,000 genes of the human genome without electronic help- and it is there
that bioinformatics comes into play. Bioinformatics approaches are of
crucial importance for identifying relevant genes and unusual activation
patterns, they correlate the gene activity of new patients to known
patterns.
This course provides insights into basic bioinformatics algorithms
including pairwise sequence comparison, multiple sequence alignment,
constructing phylogenetic trees (genealogies of animals or viruses like
bird flu), classification of DNA or protein sequences (support vector
machines and neural networks), sequence modelling (Hidden Markov Models)
and selection of important sequence characteristics or regions. All
presented algorithms are state of the art. Support vector machines, for
example, are currently under investigation for their ability to predict
therapy results from gene expression profiles of tumours and thus to help
choose the most promising therapy for each patient.
