A Graduate Course: |
Statistical Genetics and Bayesian Networks (7.5 p)
This course is of interest for geneticists, statisticians and computer scientists who work with,e.g., modelling of highly complex systems, genetic regulatory networks and genetic data analysis and need understanding of statistical models using probabilities factorized according to directed acyclic graphs (DAGs) and the algorithms for the updating of probabilistic uncertainty in response to evidence, and statistical learning of model parameters and structures.
(I) Probability and statistics basics
(II) definition and basic properrties of Bayesian networks
(III) Further properties of Bayesian networks:
The textbook is :
Another textbook :
Credit points : 7.5 p.
Examination : Homework assignments submitted to the examiner as a report .
THE COURSE FLYER : click
FIRST LECTURE: THURSDAY 8th of April
HOMEWORK SET 1. click
SECOND LECTURE: TUESDAY 13th of April
HOMEWORK SET 2. click
THIRD LECTURE: THURSDAY 22ND of April
HOMEWORK SET 3. click
FOURTH LECTURE: THURSDAY 29ND of April , 13.15, room 3733, dept. of math.
HOMEWORK SET 4. click
FIFTH LECTURE: TUESDAY 4TH of May, , 10.15, room 3733, dept. of math.
HOMEWORK SET 5. click
HANDOUT ON LEARNING click
SIXTH LECTURE: TUESDAY 11TH of May, 10.15, room 3733, dept. of math.HOMEWORK SET 6. click
SEVENTH LECTURE: THURSDAY 20TH of May, 13.15, room 3733, dept. of math.HOMEWORK SET 7. click
EIGHTH (final) LECTURE: THURSDAY 27TH of May, 13.15, room 3733, dept. of math.HOMEWORK SET 8. click
NINTH (presentations) LECTURE: (to be announced), 13.15, room 3733, dept. of math.
Course schedule and information
Timo Koski Lecturer and Examiner
Department of Mathematics
Royal Institute of Technology
SE-100 44 Stockholm
Phone: +46-8-790 71 34
|Published by: Timo Koski